Merge remote-tracking branch 'origin/more_datasets' into bits_and_tpu

benchmark.py

@@ -170,7 +170,9 @@ def profile_deepspeed(model, input_size=(3, 224, 224), batch_size=1, detailed=Fa
     return macs, 0  # no activation count in DS
 
 
-def profile_fvcore(model, input_size=(3, 224, 224), batch_size=1, detailed=False):
+def profile_fvcore(model, input_size=(3, 224, 224), batch_size=1, detailed=False, force_cpu=False):
+    if force_cpu:
+        model = model.to('cpu')
     device, dtype = next(model.parameters()).device, next(model.parameters()).dtype
     example_input = torch.ones((batch_size,) + input_size, device=device, dtype=dtype)
     fca = FlopCountAnalysis(model, example_input)
@@ -277,14 +279,20 @@ class InferenceBenchmarkRunner(BenchmarkRunner):
             img_size=self.input_size[-1],
             param_count=round(self.param_count / 1e6, 2),
         )
-        if not self.scripted:
-            if has_deepspeed_profiling:
-                macs, _ = profile_deepspeed(self.model, self.input_size)
-                results['gmacs'] = round(macs / 1e9, 2)
-            elif has_fvcore_profiling:
-                macs, activations = profile_fvcore(self.model, self.input_size)
-                results['gmacs'] = round(macs / 1e9, 2)
-                results['macts'] = round(activations / 1e6, 2)
+
+        retries = 0 if self.scripted else 2  # skip profiling if model is scripted
+        while retries:
+            retries -= 1
+            try:
+                if has_deepspeed_profiling:
+                    macs, _ = profile_deepspeed(self.model, self.input_size)
+                    results['gmacs'] = round(macs / 1e9, 2)
+                elif has_fvcore_profiling:
+                    macs, activations = profile_fvcore(self.model, self.input_size, force_cpu=not retries)
+                    results['gmacs'] = round(macs / 1e9, 2)
+                    results['macts'] = round(activations / 1e6, 2)
+            except RuntimeError as e:
+                pass
 
         _logger.info(
             f"Inference benchmark of {self.model_name} done. "
@@ -472,7 +480,12 @@ def _try_run(model_name, bench_fn, initial_batch_size, bench_kwargs):
             results = bench.run()
             return results
         except RuntimeError as e:
-            print(f'Error: {str(e)} while running benchmark. Reducing batch size to {batch_size} for retry.')
+            e_str = str(e)
+            print(e_str)
+            if 'channels_last' in e_str:
+                print(f'Error: {model_name} not supported in channels_last, skipping.')
+                break
+            print(f'Error: "{e_str}" while running benchmark. Reducing batch size to {batch_size} for retry.')
         batch_size = decay_batch_exp(batch_size)
     return results
 
@@ -521,7 +534,7 @@ def benchmark(args):
     param_count = model_results.pop('infer_param_count', model_results.pop('train_param_count', 0))
     model_results.setdefault('param_count', param_count)
     model_results.pop('train_param_count', 0)
-    return model_results
+    return model_results if model_results['param_count'] else dict()
 
 
 def main():
@@ -555,7 +568,9 @@ def main():
                     continue
                 args.model = m
                 r = benchmark(args)
-                results.append(r)
+                if r:
+                    results.append(r)
+                time.sleep(10)
         except KeyboardInterrupt as e:
             pass
         sort_key = 'infer_samples_per_sec'

results/model_benchmark_amp_nchw_rtx3090.csv

@@ -241,6 +241,7 @@ repvgg_b1,1595.1,160.478,256,224,13.16,10.64,57.42
 xcit_tiny_24_p16_224_dist,1586.68,161.331,256,224,2.34,11.82,12.12
 xcit_tiny_24_p16_224,1585.43,161.458,256,224,2.34,11.82,12.12
 xcit_small_12_p16_224_dist,1555.24,164.59,256,224,4.82,12.58,26.25
+lambda_resnet50ts,1554.98,164.616,256,256,5.07,17.48,21.54
 xcit_small_12_p16_224,1551.41,164.997,256,224,4.82,12.58,26.25
 gluon_resnet101_v1c,1549.68,165.185,256,224,8.08,17.04,44.57
 resnest50d,1546.83,165.485,256,224,5.4,14.36,27.48
@@ -262,6 +263,7 @@ densenet201,1416.48,180.718,256,224,4.34,7.85,20.01
 resmlp_36_224,1415.51,180.84,256,224,8.91,16.33,44.69
 resmlp_36_distilled_224,1415.35,180.86,256,224,8.91,16.33,44.69
 gluon_resnet101_v1s,1409.69,181.589,256,224,9.19,18.64,44.67
+lamhalobotnet50ts_256,1390.79,184.054,256,256,5.02,18.44,22.57
 nf_resnet50,1387.87,184.443,256,288,6.88,18.37,25.56
 ecaresnet101d,1376.05,186.03,256,224,8.08,17.07,44.57
 vgg16,1375.43,186.112,256,224,15.47,13.56,138.36
@@ -289,6 +291,7 @@ gluon_resnext101_32x4d,1262.61,202.744,256,224,8.01,21.23,44.18
 swsl_resnext101_32x4d,1261.41,202.934,256,224,8.01,21.23,44.18
 vgg16_bn,1259.82,203.192,256,224,15.5,13.56,138.37
 repvgg_b2g4,1250.78,204.659,256,224,12.63,12.9,61.76
+halo2botnet50ts_256,1247.07,205.268,256,256,5.02,21.78,22.64
 swin_tiny_patch4_window7_224,1247.03,205.273,256,224,4.51,17.06,28.29
 twins_pcpvt_small,1237.18,206.911,256,224,3.83,18.08,24.11
 regnety_080,1231.05,207.941,256,224,8.0,17.97,39.18

results/model_metadata_in1k.csv

@@ -150,6 +150,7 @@ gluon_seresnext50_32x4d,in1k
 gluon_xception65,in1k
 gmixer_24_224,in1k
 gmlp_s16_224,in1k
+halo2botnet50ts_256,in1k
 halonet26t,in1k
 halonet50ts,in1k
 haloregnetz_b,in1k
@@ -180,6 +181,8 @@ jx_nest_small,in1k
 jx_nest_tiny,in1k
 lambda_resnet26rpt_256,in1k
 lambda_resnet26t,in1k
+lambda_resnet50ts,in1k
+lamhalobotnet50ts_256,in1k
 legacy_senet154,in1k
 legacy_seresnet101,in1k
 legacy_seresnet152,in1k

results/results-imagenet-a-clean.csv

@@ -14,8 +14,8 @@ vit_base_patch16_384,97.830,2.170,99.670,0.330,86.86,384,1.000,bicubic
 tf_efficientnetv2_l_in21ft1k,97.680,2.320,99.670,0.330,118.52,480,1.000,bicubic
 tf_efficientnetv2_xl_in21ft1k,97.670,2.330,99.490,0.510,208.12,512,1.000,bicubic
 swin_large_patch4_window7_224,97.660,2.340,99.580,0.420,196.53,224,0.900,bicubic
-ig_resnext101_32x48d,97.640,2.360,99.710,0.290,828.41,224,0.875,bilinear
 vit_large_patch16_224,97.640,2.360,99.590,0.410,304.33,224,0.900,bicubic
+ig_resnext101_32x48d,97.640,2.360,99.710,0.290,828.41,224,0.875,bilinear
 tf_efficientnet_b6_ns,97.630,2.370,99.580,0.420,43.04,528,0.942,bicubic
 dm_nfnet_f6,97.610,2.390,99.550,0.450,438.36,576,0.956,bicubic
 dm_nfnet_f4,97.570,2.430,99.510,0.490,316.07,512,0.951,bicubic
@@ -45,9 +45,9 @@ xcit_small_24_p16_384_dist,97.130,2.870,99.450,0.550,47.67,384,1.000,bicubic
 tf_efficientnet_b8_ap,97.110,2.890,99.660,0.340,87.41,672,0.954,bicubic
 eca_nfnet_l2,97.090,2.910,99.510,0.490,56.72,384,1.000,bicubic
 ecaresnet269d,97.090,2.910,99.470,0.530,102.09,352,1.000,bicubic
-beit_base_patch16_224,97.080,2.920,99.610,0.390,86.53,224,0.900,bicubic
 cait_s24_384,97.080,2.920,99.430,0.570,47.06,384,1.000,bicubic
 tf_efficientnet_b6_ap,97.080,2.920,99.620,0.380,43.04,528,0.942,bicubic
+beit_base_patch16_224,97.080,2.920,99.610,0.390,86.53,224,0.900,bicubic
 xcit_large_24_p8_224_dist,97.060,2.940,99.420,0.580,188.93,224,1.000,bicubic
 resnetv2_152x2_bitm,97.030,2.970,99.590,0.410,236.34,448,1.000,bilinear
 dm_nfnet_f2,97.030,2.970,99.440,0.560,193.78,352,0.920,bicubic
@@ -79,8 +79,8 @@ tf_efficientnet_b5_ap,96.680,3.320,99.460,0.540,30.39,456,0.934,bicubic
 vit_small_r26_s32_384,96.680,3.320,99.570,0.430,36.47,384,1.000,bicubic
 pit_b_distilled_224,96.670,3.330,99.350,0.650,74.79,224,0.900,bicubic
 tf_efficientnet_b6,96.670,3.330,99.370,0.630,43.04,528,0.942,bicubic
-resmlp_big_24_224_in22ft1k,96.620,3.380,99.510,0.490,129.14,224,0.875,bicubic
 resnest200e,96.620,3.380,99.350,0.650,70.20,320,0.909,bicubic
+resmlp_big_24_224_in22ft1k,96.620,3.380,99.510,0.490,129.14,224,0.875,bicubic
 xcit_medium_24_p16_224_dist,96.600,3.400,99.270,0.730,84.40,224,1.000,bicubic
 swsl_resnext101_32x16d,96.600,3.400,99.530,0.470,194.03,224,0.875,bilinear
 regnetz_d,96.590,3.410,99.380,0.620,27.58,320,0.950,bicubic
@@ -95,10 +95,10 @@ vit_base_patch32_384,96.500,3.500,99.410,0.590,88.30,384,1.000,bicubic
 resmlp_big_24_distilled_224,96.470,3.530,99.310,0.690,129.14,224,0.875,bicubic
 vit_base_patch16_224_miil,96.440,3.560,99.310,0.690,86.54,224,0.875,bilinear
 swsl_resnext101_32x4d,96.420,3.580,99.470,0.530,44.18,224,0.875,bilinear
-xcit_large_24_p8_224,96.400,3.600,98.980,1.020,188.93,224,1.000,bicubic
 xcit_small_24_p8_224,96.400,3.600,99.140,0.860,47.63,224,1.000,bicubic
-crossvit_15_dagger_408,96.390,3.610,99.160,0.840,28.50,408,1.000,bicubic
+xcit_large_24_p8_224,96.400,3.600,98.980,1.020,188.93,224,1.000,bicubic
 cait_s24_224,96.390,3.610,99.150,0.850,46.92,224,1.000,bicubic
+crossvit_15_dagger_408,96.390,3.610,99.160,0.840,28.50,408,1.000,bicubic
 tf_efficientnet_b3_ns,96.370,3.630,99.350,0.650,12.23,300,0.904,bicubic
 resnet152d,96.350,3.650,99.390,0.610,60.21,320,1.000,bicubic
 regnety_160,96.340,3.660,99.330,0.670,83.59,288,1.000,bicubic
@@ -112,8 +112,8 @@ xcit_small_24_p16_224_dist,96.210,3.790,99.210,0.790,47.67,224,1.000,bicubic
 tf_efficientnet_b4_ap,96.170,3.830,99.280,0.720,19.34,380,0.922,bicubic
 efficientnet_b4,96.160,3.840,99.200,0.800,19.34,384,1.000,bicubic
 twins_svt_base,96.160,3.840,99.060,0.940,56.07,224,0.900,bicubic
-deit_base_patch16_384,96.150,3.850,99.140,0.860,86.86,384,1.000,bicubic
 twins_pcpvt_large,96.150,3.850,99.190,0.810,60.99,224,0.900,bicubic
+deit_base_patch16_384,96.150,3.850,99.140,0.860,86.86,384,1.000,bicubic
 dm_nfnet_f0,96.140,3.860,99.250,0.750,71.49,256,0.900,bicubic
 nfnet_l0,96.130,3.870,99.240,0.760,35.07,288,1.000,bicubic
 resnetv2_50x1_bit_distilled,96.110,3.890,99.280,0.720,25.55,224,0.875,bicubic
@@ -140,16 +140,16 @@ vit_large_patch32_384,95.830,4.170,99.150,0.850,306.63,384,1.000,bicubic
 xcit_tiny_24_p8_224_dist,95.820,4.180,99.210,0.790,12.11,224,1.000,bicubic
 regnetz_c,95.800,4.200,99.100,0.900,13.46,320,0.940,bicubic
 ssl_resnext101_32x16d,95.800,4.200,99.180,0.820,194.03,224,0.875,bilinear
-resnet61q,95.790,4.210,98.990,1.010,36.85,288,1.000,bicubic
 twins_pcpvt_base,95.790,4.210,99.130,0.870,43.83,224,0.900,bicubic
+resnet61q,95.790,4.210,98.990,1.010,36.85,288,1.000,bicubic
 tf_efficientnet_b2_ns,95.750,4.250,99.120,0.880,9.11,260,0.890,bicubic
 gc_efficientnetv2_rw_t,95.740,4.260,99.020,0.980,13.68,288,1.000,bicubic
 tresnet_m,95.730,4.270,99.030,0.970,31.39,224,0.875,bilinear
 pnasnet5large,95.720,4.280,98.920,1.080,86.06,331,0.911,bicubic
 efficientnet_b3,95.720,4.280,99.040,0.960,12.23,320,1.000,bicubic
 nasnetalarge,95.680,4.320,98.930,1.070,88.75,331,0.911,bicubic
-crossvit_15_dagger_240,95.670,4.330,98.820,1.180,28.21,240,0.875,bicubic
 xcit_tiny_24_p8_224,95.670,4.330,99.050,0.950,12.11,224,1.000,bicubic
+crossvit_15_dagger_240,95.670,4.330,98.820,1.180,28.21,240,0.875,bicubic
 vit_small_r26_s32_224,95.640,4.360,99.190,0.810,36.43,224,0.900,bicubic
 pit_b_224,95.630,4.370,98.670,1.330,73.76,224,0.900,bicubic
 resnetv2_101,95.630,4.370,98.990,1.010,44.54,224,0.950,bicubic
@@ -160,8 +160,8 @@ ecaresnet101d,95.540,4.460,99.130,0.870,44.57,224,0.875,bicubic
 coat_lite_small,95.530,4.470,98.860,1.140,19.84,224,0.900,bicubic
 levit_384,95.530,4.470,99.050,0.950,39.13,224,0.900,bicubic
 xcit_small_24_p16_224,95.530,4.470,98.770,1.230,47.67,224,1.000,bicubic
-crossvit_base_240,95.520,4.480,98.820,1.180,105.03,240,0.875,bicubic
 xcit_medium_24_p16_224,95.520,4.480,98.770,1.230,84.40,224,1.000,bicubic
+crossvit_base_240,95.520,4.480,98.820,1.180,105.03,240,0.875,bicubic
 visformer_small,95.500,4.500,98.900,1.100,40.22,224,0.900,bicubic
 ecaresnet50t,95.500,4.500,99.120,0.880,25.57,320,0.950,bicubic
 ssl_resnext101_32x8d,95.470,4.530,99.120,0.880,88.79,224,0.875,bilinear
@@ -194,38 +194,41 @@ convmixer_1536_20,95.080,4.920,99.030,0.970,51.63,224,0.960,bicubic
 xcit_tiny_12_p8_224_dist,95.080,4.920,98.910,1.090,6.71,224,1.000,bicubic
 ecaresnet101d_pruned,95.070,4.930,98.980,1.020,24.88,224,0.875,bicubic
 vit_small_patch32_384,95.060,4.940,98.990,1.010,22.92,384,1.000,bicubic
-regnetz_b,95.060,4.940,99.050,0.950,9.72,288,0.940,bicubic
 legacy_senet154,95.060,4.940,98.830,1.170,115.09,224,0.875,bilinear
+regnetz_b,95.060,4.940,99.050,0.950,9.72,288,0.940,bicubic
 gluon_resnet152_v1s,95.050,4.950,98.930,1.070,60.32,224,0.875,bicubic
+halonet50ts,95.050,4.950,98.590,1.410,22.73,256,0.940,bicubic
 wide_resnet50_2,95.050,4.950,98.970,1.030,68.88,224,0.875,bicubic
 tnt_s_patch16_224,95.040,4.960,98.840,1.160,23.76,224,0.900,bicubic
-levit_256,95.030,4.970,98.890,1.110,18.89,224,0.900,bicubic
 seresnext50_32x4d,95.030,4.970,98.890,1.110,27.56,224,0.875,bicubic
-resnetv2_50x1_bitm,95.020,4.980,99.050,0.950,25.55,448,1.000,bilinear
+levit_256,95.030,4.970,98.890,1.110,18.89,224,0.900,bicubic
 tf_efficientnet_b3,95.020,4.980,98.910,1.090,12.23,300,0.904,bicubic
+resnetv2_50x1_bitm,95.020,4.980,99.050,0.950,25.55,448,1.000,bilinear
 vit_base_patch32_224,95.010,4.990,99.020,0.980,88.22,224,0.900,bicubic
 coat_mini,94.990,5.010,98.780,1.220,10.34,224,0.900,bicubic
 tresnet_m_448,94.990,5.010,98.980,1.020,31.39,448,0.875,bilinear
-halonet50ts,94.950,5.050,98.750,1.250,22.73,256,0.940,bicubic
 resnest50d_4s2x40d,94.950,5.050,99.070,0.930,30.42,224,0.875,bicubic
-gluon_seresnext101_64x4d,94.940,5.060,98.820,1.180,88.23,224,0.875,bicubic
 rexnet_200,94.940,5.060,99.000,1.000,16.37,224,0.875,bicubic
+gluon_seresnext101_64x4d,94.940,5.060,98.820,1.180,88.23,224,0.875,bicubic
 gluon_senet154,94.930,5.070,98.770,1.230,115.09,224,0.875,bicubic
 gluon_seresnext101_32x4d,94.920,5.080,98.810,1.190,48.96,224,0.875,bicubic
-resmlp_36_distilled_224,94.870,5.130,98.860,1.140,44.69,224,0.875,bicubic
 seresnet33ts,94.870,5.130,98.790,1.210,19.78,256,0.900,bicubic
+resmlp_36_distilled_224,94.870,5.130,98.860,1.140,44.69,224,0.875,bicubic
 gcresnet50t,94.860,5.140,98.800,1.200,25.90,256,0.900,bicubic
 ssl_resnext50_32x4d,94.860,5.140,98.870,1.130,25.03,224,0.875,bilinear
 tf_efficientnet_lite4,94.860,5.140,99.020,0.980,13.01,380,0.920,bilinear
 crossvit_small_240,94.830,5.170,99.020,0.980,26.86,240,0.875,bicubic
 resnest50d,94.830,5.170,98.880,1.120,27.48,224,0.875,bilinear
+lamhalobotnet50ts_256,94.800,5.200,98.550,1.450,22.57,256,0.950,bicubic
 sehalonet33ts,94.780,5.220,98.570,1.430,13.69,256,0.940,bicubic
-ecaresnetlight,94.770,5.230,98.800,1.200,30.16,224,0.875,bicubic
 resnest50d_1s4x24d,94.770,5.230,98.980,1.020,25.68,224,0.875,bicubic
+ecaresnetlight,94.770,5.230,98.800,1.200,30.16,224,0.875,bicubic
+lambda_resnet50ts,94.770,5.230,98.470,1.530,21.54,256,0.950,bicubic
+halo2botnet50ts_256,94.760,5.240,98.660,1.340,22.64,256,0.950,bicubic
 gluon_resnet152_v1d,94.750,5.250,98.740,1.260,60.21,224,0.875,bicubic
+xcit_tiny_12_p8_224,94.710,5.290,98.830,1.170,6.71,224,1.000,bicubic
 deit_small_distilled_patch16_224,94.710,5.290,99.030,0.970,22.44,224,0.900,bicubic
 haloregnetz_b,94.710,5.290,98.660,1.340,11.68,224,0.940,bicubic
-xcit_tiny_12_p8_224,94.710,5.290,98.830,1.170,6.71,224,1.000,bicubic
 gluon_resnet101_v1s,94.700,5.300,98.820,1.180,44.67,224,0.875,bicubic
 cspdarknet53,94.670,5.330,98.810,1.190,27.64,256,0.887,bilinear
 resmlp_big_24_224,94.650,5.350,98.490,1.510,129.14,224,0.875,bicubic
@@ -239,44 +242,44 @@ repvgg_b3,94.570,5.430,98.790,1.210,123.09,224,0.875,bilinear
 nf_resnet50,94.560,5.440,98.790,1.210,25.56,288,0.940,bicubic
 seresnet50,94.560,5.440,98.750,1.250,28.09,224,0.875,bicubic
 regnety_320,94.550,5.450,98.850,1.150,145.05,224,0.875,bicubic
-gluon_resnext101_32x4d,94.540,5.460,98.630,1.370,44.18,224,0.875,bicubic
 inception_resnet_v2,94.540,5.460,98.790,1.210,55.84,299,0.897,bicubic
+gluon_resnext101_32x4d,94.540,5.460,98.630,1.370,44.18,224,0.875,bicubic
 repvgg_b3g4,94.530,5.470,98.960,1.040,83.83,224,0.875,bilinear
 xcit_tiny_24_p16_224_dist,94.520,5.480,98.790,1.210,12.12,224,1.000,bicubic
-tf_efficientnet_b2_ap,94.490,5.510,98.620,1.380,9.11,260,0.890,bicubic
 convmixer_768_32,94.490,5.510,98.850,1.150,21.11,224,0.960,bicubic
-gcresnet33ts,94.480,5.520,98.780,1.220,19.88,256,0.900,bicubic
-gcresnext50ts,94.480,5.520,98.670,1.330,15.67,256,0.900,bicubic
+tf_efficientnet_b2_ap,94.490,5.510,98.620,1.380,9.11,260,0.890,bicubic
 regnety_120,94.480,5.520,98.810,1.190,51.82,224,0.875,bicubic
+gcresnext50ts,94.480,5.520,98.670,1.330,15.67,256,0.900,bicubic
+gcresnet33ts,94.480,5.520,98.780,1.220,19.88,256,0.900,bicubic
 cspresnext50,94.470,5.530,98.680,1.320,20.57,224,0.875,bilinear
-rexnet_150,94.470,5.530,98.790,1.210,9.73,224,0.875,bicubic
 ssl_resnet50,94.470,5.530,98.920,1.080,25.56,224,0.875,bilinear
+rexnet_150,94.470,5.530,98.790,1.210,9.73,224,0.875,bicubic
 resmlp_24_distilled_224,94.450,5.550,98.770,1.230,30.02,224,0.875,bicubic
-regnetx_320,94.440,5.560,98.730,1.270,107.81,224,0.875,bicubic
 resnetv2_50,94.440,5.560,98.730,1.270,25.55,224,0.950,bicubic
+regnetx_320,94.440,5.560,98.730,1.270,107.81,224,0.875,bicubic
 tf_efficientnetv2_b2,94.410,5.590,98.570,1.430,10.10,260,0.890,bicubic
 deit_small_patch16_224,94.400,5.600,98.690,1.310,22.05,224,0.900,bicubic
 tf_efficientnet_el,94.400,5.600,98.710,1.290,10.59,300,0.904,bicubic
 efficientnet_el_pruned,94.390,5.610,98.750,1.250,10.59,300,0.904,bicubic
-tf_efficientnet_b2,94.370,5.630,98.610,1.390,9.11,260,0.890,bicubic
 inception_v4,94.370,5.630,98.580,1.420,42.68,299,0.875,bicubic
+tf_efficientnet_b2,94.370,5.630,98.610,1.390,9.11,260,0.890,bicubic
 legacy_seresnext101_32x4d,94.350,5.650,98.630,1.370,48.96,224,0.875,bilinear
-gluon_seresnext50_32x4d,94.330,5.670,98.620,1.380,27.56,224,0.875,bicubic
 resnet50,94.330,5.670,98.440,1.560,25.56,224,0.950,bicubic
-dpn107,94.300,5.700,98.470,1.530,86.92,224,0.875,bicubic
+gluon_seresnext50_32x4d,94.330,5.670,98.620,1.380,27.56,224,0.875,bicubic
 ecaresnet26t,94.300,5.700,98.710,1.290,16.01,320,0.950,bicubic
-resnetrs50,94.290,5.710,98.640,1.360,35.69,224,0.910,bicubic
+dpn107,94.300,5.700,98.470,1.530,86.92,224,0.875,bicubic
 xception71,94.290,5.710,98.640,1.360,42.34,299,0.903,bicubic
+resnetrs50,94.290,5.710,98.640,1.360,35.69,224,0.910,bicubic
 resnet50d,94.270,5.730,98.720,1.280,25.58,224,0.875,bicubic
-cait_xxs36_224,94.260,5.740,98.710,1.290,17.30,224,1.000,bicubic
 gluon_xception65,94.260,5.740,98.570,1.430,39.92,299,0.903,bicubic
+cait_xxs36_224,94.260,5.740,98.710,1.290,17.30,224,1.000,bicubic
 skresnext50_32x4d,94.260,5.740,98.470,1.530,27.48,224,0.875,bicubic
 regnetx_120,94.240,5.760,98.670,1.330,46.11,224,0.875,bicubic
 dpn92,94.220,5.780,98.730,1.270,37.67,224,0.875,bicubic
 ecaresnet50d_pruned,94.210,5.790,98.730,1.270,19.94,224,0.875,bicubic
 mixnet_xl,94.200,5.800,98.340,1.660,11.90,224,0.875,bicubic
-gluon_resnet101_v1d,94.200,5.800,98.570,1.430,44.57,224,0.875,bicubic
 eca_resnet33ts,94.200,5.800,98.770,1.230,19.68,256,0.900,bicubic
+gluon_resnet101_v1d,94.200,5.800,98.570,1.430,44.57,224,0.875,bicubic
 resmlp_36_224,94.190,5.810,98.660,1.340,44.69,224,0.875,bicubic
 resnext50d_32x4d,94.190,5.810,98.570,1.430,25.05,224,0.875,bicubic
 tf_efficientnet_lite3,94.190,5.810,98.640,1.360,8.20,300,0.904,bilinear
@@ -289,8 +292,8 @@ regnety_064,94.150,5.850,98.740,1.260,30.58,224,0.875,bicubic
 vit_base_patch16_sam_224,94.150,5.850,98.670,1.330,86.57,224,0.900,bicubic
 efficientnet_b2_pruned,94.140,5.860,98.520,1.480,8.31,260,0.890,bicubic
 dpn98,94.120,5.880,98.580,1.420,61.57,224,0.875,bicubic
-nf_regnet_b1,94.120,5.880,98.620,1.380,10.22,288,0.900,bicubic
 regnetx_160,94.120,5.880,98.740,1.260,54.28,224,0.875,bicubic
+nf_regnet_b1,94.120,5.880,98.620,1.380,10.22,288,0.900,bicubic
 resnext50_32x4d,94.110,5.890,98.350,1.650,25.03,224,0.875,bicubic
 ese_vovnet39b,94.090,5.910,98.660,1.340,24.57,224,0.875,bicubic
 gluon_resnet152_v1b,94.080,5.920,98.460,1.540,60.19,224,0.875,bicubic
@@ -309,20 +312,21 @@ rexnet_130,93.900,6.100,98.400,1.600,7.56,224,0.875,bicubic
 regnetx_064,93.890,6.110,98.630,1.370,26.21,224,0.875,bicubic
 regnetx_080,93.870,6.130,98.520,1.480,39.57,224,0.875,bicubic
 regnety_040,93.860,6.140,98.640,1.360,20.65,224,0.875,bicubic
-efficientnet_em,93.840,6.160,98.810,1.190,6.90,240,0.882,bicubic
 repvgg_b2g4,93.840,6.160,98.600,1.400,61.76,224,0.875,bilinear
+efficientnet_em,93.840,6.160,98.810,1.190,6.90,240,0.882,bicubic
 gluon_resnext50_32x4d,93.820,6.180,98.410,1.590,25.03,224,0.875,bicubic
 lambda_resnet26t,93.820,6.180,98.650,1.350,10.96,256,0.940,bicubic
 pit_xs_distilled_224,93.820,6.180,98.670,1.330,11.00,224,0.900,bicubic
+eca_botnext26ts_256,93.790,6.210,98.500,1.500,10.59,256,0.950,bicubic
 resnext101_32x8d,93.790,6.210,98.580,1.420,88.79,224,0.875,bilinear
 gluon_resnet50_v1d,93.780,6.220,98.400,1.600,25.58,224,0.875,bicubic
 xception65,93.770,6.230,98.360,1.640,39.92,299,0.903,bicubic
 cspresnet50,93.750,6.250,98.630,1.370,21.62,256,0.887,bilinear
 gluon_resnet101_v1b,93.730,6.270,98.400,1.600,44.55,224,0.875,bicubic
-lambda_resnet26rpt_256,93.720,6.280,98.500,1.500,10.99,256,0.940,bicubic
-legacy_seresnext50_32x4d,93.720,6.280,98.580,1.420,27.56,224,0.875,bilinear
-res2net101_26w_4s,93.720,6.280,98.320,1.680,45.21,224,0.875,bilinear
 wide_resnet101_2,93.720,6.280,98.540,1.460,126.89,224,0.875,bilinear
+res2net101_26w_4s,93.720,6.280,98.320,1.680,45.21,224,0.875,bilinear
+legacy_seresnext50_32x4d,93.720,6.280,98.580,1.420,27.56,224,0.875,bilinear
+lambda_resnet26rpt_256,93.720,6.280,98.500,1.500,10.99,256,0.940,bicubic
 tf_efficientnet_b1_ap,93.710,6.290,98.360,1.640,7.79,240,0.882,bicubic
 dpn68b,93.680,6.320,98.530,1.470,12.61,224,0.875,bicubic
 gluon_resnet101_v1c,93.660,6.340,98.410,1.590,44.57,224,0.875,bicubic
@@ -331,31 +335,32 @@ gluon_resnet50_v1s,93.630,6.370,98.470,1.530,25.68,224,0.875,bicubic
 tf_efficientnet_b0_ns,93.620,6.380,98.640,1.360,5.29,224,0.875,bicubic
 resnet33ts,93.600,6.400,98.530,1.470,19.68,256,0.900,bicubic
 cait_xxs24_224,93.590,6.410,98.440,1.560,11.96,224,1.000,bicubic
-coat_tiny,93.580,6.420,98.410,1.590,5.50,224,0.900,bicubic
 hrnet_w44,93.580,6.420,98.700,1.300,67.06,224,0.875,bilinear
+coat_tiny,93.580,6.420,98.410,1.590,5.50,224,0.900,bicubic
 regnetx_040,93.550,6.450,98.560,1.440,22.12,224,0.875,bicubic
 hrnet_w32,93.520,6.480,98.440,1.560,41.23,224,0.875,bilinear
-dla102x,93.510,6.490,98.500,1.500,26.31,224,0.875,bilinear
 eca_halonext26ts,93.510,6.490,98.280,1.720,10.76,256,0.940,bicubic
 tf_efficientnet_b1,93.510,6.490,98.360,1.640,7.79,240,0.882,bicubic
+dla102x,93.510,6.490,98.500,1.500,26.31,224,0.875,bilinear
+botnet26t_256,93.500,6.500,98.300,1.700,12.49,256,0.950,bicubic
 repvgg_b2,93.490,6.510,98.730,1.270,89.02,224,0.875,bilinear
 hrnet_w40,93.490,6.510,98.590,1.410,57.56,224,0.875,bilinear
 xcit_nano_12_p8_384_dist,93.480,6.520,98.520,1.480,3.05,384,1.000,bicubic
 xception,93.480,6.520,98.530,1.470,22.86,299,0.897,bicubic
 resnet32ts,93.470,6.530,98.490,1.510,17.96,256,0.900,bicubic
 gluon_inception_v3,93.460,6.540,98.560,1.440,23.83,299,0.875,bicubic
-mixnet_l,93.430,6.570,98.220,1.780,7.33,224,0.875,bicubic
 res2net50_26w_8s,93.430,6.570,98.180,1.820,48.40,224,0.875,bilinear
+mixnet_l,93.430,6.570,98.220,1.780,7.33,224,0.875,bicubic
 legacy_seresnet152,93.420,6.580,98.340,1.660,66.82,224,0.875,bilinear
 xception41,93.410,6.590,98.420,1.580,26.97,299,0.903,bicubic
-res2net50_26w_6s,93.400,6.600,98.280,1.720,37.05,224,0.875,bilinear
 xcit_tiny_12_p16_224_dist,93.400,6.600,98.490,1.510,6.72,224,1.000,bicubic
+res2net50_26w_6s,93.400,6.600,98.280,1.720,37.05,224,0.875,bilinear
 resnest26d,93.360,6.640,98.640,1.360,17.07,224,0.875,bilinear
-dla169,93.340,6.660,98.600,1.400,53.39,224,0.875,bilinear
 levit_128,93.340,6.660,98.380,1.620,9.21,224,0.900,bicubic
+dla169,93.340,6.660,98.600,1.400,53.39,224,0.875,bilinear
+repvgg_b1,93.330,6.670,98.510,1.490,57.42,224,0.875,bilinear
 tf_inception_v3,93.330,6.670,98.040,1.960,23.83,299,0.875,bicubic
 tv_resnet152,93.330,6.670,98.390,1.610,60.19,224,0.875,bilinear
-repvgg_b1,93.330,6.670,98.510,1.490,57.42,224,0.875,bilinear
 tf_mixnet_l,93.310,6.690,98.030,1.970,7.33,224,0.875,bicubic
 bat_resnext26ts,93.310,6.690,98.350,1.650,10.73,256,0.900,bicubic
 legacy_seresnet101,93.300,6.700,98.500,1.500,49.33,224,0.875,bilinear
@@ -366,18 +371,18 @@ efficientnet_es,93.200,6.800,98.400,1.600,5.44,224,0.875,bicubic
 hrnet_w30,93.200,6.800,98.410,1.590,37.71,224,0.875,bilinear
 dla60_res2next,93.180,6.820,98.410,1.590,17.03,224,0.875,bilinear
 dla60_res2net,93.160,6.840,98.410,1.590,20.85,224,0.875,bilinear
-pit_xs_224,93.120,6.880,98.320,1.680,10.62,224,0.900,bicubic
 regnetx_032,93.120,6.880,98.390,1.610,15.30,224,0.875,bicubic
+pit_xs_224,93.120,6.880,98.320,1.680,10.62,224,0.900,bicubic
 tf_efficientnetv2_b0,93.110,6.890,98.390,1.610,7.14,224,0.875,bicubic
 dla60x,93.090,6.910,98.490,1.510,17.35,224,0.875,bilinear
 dla102,93.080,6.920,98.540,1.460,33.27,224,0.875,bilinear
-rexnet_100,93.030,6.970,98.190,1.810,4.80,224,0.875,bicubic
 gluon_resnet50_v1c,93.030,6.970,98.370,1.630,25.58,224,0.875,bicubic
 regnety_016,93.030,6.970,98.360,1.640,11.20,224,0.875,bicubic
+rexnet_100,93.030,6.970,98.190,1.810,4.80,224,0.875,bicubic
 selecsls60,93.020,6.980,98.310,1.690,30.67,224,0.875,bicubic
 repvgg_b1g4,93.000,7.000,98.430,1.570,39.97,224,0.875,bilinear
-hardcorenas_f,92.950,7.050,98.160,1.840,8.20,224,0.875,bilinear
 legacy_seresnet50,92.950,7.050,98.190,1.810,28.09,224,0.875,bilinear
+hardcorenas_f,92.950,7.050,98.160,1.840,8.20,224,0.875,bilinear
 tf_efficientnet_em,92.950,7.050,98.210,1.790,6.90,240,0.882,bicubic
 crossvit_9_dagger_240,92.920,7.080,98.250,1.750,8.78,240,0.875,bicubic
 adv_inception_v3,92.890,7.110,98.130,1.870,23.83,299,0.875,bicubic
@@ -387,8 +392,8 @@ resmlp_12_distilled_224,92.830,7.170,98.140,1.860,15.35,224,0.875,bicubic
 tf_efficientnet_cc_b0_8e,92.820,7.180,98.180,1.820,24.01,224,0.875,bicubic
 seresnext26t_32x4d,92.810,7.190,98.370,1.630,16.81,224,0.875,bicubic
 tv_resnet101,92.810,7.190,98.230,1.770,44.55,224,0.875,bilinear
-gcresnext26ts,92.770,7.230,98.270,1.730,10.48,256,0.900,bicubic
 efficientnet_b1_pruned,92.770,7.230,98.040,1.960,6.33,240,0.882,bicubic
+gcresnext26ts,92.770,7.230,98.270,1.730,10.48,256,0.900,bicubic
 tv_resnext50_32x4d,92.760,7.240,98.280,1.720,25.03,224,0.875,bilinear
 densenet201,92.750,7.250,98.240,1.760,20.01,224,0.875,bicubic
 resnet26t,92.750,7.250,98.240,1.760,16.01,256,0.940,bicubic
@@ -417,8 +422,8 @@ skresnet34,92.380,7.620,98.140,1.860,22.28,224,0.875,bicubic
 tf_mixnet_m,92.330,7.670,97.890,2.110,5.01,224,0.875,bicubic
 hrnet_w18,92.310,7.690,98.250,1.750,21.30,224,0.875,bilinear
 selecsls42b,92.300,7.700,98.140,1.860,32.46,224,0.875,bicubic
-ese_vovnet19b_dw,92.270,7.730,98.100,1.900,6.54,224,0.875,bicubic
 mobilenetv3_large_100_miil,92.270,7.730,97.640,2.360,5.48,224,0.875,bilinear
+ese_vovnet19b_dw,92.270,7.730,98.100,1.900,6.54,224,0.875,bicubic
 tf_efficientnet_b0,92.230,7.770,98.000,2.000,5.29,224,0.875,bicubic
 tf_efficientnet_b0_ap,92.220,7.780,98.020,1.980,5.29,224,0.875,bicubic
 dla60,92.220,7.780,98.110,1.890,22.04,224,0.875,bilinear
@@ -437,10 +442,10 @@ repvgg_a2,91.940,8.060,98.150,1.850,28.21,224,0.875,bilinear
 densenet169,91.910,8.090,98.100,1.900,14.15,224,0.875,bicubic
 densenetblur121d,91.910,8.090,98.090,1.910,8.00,224,0.875,bicubic
 tv_resnet50,91.890,8.110,98.040,1.960,25.56,224,0.875,bilinear
-resnext26ts,91.860,8.140,97.930,2.070,10.30,256,0.900,bicubic
 mixer_b16_224,91.860,8.140,97.230,2.770,59.88,224,0.875,bicubic
-mobilenetv2_140,91.830,8.170,97.860,2.140,6.11,224,0.875,bicubic
+resnext26ts,91.860,8.140,97.930,2.070,10.30,256,0.900,bicubic
 xcit_nano_12_p16_384_dist,91.830,8.170,98.010,1.990,3.05,384,1.000,bicubic
+mobilenetv2_140,91.830,8.170,97.860,2.140,6.11,224,0.875,bicubic
 mixnet_s,91.820,8.180,97.690,2.310,4.13,224,0.875,bicubic
 vit_tiny_patch16_224,91.760,8.240,98.040,1.960,5.72,224,0.900,bicubic
 hardcorenas_b,91.740,8.260,97.780,2.220,5.18,224,0.875,bilinear
@@ -450,8 +455,8 @@ densenet121,91.570,8.430,98.030,1.970,7.98,224,0.875,bicubic
 tf_mixnet_s,91.510,8.490,97.610,2.390,4.13,224,0.875,bicubic
 repvgg_b0,91.450,8.550,97.980,2.020,15.82,224,0.875,bilinear
 regnety_006,91.380,8.620,97.710,2.290,6.06,224,0.875,bicubic
-hardcorenas_a,91.340,8.660,97.860,2.140,5.26,224,0.875,bilinear
 mobilenetv3_large_100,91.340,8.660,97.710,2.290,5.48,224,0.875,bicubic
+hardcorenas_a,91.340,8.660,97.860,2.140,5.26,224,0.875,bilinear
 semnasnet_100,91.280,8.720,97.570,2.430,3.89,224,0.875,bicubic
 tf_mobilenetv3_large_100,91.230,8.770,97.660,2.340,5.48,224,0.875,bilinear
 mobilenetv3_rw,91.210,8.790,97.660,2.340,5.48,224,0.875,bicubic
@@ -462,8 +467,8 @@ resnet26,91.130,8.870,97.740,2.260,16.00,224,0.875,bicubic
 resnet34,91.120,8.880,97.630,2.370,21.80,224,0.875,bilinear
 regnetx_008,91.050,8.950,97.710,2.290,7.26,224,0.875,bicubic
 tf_efficientnet_lite0,91.050,8.950,97.570,2.430,4.65,224,0.875,bicubic
-gluon_resnet34_v1b,90.990,9.010,97.650,2.350,21.80,224,0.875,bicubic
 xcit_nano_12_p8_224,90.990,9.010,97.800,2.200,3.05,224,1.000,bicubic
+gluon_resnet34_v1b,90.990,9.010,97.650,2.350,21.80,224,0.875,bicubic
 mobilenetv2_110d,90.970,9.030,97.560,2.440,4.52,224,0.875,bicubic
 legacy_seresnet34,90.900,9.100,97.580,2.420,21.96,224,0.875,bilinear
 tv_densenet121,90.900,9.100,97.700,2.300,7.98,224,0.875,bicubic
@@ -474,7 +479,6 @@ fbnetc_100,90.720,9.280,97.210,2.790,5.57,224,0.875,bilinear
 swsl_resnet18,90.680,9.320,97.710,2.290,11.69,224,0.875,bilinear
 crossvit_9_240,90.660,9.340,97.740,2.260,8.55,240,0.875,bicubic
 convit_tiny,90.610,9.390,97.730,2.270,5.71,224,0.875,bicubic
-eca_botnext26ts_256,90.550,9.450,97.250,2.750,10.59,256,0.950,bicubic
 mnasnet_100,90.510,9.490,97.470,2.530,4.38,224,0.875,bicubic
 regnety_004,90.480,9.520,97.560,2.440,4.34,224,0.875,bicubic
 spnasnet_100,90.350,9.650,97.190,2.810,4.42,224,0.875,bilinear
@@ -494,8 +498,8 @@ skresnet18,89.660,10.340,97.220,2.780,11.96,224,0.875,bicubic
 mobilenetv2_100,89.610,10.390,97.150,2.850,3.50,224,0.875,bicubic
 resnet18d,89.290,10.710,97.140,2.860,11.71,224,0.875,bicubic
 vit_tiny_r_s16_p8_224,89.190,10.810,97.230,2.770,6.34,224,0.900,bicubic
-hrnet_w18_small,89.060,10.940,97.100,2.900,13.19,224,0.875,bilinear
 vgg19,89.060,10.940,96.870,3.130,143.67,224,0.875,bilinear
+hrnet_w18_small,89.060,10.940,97.100,2.900,13.19,224,0.875,bilinear
 tf_mobilenetv3_large_minimal_100,88.950,11.050,96.870,3.130,3.92,224,0.875,bilinear
 legacy_seresnet18,88.880,11.120,96.970,3.030,11.78,224,0.875,bicubic
 regnetx_004,88.880,11.120,97.120,2.880,5.16,224,0.875,bicubic
@@ -504,7 +508,6 @@ xcit_nano_12_p16_224,88.590,11.410,96.790,3.210,3.05,224,1.000,bicubic
 vgg16,88.550,11.450,96.790,3.210,138.36,224,0.875,bilinear
 gluon_resnet18_v1b,88.380,11.620,96.700,3.300,11.69,224,0.875,bicubic
 vgg11_bn,87.520,12.480,96.810,3.190,132.87,224,0.875,bilinear
-botnet26t_256,87.460,12.540,96.190,3.810,12.49,256,0.950,bicubic
 resnet18,87.370,12.630,96.260,3.740,11.69,224,0.875,bilinear
 regnety_002,87.360,12.640,96.570,3.430,3.16,224,0.875,bicubic
 mixer_l16_224,87.160,12.840,93.530,6.470,208.20,224,0.875,bicubic

results/results-imagenet-a.csv

@@ -16,7 +16,7 @@ cait_m48_448,62.093,37.907,86.440,13.560,356.46,448,1.000,bicubic,-35.387,-13.11
 tf_efficientnet_b6_ns,61.640,38.360,84.787,15.213,43.04,528,0.942,bicubic,-35.990,-14.793,+3
 swin_large_patch4_window7_224,61.293,38.707,86.520,13.480,196.53,224,0.900,bicubic,-36.367,-13.060,-1
 vit_large_r50_s32_384,61.147,38.853,83.773,16.227,329.09,384,1.000,bicubic,-36.713,-15.897,-7
-ig_resnext101_32x48d,61.040,38.960,83.227,16.773,828.41,224,0.875,bilinear,-36.600,-16.483,-2
+ig_resnext101_32x48d,61.040,38.960,83.227,16.773,828.41,224,0.875,bilinear,-36.600,-16.363,-1
 tf_efficientnetv2_m_in21ft1k,60.853,39.147,85.267,14.733,54.14,480,1.000,bicubic,-36.627,-14.263,+8
 tf_efficientnet_b5_ns,59.800,40.200,84.213,15.787,30.39,456,0.934,bicubic,-37.690,-15.417,+5
 xcit_large_24_p8_384_dist,59.787,40.213,85.333,14.667,188.93,384,1.000,bicubic,-37.743,-14.207,+1
@@ -28,35 +28,35 @@ dm_nfnet_f4,57.787,42.213,81.507,18.493,316.07,512,0.951,bicubic,-39.783,-18.003
 cait_m36_384,57.667,42.333,84.693,15.307,271.22,384,1.000,bicubic,-39.733,-14.817,+1
 xcit_medium_24_p8_384_dist,56.587,43.413,83.440,16.560,84.32,384,1.000,bicubic,-40.713,-16.070,+4
 dm_nfnet_f3,55.333,44.667,80.480,19.520,254.92,416,0.940,bicubic,-42.017,-19.080,+1
-vit_large_patch16_224,55.333,44.667,79.840,20.160,304.33,224,0.900,bicubic,-42.307,-19.750,-13
+vit_large_patch16_224,55.333,44.667,79.840,20.160,304.33,224,0.900,bicubic,-42.307,-19.870,-14
 xcit_small_24_p8_384_dist,54.400,45.600,81.720,18.280,47.63,384,1.000,bicubic,-42.850,-17.890,+5
 vit_base_r50_s16_384,54.333,45.667,80.840,19.160,98.95,384,1.000,bicubic,-42.847,-18.720,+9
 cait_s36_384,54.240,45.760,81.267,18.733,68.37,384,1.000,bicubic,-43.100,-18.263,-2
 ig_resnext101_32x16d,53.053,46.947,76.867,23.133,194.03,224,0.875,bilinear,-43.767,-22.733,+30
 tf_efficientnetv2_l,52.933,47.067,79.000,21.000,118.52,480,1.000,bicubic,-44.337,-20.550,-1
 xcit_large_24_p16_384_dist,52.813,47.187,81.720,18.280,189.10,384,1.000,bicubic,-44.717,-17.760,-13
-resnetv2_152x2_bitm,52.733,47.267,81.187,18.813,236.34,448,1.000,bilinear,-44.297,-18.253,+14
+resnetv2_152x2_bitm,52.733,47.267,81.187,18.813,236.34,448,1.000,bilinear,-44.297,-18.403,+14
 resnetv2_101x3_bitm,52.400,47.600,79.867,20.133,387.93,448,1.000,bilinear,-44.620,-19.623,+15
 swin_base_patch4_window7_224,51.827,48.173,80.427,19.573,87.77,224,0.900,bicubic,-45.433,-19.103,-4
 swsl_resnext101_32x8d,51.187,48.813,78.200,21.800,88.79,224,0.875,bilinear,-46.013,-21.370,-1
 tf_efficientnet_b4_ns,50.893,49.107,79.040,20.960,19.34,380,0.922,bicubic,-46.037,-20.540,+17
-beit_base_patch16_224,50.707,49.293,79.893,20.107,86.53,224,0.900,bicubic,-46.373,-19.717,+5
+beit_base_patch16_224,50.707,49.293,79.893,20.107,86.53,224,0.900,bicubic,-46.373,-19.727,+7
 xcit_small_12_p8_384_dist,50.533,49.467,79.600,20.400,26.21,384,1.000,bicubic,-46.697,-19.880,-6
 resnetv2_152x2_bit_teacher_384,50.067,49.933,77.733,22.267,236.34,384,1.000,bicubic,-46.743,-21.717,+21
-cait_s24_384,49.400,50.600,78.640,21.360,47.06,384,1.000,bicubic,-47.680,-20.790,+3
+cait_s24_384,49.400,50.600,78.640,21.360,47.06,384,1.000,bicubic,-47.680,-20.970,+2
 xcit_medium_24_p16_384_dist,49.227,50.773,79.720,20.280,84.40,384,1.000,bicubic,-48.053,-19.740,-13
 deit_base_distilled_patch16_384,49.040,50.960,79.000,21.000,87.63,384,1.000,bicubic,-47.930,-20.490,+9
-dm_nfnet_f2,48.387,51.613,76.760,23.240,193.78,352,0.920,bicubic,-48.643,-22.830,+4
+dm_nfnet_f2,48.387,51.613,76.760,23.240,193.78,352,0.920,bicubic,-48.643,-22.680,+4
 tf_efficientnetv2_s_in21ft1k,48.053,51.947,77.720,22.280,21.46,384,1.000,bicubic,-48.687,-21.700,+22
 tf_efficientnet_b8,47.987,52.013,76.467,23.533,87.41,672,0.954,bicubic,-49.223,-23.033,-12
 xcit_large_24_p8_224_dist,47.893,52.107,79.133,20.867,188.93,224,1.000,bicubic,-49.167,-20.287,-1
 resnest269e,47.653,52.347,74.000,26.000,110.93,416,0.928,bicubic,-48.867,-25.350,+39
-xcit_large_24_p8_224,46.867,53.133,74.400,25.600,188.93,224,1.000,bicubic,-49.533,-24.580,+44
+xcit_large_24_p8_224,46.867,53.133,74.400,25.600,188.93,224,1.000,bicubic,-49.533,-24.740,+45
 xcit_small_24_p16_384_dist,46.773,53.227,77.013,22.987,47.67,384,1.000,bicubic,-50.357,-22.437,-11
 tf_efficientnet_b8_ap,46.453,53.547,76.160,23.840,87.41,672,0.954,bicubic,-50.657,-23.500,-11
 resnetv2_50x3_bitm,46.293,53.707,76.627,23.373,217.32,448,1.000,bilinear,-50.437,-22.913,+16
 efficientnetv2_rw_m,46.160,53.840,75.827,24.173,53.24,416,1.000,bicubic,-50.830,-23.703,-2
-swsl_resnext101_32x16d,45.933,54.067,72.053,27.947,194.03,224,0.875,bilinear,-50.667,-27.217,+26
+swsl_resnext101_32x16d,45.933,54.067,72.053,27.947,194.03,224,0.875,bilinear,-50.667,-27.477,+26
 ecaresnet269d,45.720,54.280,74.920,25.080,102.09,352,1.000,bicubic,-51.370,-24.550,-13
 vit_small_patch16_384,45.360,54.640,76.160,23.840,22.20,384,1.000,bicubic,-51.330,-23.320,+16
 tf_efficientnet_b7_ap,45.267,54.733,74.027,25.973,66.35,600,0.949,bicubic,-51.933,-25.513,-21
@@ -67,7 +67,7 @@ xcit_medium_24_p8_224_dist,45.160,54.840,76.720,23.280,84.32,224,1.000,bicubic,-
 dm_nfnet_f1,44.853,55.147,73.653,26.347,132.63,320,0.910,bicubic,-52.037,-25.757,-5
 eca_nfnet_l2,44.627,55.373,75.773,24.227,56.72,384,1.000,bicubic,-52.463,-23.737,-22
 crossvit_18_dagger_408,43.867,56.133,73.600,26.400,44.61,408,1.000,bicubic,-52.663,-25.660,+22
-resnest200e,43.867,56.133,73.293,26.707,70.20,320,0.909,bicubic,-52.753,-26.057,+13
+resnest200e,43.867,56.133,73.293,26.707,70.20,320,0.909,bicubic,-52.753,-26.217,+12
 cait_xs24_384,43.640,56.360,74.907,25.093,26.67,384,1.000,bicubic,-52.920,-24.513,+17
 tresnet_xl_448,43.187,56.813,72.120,27.880,78.44,448,0.875,bilinear,-52.783,-27.000,+57
 vit_base_patch16_224,43.107,56.893,72.547,27.453,86.57,224,0.900,bicubic,-53.763,-26.983,-10
@@ -76,15 +76,15 @@ xcit_medium_24_p8_224,43.027,56.973,70.080,29.920,84.32,224,1.000,bicubic,-53.08
 resnetrs420,42.440,57.560,70.120,29.880,191.89,416,1.000,bicubic,-54.470,-29.340,-15
 xcit_tiny_24_p8_384_dist,42.253,57.747,72.773,27.227,12.11,384,1.000,bicubic,-54.297,-26.547,+12
 tf_efficientnet_b7,42.200,57.800,72.547,27.453,66.35,600,0.949,bicubic,-54.810,-26.973,-23
-crossvit_15_dagger_408,41.773,58.227,71.973,28.027,28.50,408,1.000,bicubic,-54.617,-27.177,+21
+crossvit_15_dagger_408,41.773,58.227,71.973,28.027,28.50,408,1.000,bicubic,-54.617,-27.177,+22
 swsl_resnext101_32x4d,41.653,58.347,71.867,28.133,44.18,224,0.875,bilinear,-54.767,-27.603,+17
-xcit_small_24_p8_224,41.640,58.360,70.840,29.160,47.63,224,1.000,bicubic,-54.760,-28.300,+18
+xcit_small_24_p8_224,41.640,58.360,70.840,29.160,47.63,224,1.000,bicubic,-54.760,-28.140,+17
 vit_large_r50_s32_224,41.520,58.480,70.360,29.640,328.99,224,0.900,bicubic,-55.270,-28.990,-14
 xcit_small_24_p8_224_dist,41.467,58.533,73.707,26.293,47.63,224,1.000,bicubic,-55.403,-25.773,-19
-resmlp_big_24_224_in22ft1k,40.453,59.547,74.653,25.347,129.14,224,0.875,bicubic,-56.167,-24.857,-2
-tf_efficientnet_b6_ap,40.333,59.667,71.400,28.600,43.04,528,0.942,bicubic,-56.747,-28.220,-35
+resmlp_big_24_224_in22ft1k,40.453,59.547,74.653,25.347,129.14,224,0.875,bicubic,-56.167,-24.697,-1
+tf_efficientnet_b6_ap,40.333,59.667,71.400,28.600,43.04,528,0.942,bicubic,-56.747,-28.030,-36
 tresnet_l_448,40.133,59.867,69.707,30.293,55.99,448,0.875,bilinear,-55.737,-29.413,+50
-deit_base_patch16_384,39.880,60.120,70.440,29.560,86.86,384,1.000,bicubic,-56.270,-28.700,+28
+deit_base_patch16_384,39.880,60.120,70.440,29.560,86.86,384,1.000,bicubic,-56.270,-28.750,+29
 resnetrs350,39.347,60.653,68.293,31.707,163.96,384,1.000,bicubic,-57.413,-31.067,-18
 vit_large_patch32_384,38.867,61.133,68.573,31.427,306.63,384,1.000,bicubic,-56.963,-30.577,+50
 resnetv2_101x1_bitm,38.240,61.760,70.267,29.733,44.54,448,1.000,bilinear,-57.860,-29.013,+33
@@ -108,33 +108,33 @@ resnetrs270,34.587,65.413,65.133,34.867,129.86,352,1.000,bicubic,-62.103,-34.217
 tf_efficientnet_b5_ap,34.347,65.653,67.040,32.960,30.39,456,0.934,bicubic,-62.333,-32.420,-30
 xcit_tiny_12_p8_384_dist,34.213,65.787,66.160,33.840,6.71,384,1.000,bicubic,-61.847,-32.980,+16
 vit_base_patch16_224_miil,34.133,65.867,64.547,35.453,86.54,224,0.875,bilinear,-62.307,-34.763,-14
-xcit_medium_24_p16_224_dist,34.013,65.987,67.627,32.373,84.40,224,1.000,bicubic,-62.587,-31.903,-27
+xcit_medium_24_p16_224_dist,34.013,65.987,67.627,32.373,84.40,224,1.000,bicubic,-62.587,-31.643,-27
 resmlp_big_24_distilled_224,33.787,66.213,69.293,30.707,129.14,224,0.875,bicubic,-62.683,-30.017,-17
 resnet152d,33.707,66.293,65.480,34.520,60.21,320,1.000,bicubic,-62.643,-33.910,-10
-tresnet_m_448,33.627,66.373,64.280,35.720,31.39,448,0.875,bilinear,-61.363,-34.700,+94
+tresnet_m_448,33.627,66.373,64.280,35.720,31.39,448,0.875,bilinear,-61.363,-34.700,+95
 xcit_tiny_24_p16_384_dist,33.573,66.427,65.227,34.773,12.12,384,1.000,bicubic,-62.347,-33.993,+16
-twins_pcpvt_large,33.133,66.867,67.920,32.080,60.99,224,0.900,bicubic,-63.017,-31.270,0
+twins_pcpvt_large,33.133,66.867,67.920,32.080,60.99,224,0.900,bicubic,-63.017,-31.220,-1
 swsl_resnext50_32x4d,33.053,66.947,65.187,34.813,25.03,224,0.875,bilinear,-62.827,-33.833,+17
 twins_svt_base,33.000,67.000,65.613,34.387,56.07,224,0.900,bicubic,-63.160,-33.447,-4
 pit_b_224,32.760,67.240,62.227,37.773,73.76,224,0.900,bicubic,-62.870,-36.443,+35
 xcit_large_24_p16_224,32.653,67.347,61.667,38.333,189.10,224,1.000,bicubic,-62.757,-36.963,+53
 ssl_resnext101_32x16d,32.400,67.600,63.707,36.293,194.03,224,0.875,bilinear,-63.400,-35.473,+21
-swin_small_patch4_window7_224,32.347,67.653,65.200,34.800,49.61,224,0.900,bicubic,-63.533,-34.050,+13
+swin_small_patch4_window7_224,32.347,67.653,65.200,34.800,49.61,224,0.900,bicubic,-63.533,-33.920,+13
 jx_nest_small,32.307,67.693,63.813,36.187,38.35,224,0.875,bicubic,-63.663,-35.227,+5
 resnetv2_152x2_bit_teacher,31.973,68.027,63.600,36.400,236.34,224,0.875,bicubic,-64.117,-35.670,0
 resnest101e,31.587,68.413,64.040,35.960,48.28,256,0.875,bilinear,-64.273,-35.170,+13
-cait_s24_224,31.107,68.893,64.200,35.800,46.92,224,1.000,bicubic,-65.283,-34.960,-25
+cait_s24_224,31.107,68.893,64.200,35.800,46.92,224,1.000,bicubic,-65.283,-34.960,-26
 tf_efficientnet_b5,31.107,68.893,64.493,35.507,30.39,456,0.934,bicubic,-65.233,-34.817,-22
-crossvit_base_240,31.040,68.960,60.960,39.040,105.03,240,0.875,bicubic,-64.480,-37.860,+35
+crossvit_base_240,31.040,68.960,60.960,39.040,105.03,240,0.875,bicubic,-64.480,-37.810,+36
 efficientnet_b4,30.547,69.453,64.333,35.667,19.34,384,1.000,bicubic,-65.613,-34.867,-16
 crossvit_18_240,30.387,69.613,61.547,38.453,43.27,240,0.875,bicubic,-65.063,-37.243,+38
 xcit_small_24_p16_224_dist,30.347,69.653,64.440,35.560,47.67,224,1.000,bicubic,-65.863,-34.770,-20
 resnetrs200,30.187,69.813,62.773,37.227,93.21,320,1.000,bicubic,-66.333,-36.577,-39
 dm_nfnet_f0,30.173,69.827,62.360,37.640,71.49,256,0.900,bicubic,-65.967,-36.890,-16
 crossvit_18_dagger_240,30.120,69.880,61.613,38.387,44.27,240,0.875,bicubic,-65.440,-37.447,+23
-xcit_medium_24_p16_224,29.920,70.080,59.213,40.787,84.40,224,1.000,bicubic,-65.600,-39.557,+29
+xcit_medium_24_p16_224,29.920,70.080,59.213,40.787,84.40,224,1.000,bicubic,-65.600,-39.607,+28
 swsl_resnet50,29.773,70.227,63.720,36.280,25.56,224,0.875,bilinear,-65.627,-35.570,+38
-twins_pcpvt_base,29.773,70.227,64.467,35.533,43.83,224,0.900,bicubic,-66.017,-34.663,+7
+twins_pcpvt_base,29.773,70.227,64.467,35.533,43.83,224,0.900,bicubic,-66.017,-34.663,+6
 cait_xxs24_384,29.693,70.307,63.733,36.267,12.03,384,1.000,bicubic,-65.577,-35.227,+42
 convit_base,29.333,70.667,61.520,38.480,86.54,224,0.875,bicubic,-66.217,-37.370,+19
 deit_base_distilled_patch16_224,29.320,70.680,64.093,35.907,87.34,224,0.900,bicubic,-66.780,-35.097,-18
@@ -142,14 +142,14 @@ tf_efficientnetv2_s,29.000,71.000,61.120,38.880,21.46,384,1.000,bicubic,-67.340,
 ssl_resnext101_32x8d,28.893,71.107,60.613,39.387,88.79,224,0.875,bilinear,-66.577,-38.507,+25
 resnet101d,28.747,71.253,62.013,37.987,44.57,320,1.000,bicubic,-67.553,-37.217,-35
 resnetrs152,28.640,71.360,60.000,40.000,86.62,320,1.000,bicubic,-67.930,-39.240,-57
-xcit_tiny_24_p8_224,28.507,71.493,60.253,39.747,12.11,224,1.000,bicubic,-67.163,-38.797,+7
+xcit_tiny_24_p8_224,28.507,71.493,60.253,39.747,12.11,224,1.000,bicubic,-67.163,-38.797,+6
 xcit_tiny_24_p8_224_dist,28.467,71.533,61.173,38.827,12.11,224,1.000,bicubic,-67.353,-38.037,-6
 regnetz_c,28.453,71.547,63.160,36.840,13.46,320,0.940,bicubic,-67.347,-35.940,-6
-crossvit_15_dagger_240,28.227,71.773,60.013,39.987,28.21,240,0.875,bicubic,-67.443,-38.807,+3
+crossvit_15_dagger_240,28.227,71.773,60.013,39.987,28.21,240,0.875,bicubic,-67.443,-38.807,+4
 xcit_small_24_p16_224,28.040,71.960,58.467,41.533,47.67,224,1.000,bicubic,-67.490,-40.303,+13
 coat_lite_small,27.453,72.547,58.427,41.573,19.84,224,0.900,bicubic,-68.077,-40.433,+10
 deit_base_patch16_224,27.147,72.853,58.693,41.307,86.57,224,0.900,bicubic,-68.293,-40.147,+18
-resnetv2_50x1_bitm,27.093,72.907,62.600,37.400,25.55,448,1.000,bilinear,-67.927,-36.450,+52
+resnetv2_50x1_bitm,27.093,72.907,62.600,37.400,25.55,448,1.000,bilinear,-67.927,-36.450,+54
 xcit_small_12_p16_224_dist,26.867,73.133,59.587,40.413,26.25,224,1.000,bicubic,-69.163,-39.543,-27
 vit_small_patch16_224,26.760,73.240,58.880,41.120,22.05,224,0.900,bicubic,-68.610,-40.270,+22
 regnety_032,26.067,73.933,60.880,39.120,19.44,288,1.000,bicubic,-69.913,-38.310,-28
@@ -160,12 +160,12 @@ ecaresnet101d,25.760,74.240,58.707,41.293,44.57,224,0.875,bicubic,-69.780,-40.42
 ecaresnet50t,25.640,74.360,59.720,40.280,25.57,320,0.950,bicubic,-69.860,-39.180,+6
 visformer_small,25.480,74.520,58.520,41.480,40.22,224,0.900,bicubic,-70.020,-40.600,+4
 crossvit_15_240,25.440,74.560,57.320,42.680,27.53,240,0.875,bicubic,-69.680,-41.610,+27
-coat_mini,25.387,74.613,57.413,42.587,10.34,224,0.900,bicubic,-69.603,-41.367,+44
+coat_mini,25.387,74.613,57.413,42.587,10.34,224,0.900,bicubic,-69.603,-41.367,+45
 resnetv2_50x1_bit_distilled,25.107,74.893,59.373,40.627,25.55,224,0.875,bicubic,-71.003,-39.907,-45
 xcit_small_12_p16_224,25.080,74.920,55.653,44.347,26.25,224,1.000,bicubic,-70.320,-43.177,+10
 convit_small,24.773,75.227,56.947,43.053,27.78,224,0.875,bicubic,-70.407,-41.973,+19
 gc_efficientnetv2_rw_t,24.560,75.440,57.533,42.467,13.68,288,1.000,bicubic,-71.180,-41.487,-21
-tnt_s_patch16_224,24.547,75.453,57.773,42.227,23.76,224,0.900,bicubic,-70.493,-41.067,+33
+tnt_s_patch16_224,24.547,75.453,57.773,42.227,23.76,224,0.900,bicubic,-70.493,-41.067,+34
 eca_nfnet_l0,24.493,75.507,59.600,40.400,24.14,288,1.000,bicubic,-71.467,-39.610,-39
 efficientnetv2_rw_t,24.240,75.760,57.187,42.813,13.65,288,1.000,bicubic,-71.370,-41.883,-14
 xcit_tiny_12_p16_384_dist,24.160,75.840,57.000,43.000,6.72,384,1.000,bicubic,-70.950,-42.020,+21
@@ -176,344 +176,347 @@ ssl_resnext101_32x4d,23.760,76.240,57.133,42.867,44.18,224,0.875,bilinear,-71.67
 vit_small_patch32_384,23.547,76.453,56.907,43.093,22.92,384,1.000,bicubic,-71.513,-41.923,+20
 crossvit_small_240,23.413,76.587,56.400,43.600,26.86,240,0.875,bicubic,-71.417,-42.620,+43
 jx_nest_tiny,23.133,76.867,56.053,43.947,17.06,224,0.875,bicubic,-72.117,-42.927,+3
-nasnetalarge,23.120,76.880,54.533,45.467,88.75,331,0.911,bicubic,-72.560,-44.397,-30
 efficientnet_b3,23.120,76.880,55.813,44.187,12.23,320,1.000,bicubic,-72.600,-43.107,-30
+nasnetalarge,23.120,76.880,54.533,45.467,88.75,331,0.911,bicubic,-72.560,-44.397,-30
 pnasnet5large,23.107,76.893,53.320,46.680,86.06,331,0.911,bicubic,-72.613,-45.720,-33
 levit_384,23.013,76.987,55.840,44.160,39.13,224,0.900,bicubic,-72.517,-43.210,-21
+halo2botnet50ts_256,22.893,77.107,52.707,47.293,22.64,256,0.950,bicubic,-71.867,-45.953,+44
 resnet61q,22.693,77.307,55.440,44.560,36.85,288,1.000,bicubic,-73.097,-43.550,-40
-resmlp_big_24_224,22.627,77.373,54.067,45.933,129.14,224,0.875,bicubic,-72.023,-44.423,+47
-twins_pcpvt_small,22.440,77.560,56.547,43.453,24.11,224,0.900,bicubic,-72.790,-42.333,-2
+resmlp_big_24_224,22.627,77.373,54.067,45.933,129.14,224,0.875,bicubic,-72.023,-44.423,+49
+twins_pcpvt_small,22.440,77.560,56.547,43.453,24.11,224,0.900,bicubic,-72.790,-42.333,-3
 vit_base_patch32_224,22.253,77.747,53.760,46.240,88.22,224,0.900,bicubic,-72.757,-45.260,+20
-pit_s_distilled_224,22.147,77.853,56.867,43.133,24.04,224,0.900,bicubic,-73.093,-42.183,-5
-xcit_tiny_12_p8_224_dist,22.040,77.960,53.920,46.080,6.71,224,1.000,bicubic,-73.040,-44.990,+6
-halonet50ts,21.773,78.227,51.293,48.707,22.73,256,0.940,bicubic,-73.177,-47.457,+20
-tresnet_m,21.267,78.733,53.480,46.520,31.39,224,0.875,bilinear,-74.463,-45.550,-43
-pit_s_224,21.040,78.960,53.520,46.480,23.46,224,0.900,bicubic,-73.540,-45.200,+46
-swin_tiny_patch4_window7_224,21.027,78.973,55.627,44.373,28.29,224,0.900,bicubic,-74.103,-43.223,-4
-convmixer_1536_20,20.907,79.093,55.267,44.733,51.63,224,0.960,bicubic,-74.173,-43.763,0
-xcit_tiny_12_p8_224,20.893,79.107,52.307,47.693,6.71,224,1.000,bicubic,-73.817,-46.523,+34
-regnetz_b,20.787,79.213,53.453,46.547,9.72,288,0.940,bicubic,-74.273,-45.597,+2
-deit_small_distilled_patch16_224,20.680,79.320,54.853,45.147,22.44,224,0.900,bicubic,-74.030,-44.177,+30
-resnet51q,20.533,79.467,55.133,44.867,35.70,288,1.000,bilinear,-75.347,-43.987,-64
-resnetrs101,20.280,79.720,52.533,47.467,63.62,288,0.940,bicubic,-75.140,-46.497,-26
-resnest50d_4s2x40d,20.080,79.920,52.920,47.080,30.42,224,0.875,bicubic,-74.870,-46.150,+11
-ssl_resnext50_32x4d,19.680,80.320,53.213,46.787,25.03,224,0.875,bilinear,-75.180,-45.657,+18
-xcit_nano_12_p8_384_dist,19.680,80.320,50.413,49.587,3.05,384,1.000,bicubic,-73.800,-48.117,+142
-haloregnetz_b,19.560,80.440,49.720,50.280,11.68,224,0.940,bicubic,-75.150,-48.940,+25
-tresnet_xl,19.320,80.680,52.867,47.133,78.44,224,0.875,bilinear,-76.120,-46.193,-33
-resnetv2_101,19.307,80.693,48.800,51.200,44.54,224,0.950,bicubic,-76.323,-50.190,-49
-gluon_senet154,19.067,80.933,47.160,52.840,115.09,224,0.875,bicubic,-75.863,-51.610,+8
-gluon_seresnext101_64x4d,18.960,81.040,48.960,51.040,88.23,224,0.875,bicubic,-75.980,-49.860,+5
-legacy_senet154,18.920,81.080,47.627,52.373,115.09,224,0.875,bilinear,-76.140,-51.363,-9
-tf_efficientnet_b1_ns,18.920,81.080,51.707,48.293,7.79,240,0.882,bicubic,-76.250,-47.413,-22
-levit_256,18.893,81.107,49.653,50.347,18.89,224,0.900,bicubic,-76.137,-49.237,-7
+pit_s_distilled_224,22.147,77.853,56.867,43.133,24.04,224,0.900,bicubic,-73.093,-42.183,-6
+lamhalobotnet50ts_256,22.080,77.920,51.360,48.640,22.57,256,0.950,bicubic,-72.720,-47.190,+33
+xcit_tiny_12_p8_224_dist,22.040,77.960,53.920,46.080,6.71,224,1.000,bicubic,-73.040,-44.990,+4
+halonet50ts,21.667,78.333,52.507,47.493,22.73,256,0.940,bicubic,-73.383,-46.463,+9
+tresnet_m,21.267,78.733,53.480,46.520,31.39,224,0.875,bilinear,-74.463,-45.550,-45
+pit_s_224,21.040,78.960,53.520,46.480,23.46,224,0.900,bicubic,-73.540,-45.200,+47
+swin_tiny_patch4_window7_224,21.027,78.973,55.627,44.373,28.29,224,0.900,bicubic,-74.103,-43.223,-6
+convmixer_1536_20,20.907,79.093,55.267,44.733,51.63,224,0.960,bicubic,-74.173,-43.763,-2
+xcit_tiny_12_p8_224,20.893,79.107,52.307,47.693,6.71,224,1.000,bicubic,-73.817,-46.723,+33
+regnetz_b,20.787,79.213,53.453,46.547,9.72,288,0.940,bicubic,-74.273,-45.537,+1
+deit_small_distilled_patch16_224,20.680,79.320,54.853,45.147,22.44,224,0.900,bicubic,-74.030,-43.807,+32
+resnet51q,20.533,79.467,55.133,44.867,35.70,288,1.000,bilinear,-75.347,-44.117,-66
+resnetrs101,20.280,79.720,52.533,47.467,63.62,288,0.940,bicubic,-75.140,-46.497,-28
+resnest50d_4s2x40d,20.080,79.920,52.920,47.080,30.42,224,0.875,bicubic,-74.870,-46.150,+9
+xcit_nano_12_p8_384_dist,19.680,80.320,50.413,49.587,3.05,384,1.000,bicubic,-73.800,-48.107,+146
+ssl_resnext50_32x4d,19.680,80.320,53.213,46.787,25.03,224,0.875,bilinear,-75.180,-45.657,+15
+haloregnetz_b,19.560,80.440,49.720,50.280,11.68,224,0.940,bicubic,-75.150,-49.110,+27
+tresnet_xl,19.320,80.680,52.867,47.133,78.44,224,0.875,bilinear,-76.120,-46.193,-35
+resnetv2_101,19.307,80.693,48.800,51.200,44.54,224,0.950,bicubic,-76.323,-50.190,-51
+lambda_resnet50ts,19.120,80.880,49.307,50.693,21.54,256,0.950,bicubic,-75.650,-49.163,+19
+gluon_senet154,19.067,80.933,47.160,52.840,115.09,224,0.875,bicubic,-75.863,-51.610,+5
+gluon_seresnext101_64x4d,18.960,81.040,48.960,51.040,88.23,224,0.875,bicubic,-75.980,-49.860,+3
+tf_efficientnet_b1_ns,18.920,81.080,51.707,48.293,7.79,240,0.882,bicubic,-76.250,-47.413,-24
+legacy_senet154,18.920,81.080,47.627,52.373,115.09,224,0.875,bilinear,-76.140,-51.423,-14
+levit_256,18.893,81.107,49.653,50.347,18.89,224,0.900,bicubic,-76.137,-49.237,-8
+rexnet_200,18.880,81.120,52.587,47.413,16.37,224,0.875,bicubic,-76.060,-46.413,-3
 repvgg_b3,18.880,81.120,49.800,50.200,123.09,224,0.875,bilinear,-75.690,-48.990,+28
-rexnet_200,18.880,81.120,52.587,47.413,16.37,224,0.875,bicubic,-76.060,-46.413,+1
-deit_small_patch16_224,18.720,81.280,51.093,48.907,22.05,224,0.900,bicubic,-75.680,-47.597,+46
-mixer_b16_224_miil,18.480,81.520,50.987,49.013,59.88,224,0.875,bilinear,-76.830,-47.903,-35
-seresnext50_32x4d,18.227,81.773,50.907,49.093,27.56,224,0.875,bicubic,-76.803,-47.983,-11
-cait_xxs36_224,18.053,81.947,49.267,50.733,17.30,224,1.000,bicubic,-76.207,-49.443,+56
+deit_small_patch16_224,18.720,81.280,51.093,48.907,22.05,224,0.900,bicubic,-75.680,-47.617,+46
+mixer_b16_224_miil,18.480,81.520,50.987,49.013,59.88,224,0.875,bilinear,-76.830,-47.903,-38
+seresnext50_32x4d,18.227,81.773,50.907,49.093,27.56,224,0.875,bicubic,-76.803,-47.983,-14
+cait_xxs36_224,18.053,81.947,49.267,50.733,17.30,224,1.000,bicubic,-76.207,-49.443,+57
 ecaresnet50d,17.960,82.040,51.453,48.547,25.58,224,0.875,bicubic,-76.660,-47.437,+18
-sehalonet33ts,17.827,82.173,47.347,52.653,13.69,256,0.940,bicubic,-76.953,-51.223,+5
-resnest50d_1s4x24d,17.640,82.360,49.613,50.387,25.68,224,0.875,bicubic,-77.130,-49.367,+6
-tf_efficientnet_lite4,17.627,82.373,50.253,49.747,13.01,380,0.920,bilinear,-77.233,-48.767,0
-vit_tiny_patch16_384,17.547,82.453,49.920,50.080,5.79,384,1.000,bicubic,-76.103,-48.680,+109
-gluon_seresnext101_32x4d,17.373,82.627,46.467,53.533,48.96,224,0.875,bicubic,-77.547,-52.343,-7
-inception_v4,17.293,82.707,45.387,54.613,42.68,299,0.875,bicubic,-77.077,-53.223,+40
-resnest50d,17.293,82.707,50.533,49.467,27.48,224,0.875,bilinear,-77.537,-48.347,-2
-efficientnet_el,17.013,82.987,49.933,50.067,10.59,300,0.904,bicubic,-78.107,-49.047,-34
-tf_efficientnet_b3_ap,17.000,83.000,49.387,50.613,12.23,300,0.904,bicubic,-78.320,-49.513,-48
+sehalonet33ts,17.827,82.173,47.347,52.653,13.69,256,0.940,bicubic,-76.953,-51.223,+3
+resnest50d_1s4x24d,17.640,82.360,49.613,50.387,25.68,224,0.875,bicubic,-77.130,-49.367,+3
+tf_efficientnet_lite4,17.627,82.373,50.253,49.747,13.01,380,0.920,bilinear,-77.233,-48.767,-3
+vit_tiny_patch16_384,17.547,82.453,49.920,50.080,5.79,384,1.000,bicubic,-76.103,-48.680,+110
+gluon_seresnext101_32x4d,17.373,82.627,46.467,53.533,48.96,224,0.875,bicubic,-77.547,-52.343,-10
+resnest50d,17.293,82.707,50.533,49.467,27.48,224,0.875,bilinear,-77.537,-48.347,-4
+inception_v4,17.293,82.707,45.387,54.613,42.68,299,0.875,bicubic,-77.077,-53.193,+38
+efficientnet_el,17.013,82.987,49.933,50.067,10.59,300,0.904,bicubic,-78.107,-49.047,-37
+tf_efficientnet_b3_ap,17.000,83.000,49.387,50.613,12.23,300,0.904,bicubic,-78.320,-49.513,-51
 xcit_tiny_24_p16_224_dist,16.960,83.040,47.253,52.747,12.12,224,1.000,bicubic,-77.560,-51.537,+19
+resmlp_36_distilled_224,16.707,83.293,51.093,48.907,44.69,224,0.875,bicubic,-78.163,-47.697,-15
 gluon_resnext101_64x4d,16.707,83.293,43.933,56.067,83.46,224,0.875,bicubic,-77.933,-54.737,+5
-resmlp_36_distilled_224,16.707,83.293,51.093,48.907,44.69,224,0.875,bicubic,-78.163,-47.767,-13
-tf_efficientnet_b3,16.680,83.320,49.107,50.893,12.23,300,0.904,bicubic,-78.340,-49.803,-24
-xception71,16.600,83.400,45.240,54.760,42.34,299,0.903,bicubic,-77.690,-53.400,+39
-tf_efficientnetv2_b3,16.493,83.507,48.400,51.600,14.36,300,0.904,bicubic,-78.677,-50.420,-44
-gluon_resnet152_v1s,16.467,83.533,44.227,55.773,60.32,224,0.875,bicubic,-78.583,-54.703,-33
-inception_resnet_v2,16.467,83.533,44.720,55.280,55.84,299,0.897,bicubic,-78.073,-54.070,+10
-tresnet_l,16.413,83.587,49.587,50.413,55.99,224,0.875,bilinear,-78.877,-49.423,-55
+tf_efficientnet_b3,16.680,83.320,49.107,50.893,12.23,300,0.904,bicubic,-78.340,-49.803,-27
+xception71,16.600,83.400,45.240,54.760,42.34,299,0.903,bicubic,-77.690,-53.400,+38
+tf_efficientnetv2_b3,16.493,83.507,48.400,51.600,14.36,300,0.904,bicubic,-78.677,-50.420,-47
+inception_resnet_v2,16.467,83.533,44.720,55.280,55.84,299,0.897,bicubic,-78.073,-53.910,+10
+gluon_resnet152_v1s,16.467,83.533,44.227,55.773,60.32,224,0.875,bicubic,-78.583,-54.363,-37
+tresnet_l,16.413,83.587,49.587,50.413,55.99,224,0.875,bilinear,-78.877,-49.423,-58
 resmlp_24_distilled_224,16.253,83.747,49.960,50.040,30.02,224,0.875,bicubic,-78.197,-48.810,+19
-gluon_xception65,16.240,83.760,45.933,54.067,39.92,299,0.903,bicubic,-78.020,-52.637,+36
-gcresnet50t,16.227,83.773,48.107,51.893,25.90,256,0.900,bicubic,-78.633,-50.693,-20
-gernet_l,16.187,83.813,46.973,53.027,31.08,256,0.875,bilinear,-78.923,-51.927,-47
-wide_resnet50_2,16.187,83.813,48.053,51.947,68.88,224,0.875,bicubic,-78.863,-50.917,-39
+gluon_xception65,16.240,83.760,45.933,54.067,39.92,299,0.903,bicubic,-78.020,-52.637,+35
+gcresnet50t,16.227,83.773,48.107,51.893,25.90,256,0.900,bicubic,-78.633,-50.693,-23
+gernet_l,16.187,83.813,46.973,53.027,31.08,256,0.875,bilinear,-78.923,-51.927,-50
+wide_resnet50_2,16.187,83.813,48.053,51.947,68.88,224,0.875,bicubic,-78.863,-50.877,-41
 gluon_resnet152_v1d,16.160,83.840,44.107,55.893,60.21,224,0.875,bicubic,-78.590,-54.633,-15
-ens_adv_inception_resnet_v2,16.093,83.907,43.413,56.587,55.84,299,0.897,bicubic,-78.067,-55.197,+44
-gmlp_s16_224,16.093,83.907,44.693,55.307,19.42,224,0.875,bicubic,-78.057,-53.807,+45
+gmlp_s16_224,16.093,83.907,44.693,55.307,19.42,224,0.875,bicubic,-78.057,-53.807,+46
+ens_adv_inception_resnet_v2,16.093,83.907,43.413,56.587,55.84,299,0.897,bicubic,-78.067,-55.197,+43
 gcresnext50ts,16.040,83.960,46.080,53.920,15.67,256,0.900,bicubic,-78.440,-52.590,+6
 xcit_tiny_24_p16_224,16.027,83.973,45.600,54.400,12.12,224,1.000,bicubic,-78.053,-52.910,+53
-xception65,15.907,84.093,43.467,56.533,39.92,299,0.903,bicubic,-77.863,-54.893,+74
-ssl_resnet50,15.840,84.160,49.280,50.720,25.56,224,0.875,bilinear,-78.630,-49.640,+7
+xception65,15.907,84.093,43.467,56.533,39.92,299,0.903,bicubic,-77.863,-54.893,+75
+ssl_resnet50,15.840,84.160,49.280,50.720,25.56,224,0.875,bilinear,-78.630,-49.640,+6
 repvgg_b3g4,15.813,84.187,47.373,52.627,83.83,224,0.875,bilinear,-78.717,-51.587,-3
-ecaresnet26t,15.480,84.520,47.800,52.200,16.01,320,0.950,bicubic,-78.820,-50.910,+19
-ecaresnet101d_pruned,15.480,84.520,47.933,52.067,24.88,224,0.875,bicubic,-79.590,-51.047,-54
+ecaresnet26t,15.480,84.520,47.800,52.200,16.01,320,0.950,bicubic,-78.820,-50.910,+18
+ecaresnet101d_pruned,15.480,84.520,47.933,52.067,24.88,224,0.875,bicubic,-79.590,-51.047,-57
 regnety_320,15.453,84.547,44.560,55.440,145.05,224,0.875,bicubic,-79.097,-54.290,-9
-coat_tiny,15.440,84.560,45.560,54.440,5.50,224,0.900,bicubic,-78.140,-52.850,+83
-convmixer_768_32,15.360,84.640,47.667,52.333,21.11,224,0.960,bicubic,-79.130,-50.953,-5
-ecaresnetlight,15.160,84.840,45.680,54.320,30.16,224,0.875,bicubic,-79.610,-53.120,-30
+coat_tiny,15.440,84.560,45.560,54.440,5.50,224,0.900,bicubic,-78.140,-52.850,+85
+convmixer_768_32,15.360,84.640,47.667,52.333,21.11,224,0.960,bicubic,-79.130,-51.183,-6
+ecaresnetlight,15.160,84.840,45.680,54.320,30.16,224,0.875,bicubic,-79.610,-53.120,-31
 skresnext50_32x4d,15.107,84.893,44.467,55.533,27.48,224,0.875,bicubic,-79.153,-54.003,+19
-cait_xxs24_224,14.893,85.107,44.547,55.453,11.96,224,1.000,bicubic,-78.697,-53.893,+78
+cait_xxs24_224,14.893,85.107,44.547,55.453,11.96,224,1.000,bicubic,-78.697,-53.893,+79
 levit_192,14.667,85.333,44.627,55.373,10.95,224,0.900,bicubic,-79.513,-53.933,+27
 efficientnet_el_pruned,14.373,85.627,45.853,54.147,10.59,300,0.904,bicubic,-80.017,-52.897,+3
-rexnet_150,14.347,85.653,46.587,53.413,9.73,224,0.875,bicubic,-80.123,-52.203,-6
+rexnet_150,14.347,85.653,46.587,53.413,9.73,224,0.875,bicubic,-80.123,-52.203,-5
 efficientnet_b2,14.307,85.693,45.773,54.227,9.11,288,1.000,bicubic,-80.323,-52.937,-26
 coat_lite_mini,14.280,85.720,44.347,55.653,11.01,224,0.900,bicubic,-79.770,-54.193,+38
-seresnet33ts,14.267,85.733,45.707,54.293,19.78,256,0.900,bicubic,-80.603,-53.083,-45
+seresnet33ts,14.267,85.733,45.707,54.293,19.78,256,0.900,bicubic,-80.603,-53.153,-49
 seresnet50,14.040,85.960,45.347,54.653,28.09,224,0.875,bicubic,-80.520,-53.403,-22
-eca_resnet33ts,14.013,85.987,46.907,53.093,19.68,256,0.900,bicubic,-80.187,-51.433,+16
+eca_resnet33ts,14.013,85.987,46.907,53.093,19.68,256,0.900,bicubic,-80.187,-51.863,+15
 gernet_m,14.000,86.000,45.853,54.147,21.14,224,0.875,bilinear,-80.620,-53.007,-28
 legacy_seresnext101_32x4d,13.867,86.133,42.653,57.347,48.96,224,0.875,bilinear,-80.483,-55.977,-2
-gluon_resnext101_32x4d,13.667,86.333,41.480,58.520,44.18,224,0.875,bicubic,-80.873,-57.150,-24
-gluon_seresnext50_32x4d,13.453,86.547,43.507,56.493,27.56,224,0.875,bicubic,-80.877,-55.113,-3
+gluon_resnext101_32x4d,13.667,86.333,41.480,58.520,44.18,224,0.875,bicubic,-80.873,-57.310,-23
+gluon_seresnext50_32x4d,13.453,86.547,43.507,56.493,27.56,224,0.875,bicubic,-80.877,-55.113,-2
 resmlp_36_224,13.400,86.600,46.267,53.733,44.69,224,0.875,bicubic,-80.790,-52.393,+12
-gcresnet33ts,13.360,86.640,44.480,55.520,19.88,256,0.900,bicubic,-81.120,-54.300,-21
-repvgg_b2g4,13.240,86.760,43.453,56.547,61.76,224,0.875,bilinear,-80.600,-55.147,+43
+gcresnet33ts,13.360,86.640,44.480,55.520,19.88,256,0.900,bicubic,-81.120,-54.300,-19
+eca_botnext26ts_256,13.320,86.680,42.147,57.853,10.59,256,0.950,bicubic,-80.470,-56.353,+47
+repvgg_b2g4,13.240,86.760,43.453,56.547,61.76,224,0.875,bilinear,-80.600,-55.147,+41
 regnetx_320,13.187,86.813,40.240,59.760,107.81,224,0.875,bicubic,-81.253,-58.490,-16
-ese_vovnet39b,13.147,86.853,43.667,56.333,24.57,224,0.875,bicubic,-80.943,-54.993,+23
-pit_xs_distilled_224,13.120,86.880,44.440,55.560,11.00,224,0.900,bicubic,-80.700,-54.230,+43
-mixnet_xl,13.000,87.000,43.133,56.867,11.90,224,0.875,bicubic,-81.200,-55.637,+3
-efficientnet_b3_pruned,12.987,87.013,44.813,55.187,9.86,300,0.904,bicubic,-81.633,-53.957,-40
-nf_regnet_b1,12.840,87.160,44.027,55.973,10.22,288,0.900,bicubic,-81.280,-54.593,+16
+ese_vovnet39b,13.147,86.853,43.667,56.333,24.57,224,0.875,bicubic,-80.943,-54.993,+22
+pit_xs_distilled_224,13.120,86.880,44.440,55.560,11.00,224,0.900,bicubic,-80.700,-54.230,+42
+mixnet_xl,13.000,87.000,43.133,56.867,11.90,224,0.875,bicubic,-81.200,-55.207,+2
+efficientnet_b3_pruned,12.987,87.013,44.813,55.187,9.86,300,0.904,bicubic,-81.633,-53.957,-41
+nf_regnet_b1,12.840,87.160,44.027,55.973,10.22,288,0.900,bicubic,-81.280,-54.553,+16
 gluon_resnet101_v1d,12.747,87.253,41.280,58.720,44.57,224,0.875,bicubic,-81.453,-57.290,+1
-pit_xs_224,12.747,87.253,42.627,57.373,10.62,224,0.900,bicubic,-80.373,-55.693,+91
-crossvit_9_dagger_240,12.560,87.440,41.480,58.520,8.78,240,0.875,bicubic,-80.360,-56.770,+103
-gluon_inception_v3,12.520,87.480,40.187,59.813,23.83,299,0.875,bicubic,-80.940,-58.373,+66
-resmlp_24_224,12.387,87.613,43.133,56.867,30.02,224,0.875,bicubic,-81.633,-55.197,+18
-coat_lite_tiny,12.267,87.733,41.067,58.933,5.72,224,0.900,bicubic,-80.953,-57.203,+82
-regnety_120,12.240,87.760,41.880,58.120,51.82,224,0.875,bicubic,-82.240,-56.930,-33
-gluon_resnet101_v1s,12.000,88.000,40.773,59.227,44.67,224,0.875,bicubic,-82.700,-58.047,-55
+pit_xs_224,12.747,87.253,42.627,57.373,10.62,224,0.900,bicubic,-80.373,-55.693,+93
+crossvit_9_dagger_240,12.560,87.440,41.480,58.520,8.78,240,0.875,bicubic,-80.360,-56.770,+104
+gluon_inception_v3,12.520,87.480,40.187,59.813,23.83,299,0.875,bicubic,-80.940,-58.373,+67
+resmlp_24_224,12.387,87.613,43.133,56.867,30.02,224,0.875,bicubic,-81.633,-55.197,+17
+coat_lite_tiny,12.267,87.733,41.067,58.933,5.72,224,0.900,bicubic,-80.953,-57.203,+83
+regnety_120,12.240,87.760,41.880,58.120,51.82,224,0.875,bicubic,-82.240,-56.930,-36
+gluon_resnet101_v1s,12.000,88.000,40.773,59.227,44.67,224,0.875,bicubic,-82.700,-58.047,-56
 efficientnet_em,11.960,88.040,43.667,56.333,6.90,240,0.882,bicubic,-81.880,-55.143,+27
-hrnet_w64,11.867,88.133,40.560,59.440,128.06,224,0.875,bilinear,-82.123,-58.060,+15
+hrnet_w64,11.867,88.133,40.560,59.440,128.06,224,0.875,bilinear,-82.123,-58.060,+14
 xcit_tiny_12_p16_224_dist,11.707,88.293,39.840,60.160,6.72,224,1.000,bicubic,-81.693,-58.650,+65
-cspdarknet53,11.680,88.320,42.880,57.120,27.64,256,0.887,bilinear,-82.990,-55.930,-58
-nf_resnet50,11.680,88.320,45.320,54.680,25.56,288,0.940,bicubic,-82.880,-53.470,-50
-resnet50d,11.640,88.360,42.080,57.920,25.58,224,0.875,bicubic,-82.630,-56.640,-20
+cspdarknet53,11.680,88.320,42.880,57.120,27.64,256,0.887,bilinear,-82.990,-55.930,-59
+nf_resnet50,11.680,88.320,45.320,54.680,25.56,288,0.940,bicubic,-82.880,-53.470,-51
+resnet50d,11.640,88.360,42.080,57.920,25.58,224,0.875,bicubic,-82.630,-56.640,-21
+botnet26t_256,11.613,88.387,40.133,59.867,12.49,256,0.950,bicubic,-81.887,-58.167,+50
 gmixer_24_224,11.600,88.400,37.173,62.827,24.72,224,0.875,bicubic,-81.240,-60.707,+94
 xception41,11.547,88.453,38.760,61.240,26.97,299,0.903,bicubic,-81.863,-59.660,+58
 vit_small_patch32_224,11.507,88.493,39.453,60.547,22.88,224,0.900,bicubic,-80.523,-58.777,+137
-dla102x2,11.400,88.600,41.240,58.760,41.28,224,0.875,bilinear,-82.560,-57.240,+9
-dpn92,11.333,88.667,39.507,60.493,37.67,224,0.875,bicubic,-82.887,-59.223,-20
-lambda_resnet26t,11.293,88.707,39.987,60.013,10.96,256,0.940,bicubic,-82.527,-58.663,+19
-efficientnet_b2_pruned,11.253,88.747,41.773,58.227,8.31,260,0.890,bicubic,-82.887,-56.747,-7
-regnety_080,11.253,88.747,40.627,59.373,39.18,224,0.875,bicubic,-82.927,-58.053,-14
-levit_128,11.213,88.787,40.053,59.947,9.21,224,0.900,bicubic,-82.127,-58.327,+56
-xcit_nano_12_p16_384_dist,11.187,88.813,39.560,60.440,3.05,384,1.000,bicubic,-80.643,-58.450,+143
-tf_efficientnet_el,11.173,88.827,41.360,58.640,10.59,300,0.904,bicubic,-83.227,-57.350,-42
-tf_efficientnet_b0_ns,11.080,88.920,39.880,60.120,5.29,224,0.875,bicubic,-82.540,-58.760,+29
-ecaresnet50d_pruned,11.000,89.000,42.013,57.987,19.94,224,0.875,bicubic,-83.210,-56.717,-27
+dla102x2,11.400,88.600,41.240,58.760,41.28,224,0.875,bilinear,-82.560,-57.240,+7
+dpn92,11.333,88.667,39.507,60.493,37.67,224,0.875,bicubic,-82.887,-59.223,-22
+lambda_resnet26t,11.293,88.707,39.987,60.013,10.96,256,0.940,bicubic,-82.527,-58.663,+17
+regnety_080,11.253,88.747,40.627,59.373,39.18,224,0.875,bicubic,-82.927,-58.053,-15
+efficientnet_b2_pruned,11.253,88.747,41.773,58.227,8.31,260,0.890,bicubic,-82.887,-56.747,-10
+levit_128,11.213,88.787,40.053,59.947,9.21,224,0.900,bicubic,-82.127,-58.547,+55
+xcit_nano_12_p16_384_dist,11.187,88.813,39.560,60.440,3.05,384,1.000,bicubic,-80.643,-58.450,+142
+tf_efficientnet_el,11.173,88.827,41.360,58.640,10.59,300,0.904,bicubic,-83.227,-57.330,-44
+tf_efficientnet_b0_ns,11.080,88.920,39.880,60.120,5.29,224,0.875,bicubic,-82.540,-58.760,+28
+ecaresnet50d_pruned,11.000,89.000,42.013,57.987,19.94,224,0.875,bicubic,-83.210,-56.717,-29
 vit_tiny_r_s16_p8_384,10.933,89.067,39.427,60.573,6.36,384,1.000,bicubic,-81.097,-58.863,+127
 xcit_tiny_12_p16_224,10.920,89.080,36.840,63.160,6.72,224,1.000,bicubic,-81.570,-61.410,+105
-eca_halonext26ts,10.867,89.133,39.560,60.440,10.76,256,0.940,bicubic,-82.643,-58.720,+33
-hrnet_w48,10.853,89.147,39.973,60.027,77.47,224,0.875,bilinear,-83.087,-58.637,-3
-tf_efficientnetv2_b2,10.853,89.147,39.493,60.507,10.10,260,0.890,bicubic,-83.557,-59.077,-51
+eca_halonext26ts,10.867,89.133,39.560,60.440,10.76,256,0.940,bicubic,-82.643,-58.940,+31
+hrnet_w48,10.853,89.147,39.973,60.027,77.47,224,0.875,bilinear,-83.087,-58.637,-6
+tf_efficientnetv2_b2,10.853,89.147,39.493,60.507,10.10,260,0.890,bicubic,-83.557,-59.077,-52
 dpn107,10.827,89.173,38.453,61.547,86.92,224,0.875,bicubic,-83.473,-60.017,-44
-tf_inception_v3,10.827,89.173,36.680,63.320,23.83,299,0.875,bicubic,-82.503,-61.830,+45
-adv_inception_v3,10.827,89.173,36.480,63.520,23.83,299,0.875,bicubic,-82.063,-61.650,+74
-halonet26t,10.813,89.187,38.587,61.413,12.48,256,0.950,bicubic,-83.167,-59.903,-10
-gluon_resnet152_v1c,10.747,89.253,36.840,63.160,60.21,224,0.875,bicubic,-83.413,-61.800,-27
-resnext50_32x4d,10.640,89.360,40.213,59.787,25.03,224,0.875,bicubic,-83.470,-58.137,-20
+tf_inception_v3,10.827,89.173,36.680,63.320,23.83,299,0.875,bicubic,-82.503,-61.360,+47
+adv_inception_v3,10.827,89.173,36.480,63.520,23.83,299,0.875,bicubic,-82.063,-61.650,+72
+halonet26t,10.813,89.187,38.587,61.413,12.48,256,0.950,bicubic,-83.167,-59.903,-12
+gluon_resnet152_v1c,10.747,89.253,36.840,63.160,60.21,224,0.875,bicubic,-83.413,-61.800,-29
+resnext50_32x4d,10.640,89.360,40.213,59.787,25.03,224,0.875,bicubic,-83.470,-58.137,-22
 xcit_nano_12_p8_224_dist,10.573,89.427,38.053,61.947,3.05,224,1.000,bicubic,-81.527,-60.107,+113
-dpn131,10.560,89.440,37.000,63.000,79.25,224,0.875,bicubic,-83.430,-61.720,-16
-resnetv2_50,10.547,89.453,39.173,60.827,25.55,224,0.950,bicubic,-83.893,-59.557,-61
-resnext50d_32x4d,10.427,89.573,39.333,60.667,25.05,224,0.875,bicubic,-83.763,-59.237,-37
-tf_efficientnet_b2_ap,10.413,89.587,39.760,60.240,9.11,260,0.890,bicubic,-84.077,-59.090,-73
-hrnet_w44,10.333,89.667,39.200,60.800,67.06,224,0.875,bilinear,-83.247,-59.500,+15
-rexnet_130,10.333,89.667,41.387,58.613,7.56,224,0.875,bicubic,-83.567,-57.013,-13
-xcit_nano_12_p8_224,10.213,89.787,37.200,62.800,3.05,224,1.000,bicubic,-80.777,-60.600,+144
-cspresnext50,10.133,89.867,40.213,59.787,20.57,224,0.875,bilinear,-84.337,-58.467,-72
-dpn98,10.120,89.880,36.440,63.560,61.57,224,0.875,bicubic,-84.000,-62.140,-33
-resnetrs50,10.067,89.933,37.227,62.773,35.69,224,0.910,bicubic,-84.223,-61.413,-57
-resnet50,10.000,90.000,37.947,62.053,25.56,224,0.950,bicubic,-84.330,-60.493,-62
-regnety_064,10.000,90.000,38.960,61.040,30.58,224,0.875,bicubic,-84.150,-59.780,-38
-regnetx_160,9.973,90.027,37.760,62.240,54.28,224,0.875,bicubic,-84.147,-60.980,-35
-resnext101_32x8d,9.947,90.053,37.453,62.547,88.79,224,0.875,bilinear,-83.843,-61.127,-12
-lambda_resnet26rpt_256,9.907,90.093,37.520,62.480,10.99,256,0.940,bicubic,-83.813,-60.980,-8
-legacy_seresnext50_32x4d,9.880,90.120,39.013,60.987,27.56,224,0.875,bilinear,-83.840,-59.567,-8
+dpn131,10.560,89.440,37.000,63.000,79.25,224,0.875,bicubic,-83.430,-61.720,-18
+resnetv2_50,10.547,89.453,39.173,60.827,25.55,224,0.950,bicubic,-83.893,-59.557,-64
+resnext50d_32x4d,10.427,89.573,39.333,60.667,25.05,224,0.875,bicubic,-83.763,-59.237,-39
+tf_efficientnet_b2_ap,10.413,89.587,39.760,60.240,9.11,260,0.890,bicubic,-84.077,-58.860,-74
+hrnet_w44,10.333,89.667,39.200,60.800,67.06,224,0.875,bilinear,-83.247,-59.500,+13
+rexnet_130,10.333,89.667,41.387,58.613,7.56,224,0.875,bicubic,-83.567,-57.013,-15
+xcit_nano_12_p8_224,10.213,89.787,37.200,62.800,3.05,224,1.000,bicubic,-80.777,-60.600,+143
+cspresnext50,10.133,89.867,40.213,59.787,20.57,224,0.875,bilinear,-84.337,-58.467,-74
+dpn98,10.120,89.880,36.440,63.560,61.57,224,0.875,bicubic,-84.000,-62.180,-35
+resnetrs50,10.067,89.933,37.227,62.773,35.69,224,0.910,bicubic,-84.223,-61.413,-58
+regnety_064,10.000,90.000,38.960,61.040,30.58,224,0.875,bicubic,-84.150,-59.780,-40
+resnet50,10.000,90.000,37.947,62.053,25.56,224,0.950,bicubic,-84.330,-60.493,-65
+regnetx_160,9.973,90.027,37.760,62.240,54.28,224,0.875,bicubic,-84.147,-60.980,-38
+resnext101_32x8d,9.947,90.053,37.453,62.547,88.79,224,0.875,bilinear,-83.843,-61.127,-13
+lambda_resnet26rpt_256,9.907,90.093,37.520,62.480,10.99,256,0.940,bicubic,-83.813,-61.020,-6
+legacy_seresnext50_32x4d,9.880,90.120,39.013,60.987,27.56,224,0.875,bilinear,-83.840,-59.307,-8
 efficientnet_b1,9.867,90.133,37.293,62.707,7.79,256,1.000,bicubic,-83.373,-60.997,+31
-xception,9.853,90.147,37.920,62.080,22.86,299,0.897,bicubic,-83.627,-60.600,+11
+xception,9.853,90.147,37.920,62.080,22.86,299,0.897,bicubic,-83.627,-60.610,+11
 inception_v3,9.827,90.173,35.040,64.960,23.83,299,0.875,bicubic,-82.893,-62.920,+62
-tf_efficientnet_b2,9.653,90.347,38.640,61.360,9.11,260,0.890,bicubic,-84.717,-59.940,-74
-tf_efficientnet_cc_b1_8e,9.613,90.387,36.867,63.133,39.72,240,0.882,bicubic,-84.307,-61.383,-29
-dpn68b,9.587,90.413,37.720,62.280,12.61,224,0.875,bicubic,-84.093,-60.810,-10
-gluon_resnet152_v1b,9.573,90.427,35.707,64.293,60.19,224,0.875,bicubic,-84.507,-62.753,-42
-tf_efficientnet_lite3,9.480,90.520,38.947,61.053,8.20,300,0.904,bilinear,-84.710,-59.693,-57
-res2net101_26w_4s,9.413,90.587,34.440,65.560,45.21,224,0.875,bilinear,-84.307,-63.880,-16
+tf_efficientnet_b2,9.653,90.347,38.640,61.360,9.11,260,0.890,bicubic,-84.717,-59.970,-75
+tf_efficientnet_cc_b1_8e,9.613,90.387,36.867,63.133,39.72,240,0.882,bicubic,-84.307,-61.383,-31
+dpn68b,9.587,90.413,37.720,62.280,12.61,224,0.875,bicubic,-84.093,-60.810,-11
+gluon_resnet152_v1b,9.573,90.427,35.707,64.293,60.19,224,0.875,bicubic,-84.507,-62.753,-44
+tf_efficientnet_lite3,9.480,90.520,38.947,61.053,8.20,300,0.904,bilinear,-84.710,-59.693,-59
+res2net101_26w_4s,9.413,90.587,34.440,65.560,45.21,224,0.875,bilinear,-84.307,-64.140,-18
 legacy_seresnet152,9.240,90.760,37.093,62.907,66.82,224,0.875,bilinear,-84.180,-61.247,+8
-cspresnet50,9.227,90.773,39.493,60.507,21.62,256,0.887,bilinear,-84.523,-59.137,-22
-hrnet_w40,9.120,90.880,36.533,63.467,57.56,224,0.875,bilinear,-84.370,-62.197,-1
-regnetx_120,9.067,90.933,36.947,63.053,46.11,224,0.875,bicubic,-85.173,-61.723,-70
+cspresnet50,9.227,90.773,39.493,60.507,21.62,256,0.887,bilinear,-84.523,-59.137,-23
+hrnet_w40,9.120,90.880,36.533,63.467,57.56,224,0.875,bilinear,-84.370,-62.057,-1
+regnetx_120,9.067,90.933,36.947,63.053,46.11,224,0.875,bicubic,-85.173,-61.723,-72
 vit_tiny_patch16_224,9.040,90.960,34.267,65.733,5.72,224,0.900,bicubic,-82.720,-63.773,+100
-gluon_resnext50_32x4d,9.027,90.973,36.307,63.693,25.03,224,0.875,bicubic,-84.793,-62.103,-32
-vit_base_patch16_sam_224,9.013,90.987,36.080,63.920,86.57,224,0.900,bicubic,-85.137,-62.590,-58
-resnest26d,9.000,91.000,37.533,62.467,17.07,224,0.875,bilinear,-84.360,-61.107,+5
+gluon_resnext50_32x4d,9.027,90.973,36.307,63.693,25.03,224,0.875,bicubic,-84.793,-62.103,-34
+vit_base_patch16_sam_224,9.013,90.987,36.080,63.920,86.57,224,0.900,bicubic,-85.137,-62.590,-60
 resnet33ts,9.000,91.000,38.240,61.760,19.68,256,0.900,bicubic,-84.600,-60.290,-17
-crossvit_tiny_240,8.893,91.107,34.320,65.680,7.01,240,0.875,bicubic,-81.357,-63.290,+132
-bat_resnext26ts,8.867,91.133,35.987,64.013,10.73,256,0.900,bicubic,-84.443,-62.043,+9
-regnety_040,8.853,91.147,37.000,63.000,20.65,224,0.875,bicubic,-85.007,-61.640,-41
-rexnet_100,8.827,91.173,36.240,63.760,4.80,224,0.875,bicubic,-84.203,-62.130,+21
+resnest26d,9.000,91.000,37.533,62.467,17.07,224,0.875,bilinear,-84.360,-61.107,+4
+crossvit_tiny_240,8.893,91.107,34.320,65.680,7.01,240,0.875,bicubic,-81.357,-63.290,+131
+bat_resnext26ts,8.867,91.133,35.987,64.013,10.73,256,0.900,bicubic,-84.443,-62.363,+9
+regnety_040,8.853,91.147,37.000,63.000,20.65,224,0.875,bicubic,-85.007,-61.640,-43
+rexnet_100,8.827,91.173,36.240,63.760,4.80,224,0.875,bicubic,-84.203,-61.950,+23
 seresnext26t_32x4d,8.813,91.187,36.573,63.427,16.81,224,0.875,bicubic,-83.997,-61.797,+34
 seresnext26d_32x4d,8.800,91.200,36.467,63.533,16.81,224,0.875,bicubic,-83.940,-61.683,+40
-mixnet_l,8.733,91.267,36.173,63.827,7.33,224,0.875,bicubic,-84.697,-62.047,-9
-mobilenetv3_large_100_miil,8.720,91.280,32.893,67.107,5.48,224,0.875,bilinear,-83.550,-64.747,+64
+mixnet_l,8.733,91.267,36.173,63.827,7.33,224,0.875,bicubic,-84.697,-62.047,-8
+mobilenetv3_large_100_miil,8.720,91.280,32.893,67.107,5.48,224,0.875,bilinear,-83.550,-65.207,+63
 convit_tiny,8.693,91.307,33.987,66.013,5.71,224,0.875,bicubic,-81.917,-63.743,+118
 levit_128s,8.667,91.333,32.800,67.200,7.78,224,0.900,bicubic,-83.283,-65.260,+76
-gcresnext26ts,8.560,91.440,35.547,64.453,10.48,256,0.900,bicubic,-84.210,-62.493,+30
+gcresnext26ts,8.560,91.440,35.547,64.453,10.48,256,0.900,bicubic,-84.210,-62.723,+31
 hrnet_w30,8.533,91.467,36.800,63.200,37.71,224,0.875,bilinear,-84.667,-61.610,+5
 resnet32ts,8.480,91.520,36.880,63.120,17.96,256,0.900,bicubic,-84.990,-61.610,-17
-dla169,8.373,91.627,35.867,64.133,53.39,224,0.875,bilinear,-84.967,-62.733,-9
-mixer_b16_224,8.360,91.640,29.320,70.680,59.88,224,0.875,bicubic,-83.500,-68.610,+77
-tf_efficientnet_b1_ap,8.333,91.667,35.160,64.840,7.79,240,0.882,bicubic,-85.377,-63.200,-39
+dla169,8.373,91.627,35.867,64.133,53.39,224,0.875,bilinear,-84.967,-62.513,-8
+mixer_b16_224,8.360,91.640,29.320,70.680,59.88,224,0.875,bicubic,-83.500,-67.910,+76
+tf_efficientnet_b1_ap,8.333,91.667,35.160,64.840,7.79,240,0.882,bicubic,-85.377,-63.200,-40
 legacy_seresnet101,8.253,91.747,35.747,64.253,49.33,224,0.875,bilinear,-85.047,-62.753,-5
-resnetblur50,8.213,91.787,37.360,62.640,25.56,224,0.875,bicubic,-85.717,-61.220,-61
-repvgg_b2,8.173,91.827,36.040,63.960,89.02,224,0.875,bilinear,-85.317,-62.550,-27
-dla102x,8.160,91.840,36.787,63.213,26.31,224,0.875,bilinear,-85.350,-61.713,-31
+resnetblur50,8.213,91.787,37.360,62.640,25.56,224,0.875,bicubic,-85.717,-61.220,-63
+repvgg_b2,8.173,91.827,36.040,63.960,89.02,224,0.875,bilinear,-85.317,-62.690,-27
+dla102x,8.160,91.840,36.787,63.213,26.31,224,0.875,bilinear,-85.350,-61.573,-30
 crossvit_9_240,8.147,91.853,34.027,65.973,8.55,240,0.875,bicubic,-82.513,-63.713,+105
-eca_botnext26ts_256,8.133,91.867,30.947,69.053,10.59,256,0.950,bicubic,-82.417,-66.303,+106
-eca_resnext26ts,8.120,91.880,35.747,64.253,10.30,256,0.900,bicubic,-84.540,-62.513,+29
-resmlp_12_distilled_224,8.080,91.920,36.573,63.427,15.35,224,0.875,bicubic,-84.750,-61.567,+13
+eca_resnext26ts,8.120,91.880,35.747,64.253,10.30,256,0.900,bicubic,-84.540,-62.513,+30
+resmlp_12_distilled_224,8.080,91.920,36.573,63.427,15.35,224,0.875,bicubic,-84.750,-61.567,+14
 hrnet_w32,7.947,92.053,37.267,62.733,41.23,224,0.875,bilinear,-85.573,-61.173,-37
 gluon_resnet50_v1d,7.840,92.160,34.773,65.227,25.58,224,0.875,bicubic,-85.940,-63.627,-57
 res2net50_26w_8s,7.813,92.187,33.147,66.853,48.40,224,0.875,bilinear,-85.617,-65.033,-28
 gluon_resnet101_v1c,7.800,92.200,32.973,67.027,44.57,224,0.875,bicubic,-85.860,-65.437,-49
-dla60_res2next,7.733,92.267,34.653,65.347,17.03,224,0.875,bilinear,-85.447,-63.757,-11
-tf_efficientnetv2_b1,7.720,92.280,34.360,65.640,8.14,240,0.882,bicubic,-86.220,-64.260,-74
-deit_tiny_distilled_patch16_224,7.707,92.293,33.520,66.480,5.91,224,0.900,bicubic,-83.023,-64.060,+92
-densenetblur121d,7.573,92.427,34.587,65.413,8.00,224,0.875,bicubic,-84.337,-63.503,+57
-dla60_res2net,7.373,92.627,34.400,65.600,20.85,224,0.875,bilinear,-85.787,-64.010,-14
-regnetx_064,7.333,92.667,34.360,65.640,26.21,224,0.875,bicubic,-86.557,-64.270,-74
-wide_resnet101_2,7.307,92.693,33.693,66.307,126.89,224,0.875,bilinear,-86.413,-64.847,-59
-efficientnet_b1_pruned,7.280,92.720,34.427,65.573,6.33,240,0.882,bicubic,-85.490,-63.843,+6
-deit_tiny_patch16_224,7.227,92.773,30.667,69.333,5.72,224,0.900,bicubic,-82.443,-66.773,+106
-hardcorenas_e,7.227,92.773,33.160,66.840,8.07,224,0.875,bilinear,-85.353,-64.950,+19
-efficientnet_b0,7.213,92.787,33.840,66.160,5.29,224,0.875,bicubic,-85.457,-64.240,+12
+dla60_res2next,7.733,92.267,34.653,65.347,17.03,224,0.875,bilinear,-85.447,-63.757,-10
+tf_efficientnetv2_b1,7.720,92.280,34.360,65.640,8.14,240,0.882,bicubic,-86.220,-64.260,-75
+deit_tiny_distilled_patch16_224,7.707,92.293,33.520,66.480,5.91,224,0.900,bicubic,-83.023,-64.060,+93
+densenetblur121d,7.573,92.427,34.587,65.413,8.00,224,0.875,bicubic,-84.337,-63.513,+58
+dla60_res2net,7.373,92.627,34.400,65.600,20.85,224,0.875,bilinear,-85.787,-64.010,-13
+regnetx_064,7.333,92.667,34.360,65.640,26.21,224,0.875,bicubic,-86.557,-64.270,-75
+wide_resnet101_2,7.307,92.693,33.693,66.307,126.89,224,0.875,bilinear,-86.413,-64.807,-62
+efficientnet_b1_pruned,7.280,92.720,34.427,65.573,6.33,240,0.882,bicubic,-85.490,-63.613,+6
+hardcorenas_e,7.227,92.773,33.160,66.840,8.07,224,0.875,bilinear,-85.353,-64.950,+21
+deit_tiny_patch16_224,7.227,92.773,30.667,69.333,5.72,224,0.900,bicubic,-82.443,-66.773,+105
+efficientnet_b0,7.213,92.787,33.840,66.160,5.29,224,0.875,bicubic,-85.457,-64.240,+13
 gluon_resnet101_v1b,7.160,92.840,32.720,67.280,44.55,224,0.875,bicubic,-86.570,-65.680,-68
-tf_efficientnet_cc_b0_8e,7.120,92.880,31.653,68.347,24.01,224,0.875,bicubic,-85.700,-66.527,-4
-tf_efficientnet_b1,7.120,92.880,33.107,66.893,7.79,240,0.882,bicubic,-86.390,-65.253,-50
-gluon_resnet50_v1s,7.080,92.920,33.200,66.800,25.68,224,0.875,bicubic,-86.550,-65.270,-62
-tf_mixnet_l,7.080,92.920,31.587,68.413,7.33,224,0.875,bicubic,-86.230,-66.763,-34
-resmlp_12_224,7.067,92.933,33.853,66.147,15.35,224,0.875,bicubic,-85.123,-64.307,+31
-convmixer_1024_20_ks9_p14,7.027,92.973,32.693,67.307,24.38,224,0.960,bicubic,-85.403,-65.577,+18
-seresnext26ts,6.933,93.067,34.600,65.400,10.39,256,0.900,bicubic,-85.747,-63.700,+3
-hardcorenas_f,6.853,93.147,33.907,66.093,8.20,224,0.875,bilinear,-86.097,-64.253,-18
-mixnet_m,6.667,93.333,32.040,67.960,5.01,224,0.875,bicubic,-85.773,-65.830,+14
-ese_vovnet19b_dw,6.627,93.373,33.107,66.893,6.54,224,0.875,bicubic,-85.643,-64.993,+21
-selecsls60b,6.613,93.387,33.133,66.867,32.77,224,0.875,bicubic,-86.677,-65.147,-38
-efficientnet_es,6.560,93.440,33.693,66.307,5.44,224,0.875,bicubic,-86.640,-64.707,-36
-pit_ti_distilled_224,6.547,93.453,30.507,69.493,5.10,224,0.900,bicubic,-84.333,-67.213,+68
-res2net50_26w_6s,6.507,93.493,31.467,68.533,37.05,224,0.875,bilinear,-86.893,-66.813,-52
-hardcorenas_d,6.453,93.547,32.053,67.947,7.50,224,0.875,bilinear,-85.967,-66.017,+10
-legacy_seresnext26_32x4d,6.440,93.560,32.920,67.080,16.79,224,0.875,bicubic,-86.190,-65.200,-2
-skresnet34,6.387,93.613,31.493,68.507,22.28,224,0.875,bicubic,-85.993,-66.647,+10
-regnetx_080,6.360,93.640,32.213,67.787,39.57,224,0.875,bicubic,-87.510,-66.307,-97
-resnet34d,6.347,93.653,31.680,68.320,21.82,224,0.875,bicubic,-86.353,-66.620,-10
-dla60x,6.307,93.693,33.787,66.213,17.35,224,0.875,bilinear,-86.783,-64.703,-37
-repvgg_b1,6.240,93.760,33.307,66.693,57.42,224,0.875,bilinear,-87.090,-65.083,-52
-swsl_resnet18,6.213,93.787,31.347,68.653,11.69,224,0.875,bilinear,-84.467,-66.363,+63
+tf_efficientnet_cc_b0_8e,7.120,92.880,31.653,68.347,24.01,224,0.875,bicubic,-85.700,-66.527,-2
+tf_efficientnet_b1,7.120,92.880,33.107,66.893,7.79,240,0.882,bicubic,-86.390,-65.173,-52
+tf_mixnet_l,7.080,92.920,31.587,68.413,7.33,224,0.875,bicubic,-86.230,-66.443,-32
+gluon_resnet50_v1s,7.080,92.920,33.200,66.800,25.68,224,0.875,bicubic,-86.550,-65.270,-63
+resmlp_12_224,7.067,92.933,33.853,66.147,15.35,224,0.875,bicubic,-85.123,-64.307,+32
+convmixer_1024_20_ks9_p14,7.027,92.973,32.693,67.307,24.38,224,0.960,bicubic,-85.403,-65.577,+19
+seresnext26ts,6.933,93.067,34.600,65.400,10.39,256,0.900,bicubic,-85.747,-63.700,+4
+hardcorenas_f,6.853,93.147,33.907,66.093,8.20,224,0.875,bilinear,-86.097,-64.253,-16
+mixnet_m,6.667,93.333,32.040,67.960,5.01,224,0.875,bicubic,-85.773,-65.830,+15
+ese_vovnet19b_dw,6.627,93.373,33.107,66.893,6.54,224,0.875,bicubic,-85.643,-64.533,+23
+selecsls60b,6.613,93.387,33.133,66.867,32.77,224,0.875,bicubic,-86.677,-65.147,-37
+efficientnet_es,6.560,93.440,33.693,66.307,5.44,224,0.875,bicubic,-86.640,-64.707,-35
+pit_ti_distilled_224,6.547,93.453,30.507,69.493,5.10,224,0.900,bicubic,-84.333,-67.213,+69
+res2net50_26w_6s,6.507,93.493,31.467,68.533,37.05,224,0.875,bilinear,-86.893,-66.813,-50
+hardcorenas_d,6.453,93.547,32.053,67.947,7.50,224,0.875,bilinear,-85.967,-66.017,+11
+legacy_seresnext26_32x4d,6.440,93.560,32.920,67.080,16.79,224,0.875,bicubic,-86.190,-65.200,-1
+skresnet34,6.387,93.613,31.493,68.507,22.28,224,0.875,bicubic,-85.993,-66.647,+11
+regnetx_080,6.360,93.640,32.213,67.787,39.57,224,0.875,bicubic,-87.510,-66.307,-98
+resnet34d,6.347,93.653,31.680,68.320,21.82,224,0.875,bicubic,-86.353,-66.620,-9
+dla60x,6.307,93.693,33.787,66.213,17.35,224,0.875,bilinear,-86.783,-64.703,-36
+repvgg_b1,6.240,93.760,33.307,66.693,57.42,224,0.875,bilinear,-87.090,-65.203,-53
+swsl_resnet18,6.213,93.787,31.347,68.653,11.69,224,0.875,bilinear,-84.467,-66.363,+64
 legacy_seresnet50,6.067,93.933,32.453,67.547,28.09,224,0.875,bilinear,-86.883,-65.737,-32
 pit_ti_224,6.053,93.947,30.053,69.947,4.85,224,0.900,bicubic,-83.877,-67.387,+74
-tv_resnet152,6.000,94.000,31.640,68.360,60.19,224,0.875,bilinear,-87.330,-66.400,-57
-resnet26t,5.987,94.013,31.720,68.280,16.01,256,0.940,bicubic,-86.763,-66.520,-21
-tf_efficientnet_cc_b0_4e,5.960,94.040,29.533,70.467,13.31,224,0.875,bicubic,-86.660,-68.547,-12
-tf_efficientnetv2_b0,5.893,94.107,30.613,69.387,7.14,224,0.875,bicubic,-87.217,-67.777,-46
-mixer_l16_224,5.853,94.147,18.200,81.800,208.20,224,0.875,bicubic,-81.307,-75.330,+92
-dla102,5.840,94.160,32.453,67.547,33.27,224,0.875,bilinear,-87.240,-66.087,-46
+tv_resnet152,6.000,94.000,31.640,68.360,60.19,224,0.875,bilinear,-87.330,-66.750,-55
+resnet26t,5.987,94.013,31.720,68.280,16.01,256,0.940,bicubic,-86.763,-66.520,-20
+tf_efficientnet_cc_b0_4e,5.960,94.040,29.533,70.467,13.31,224,0.875,bicubic,-86.660,-68.547,-11
+tf_efficientnetv2_b0,5.893,94.107,30.613,69.387,7.14,224,0.875,bicubic,-87.217,-67.777,-45
+mixer_l16_224,5.853,94.147,18.200,81.800,208.20,224,0.875,bicubic,-81.307,-75.330,+91
+dla102,5.840,94.160,32.453,67.547,33.27,224,0.875,bilinear,-87.240,-66.087,-45
 regnetx_040,5.800,94.200,31.187,68.813,22.12,224,0.875,bicubic,-87.750,-67.373,-84
-selecsls60,5.720,94.280,32.280,67.720,30.67,224,0.875,bicubic,-87.300,-66.030,-44
-hardcorenas_c,5.600,94.400,30.213,69.787,5.52,224,0.875,bilinear,-86.420,-67.627,+11
-regnety_016,5.573,94.427,30.280,69.720,11.20,224,0.875,bicubic,-87.457,-67.910,-47
-res2next50,5.520,94.480,30.600,69.400,24.67,224,0.875,bilinear,-87.330,-67.580,-40
-hrnet_w18,5.453,94.547,30.813,69.187,21.30,224,0.875,bilinear,-86.857,-67.437,-7
-tf_efficientnet_lite2,5.373,94.627,30.907,69.093,6.09,260,0.890,bicubic,-87.287,-67.323,-24
-botnet26t_256,5.333,94.667,24.307,75.693,12.49,256,0.950,bicubic,-82.127,-71.883,+80
-resnest14d,5.333,94.667,28.547,71.453,10.61,224,0.875,bilinear,-86.397,-69.323,+19
-tf_efficientnet_b0_ap,5.320,94.680,28.707,71.293,5.29,224,0.875,bicubic,-86.900,-69.403,-6
-gernet_s,5.200,94.800,30.067,69.933,8.17,224,0.875,bilinear,-86.940,-68.123,-3
-tf_efficientnet_em,5.200,94.800,30.653,69.347,6.90,240,0.882,bicubic,-87.750,-67.557,-50
-mobilenetv3_large_100,5.107,94.893,28.053,71.947,5.48,224,0.875,bicubic,-86.233,-69.657,+22
-repvgg_b1g4,5.107,94.893,30.467,69.533,39.97,224,0.875,bilinear,-87.893,-67.963,-55
-xcit_nano_12_p16_224_dist,5.107,94.893,26.280,73.720,3.05,224,1.000,bicubic,-84.573,-70.810,+57
-densenet121,5.080,94.920,29.627,70.373,7.98,224,0.875,bicubic,-86.490,-68.403,+14
-res2net50_26w_4s,5.053,94.947,28.987,71.013,25.70,224,0.875,bilinear,-87.427,-69.083,-25
-tf_efficientnet_b0,5.040,94.960,28.907,71.093,5.29,224,0.875,bicubic,-87.190,-69.093,-15
-tf_mixnet_m,5.040,94.960,28.093,71.907,5.01,224,0.875,bicubic,-87.290,-69.797,-21
-vit_tiny_r_s16_p8_224,4.947,95.053,26.707,73.293,6.34,224,0.900,bicubic,-84.243,-70.523,+57
-hardcorenas_a,4.893,95.107,27.987,72.013,5.26,224,0.875,bilinear,-86.447,-69.873,+13
-regnetx_032,4.880,95.120,29.893,70.107,15.30,224,0.875,bicubic,-88.240,-68.497,-71
-res2net50_14w_8s,4.880,95.120,28.320,71.680,25.06,224,0.875,bilinear,-87.840,-69.870,-45
-mixnet_s,4.840,95.160,28.507,71.493,4.13,224,0.875,bicubic,-86.980,-69.183,+1
-hardcorenas_b,4.827,95.173,27.800,72.200,5.18,224,0.875,bilinear,-86.913,-69.980,+2
-mobilenetv3_rw,4.813,95.187,29.507,70.493,5.48,224,0.875,bicubic,-86.397,-68.153,+12
-xcit_nano_12_p16_224,4.800,95.200,25.253,74.747,3.05,224,1.000,bicubic,-83.790,-71.537,+57
-gluon_resnet50_v1c,4.773,95.227,27.787,72.213,25.58,224,0.875,bicubic,-88.257,-70.573,-72
-selecsls42b,4.707,95.293,28.333,71.667,32.46,224,0.875,bicubic,-87.593,-69.807,-29
-tv_resnext50_32x4d,4.693,95.307,29.813,70.187,25.03,224,0.875,bilinear,-88.067,-68.467,-57
-resnext26ts,4.640,95.360,28.733,71.267,10.30,256,0.900,bicubic,-87.220,-68.497,-10
-densenet161,4.573,95.427,29.520,70.480,28.68,224,0.875,bicubic,-87.927,-68.770,-42
-tv_resnet101,4.573,95.427,28.867,71.133,44.55,224,0.875,bilinear,-88.237,-69.363,-63
-tf_efficientnet_lite1,4.467,95.533,28.360,71.640,5.42,240,0.882,bicubic,-88.153,-69.720,-48
-mobilenetv2_120d,4.440,95.560,29.067,70.933,5.83,224,0.875,bicubic,-87.960,-68.983,-39
-vit_base_patch32_sam_224,4.307,95.693,24.347,75.653,88.22,224,0.900,bicubic,-85.443,-72.653,+34
-efficientnet_es_pruned,4.120,95.880,26.547,73.453,5.44,224,0.875,bicubic,-87.070,-71.193,+2
-fbnetc_100,4.093,95.907,25.493,74.507,5.57,224,0.875,bilinear,-86.627,-71.717,+16
-gluon_resnet50_v1b,4.027,95.973,26.827,73.173,25.56,224,0.875,bicubic,-88.513,-71.363,-50
-densenet201,3.973,96.027,27.280,72.720,20.01,224,0.875,bicubic,-88.777,-70.960,-66
-dpn68,3.933,96.067,26.000,74.000,12.61,224,0.875,bicubic,-88.087,-72.040,-28
-resnet26d,3.920,96.080,28.240,71.760,16.01,224,0.875,bicubic,-88.130,-69.720,-32
-tf_mixnet_s,3.920,96.080,25.200,74.800,4.13,224,0.875,bicubic,-87.590,-72.410,-12
-semnasnet_100,3.880,96.120,26.840,73.160,3.89,224,0.875,bicubic,-87.400,-70.730,-8
-repvgg_a2,3.800,96.200,27.293,72.707,28.21,224,0.875,bilinear,-88.140,-70.857,-28
-tf_efficientnet_es,3.747,96.253,25.973,74.027,5.44,224,0.875,bicubic,-88.243,-71.897,-31
-regnety_008,3.707,96.293,26.853,73.147,6.26,224,0.875,bicubic,-88.003,-71.327,-18
-ssl_resnet18,3.693,96.307,25.280,74.720,11.69,224,0.875,bilinear,-86.537,-72.280,+16
-densenet169,3.680,96.320,25.520,74.480,14.15,224,0.875,bicubic,-88.230,-72.580,-31
-mobilenetv2_140,3.667,96.333,26.507,73.493,6.11,224,0.875,bicubic,-88.163,-71.353,-27
-tf_mobilenetv3_large_100,3.653,96.347,24.987,75.013,5.48,224,0.875,bilinear,-87.577,-72.673,-14
-dla60,3.587,96.413,27.920,72.080,22.04,224,0.875,bilinear,-88.633,-70.100,-47
-res2net50_48w_2s,3.573,96.427,26.333,73.667,25.29,224,0.875,bilinear,-88.977,-71.747,-65
-spnasnet_100,3.533,96.467,24.213,75.787,4.42,224,0.875,bilinear,-86.817,-72.977,+7
-regnety_006,3.507,96.493,24.893,75.107,6.06,224,0.875,bicubic,-87.873,-72.817,-22
-regnetx_016,3.467,96.533,26.373,73.627,9.19,224,0.875,bicubic,-88.693,-71.837,-49
-legacy_seresnet34,3.293,96.707,23.613,76.387,21.96,224,0.875,bilinear,-87.607,-73.967,-8
-efficientnet_lite0,3.280,96.720,25.720,74.280,4.65,224,0.875,bicubic,-87.860,-71.910,-17
-ghostnet_100,3.253,96.747,24.720,75.280,5.18,224,0.875,bilinear,-86.777,-72.650,+8
-dla34,3.173,96.827,23.587,76.413,15.74,224,0.875,bilinear,-87.597,-74.063,-8
-mobilenetv2_110d,3.107,96.893,24.387,75.613,4.52,224,0.875,bicubic,-87.863,-73.173,-13
-mnasnet_100,3.093,96.907,24.227,75.773,4.38,224,0.875,bicubic,-87.417,-73.243,-3
-regnety_004,3.067,96.933,22.587,77.413,4.34,224,0.875,bicubic,-87.413,-74.973,-3
-tf_efficientnet_lite0,3.067,96.933,22.827,77.173,4.65,224,0.875,bicubic,-87.983,-74.743,-19
-skresnet18,2.960,97.040,22.733,77.267,11.96,224,0.875,bicubic,-86.700,-74.487,+9
-resnet34,2.893,97.107,23.560,76.440,21.80,224,0.875,bilinear,-88.227,-74.070,-23
-tf_mobilenetv3_large_075,2.867,97.133,21.600,78.400,3.99,224,0.875,bilinear,-86.843,-75.620,+4
-vgg19_bn,2.867,97.133,23.547,76.453,143.68,224,0.875,bilinear,-87.233,-74.033,-3
-regnetx_008,2.733,97.267,22.333,77.667,7.26,224,0.875,bicubic,-88.317,-75.377,-25
-gluon_resnet34_v1b,2.653,97.347,21.533,78.467,21.80,224,0.875,bicubic,-88.337,-76.117,-24
-hrnet_w18_small_v2,2.627,97.373,23.587,76.413,15.60,224,0.875,bilinear,-88.563,-74.313,-31
-vgg16,2.560,97.440,19.960,80.040,138.36,224,0.875,bilinear,-85.990,-76.830,+13
-vgg16_bn,2.547,97.453,23.587,76.413,138.37,224,0.875,bilinear,-87.543,-73.783,-7
-repvgg_b0,2.533,97.467,23.920,76.080,15.82,224,0.875,bilinear,-88.917,-74.060,-42
-resnet18d,2.493,97.507,21.600,78.400,11.71,224,0.875,bicubic,-86.797,-75.540,+1
+selecsls60,5.720,94.280,32.280,67.720,30.67,224,0.875,bicubic,-87.300,-66.030,-43
+hardcorenas_c,5.600,94.400,30.213,69.787,5.52,224,0.875,bilinear,-86.420,-67.627,+12
+regnety_016,5.573,94.427,30.280,69.720,11.20,224,0.875,bicubic,-87.457,-68.080,-47
+res2next50,5.520,94.480,30.600,69.400,24.67,224,0.875,bilinear,-87.330,-67.580,-39
+hrnet_w18,5.453,94.547,30.813,69.187,21.30,224,0.875,bilinear,-86.857,-67.437,-6
+tf_efficientnet_lite2,5.373,94.627,30.907,69.093,6.09,260,0.890,bicubic,-87.287,-67.323,-23
+resnest14d,5.333,94.667,28.547,71.453,10.61,224,0.875,bilinear,-86.397,-69.323,+21
+tf_efficientnet_b0_ap,5.320,94.680,28.707,71.293,5.29,224,0.875,bicubic,-86.900,-69.313,-4
+tf_efficientnet_em,5.200,94.800,30.653,69.347,6.90,240,0.882,bicubic,-87.750,-67.557,-47
+gernet_s,5.200,94.800,30.067,69.933,8.17,224,0.875,bilinear,-86.940,-68.123,-2
+repvgg_b1g4,5.107,94.893,30.467,69.533,39.97,224,0.875,bilinear,-87.893,-67.963,-52
+mobilenetv3_large_100,5.107,94.893,28.053,71.947,5.48,224,0.875,bicubic,-86.233,-69.807,+22
+xcit_nano_12_p16_224_dist,5.107,94.893,26.280,73.720,3.05,224,1.000,bicubic,-84.573,-70.810,+58
+densenet121,5.080,94.920,29.627,70.373,7.98,224,0.875,bicubic,-86.490,-68.403,+16
+res2net50_26w_4s,5.053,94.947,28.987,71.013,25.70,224,0.875,bilinear,-87.427,-69.083,-23
+tf_mixnet_m,5.040,94.960,28.093,71.907,5.01,224,0.875,bicubic,-87.290,-69.797,-18
+tf_efficientnet_b0,5.040,94.960,28.907,71.093,5.29,224,0.875,bicubic,-87.190,-69.093,-14
+vit_tiny_r_s16_p8_224,4.947,95.053,26.707,73.293,6.34,224,0.900,bicubic,-84.243,-70.523,+58
+hardcorenas_a,4.893,95.107,27.987,72.013,5.26,224,0.875,bilinear,-86.447,-69.723,+16
+regnetx_032,4.880,95.120,29.893,70.107,15.30,224,0.875,bicubic,-88.240,-68.497,-70
+res2net50_14w_8s,4.880,95.120,28.320,71.680,25.06,224,0.875,bilinear,-87.840,-69.870,-43
+mixnet_s,4.840,95.160,28.507,71.493,4.13,224,0.875,bicubic,-86.980,-69.183,+3
+hardcorenas_b,4.827,95.173,27.800,72.200,5.18,224,0.875,bilinear,-86.913,-69.980,+4
+mobilenetv3_rw,4.813,95.187,29.507,70.493,5.48,224,0.875,bicubic,-86.397,-68.153,+14
+xcit_nano_12_p16_224,4.800,95.200,25.253,74.747,3.05,224,1.000,bicubic,-83.790,-71.537,+58
+gluon_resnet50_v1c,4.773,95.227,27.787,72.213,25.58,224,0.875,bicubic,-88.257,-70.583,-71
+selecsls42b,4.707,95.293,28.333,71.667,32.46,224,0.875,bicubic,-87.593,-69.807,-27
+tv_resnext50_32x4d,4.693,95.307,29.813,70.187,25.03,224,0.875,bilinear,-88.067,-68.467,-55
+resnext26ts,4.640,95.360,28.733,71.267,10.30,256,0.900,bicubic,-87.220,-69.197,-7
+densenet161,4.573,95.427,29.520,70.480,28.68,224,0.875,bicubic,-87.927,-68.770,-40
+tv_resnet101,4.573,95.427,28.867,71.133,44.55,224,0.875,bilinear,-88.237,-69.363,-61
+tf_efficientnet_lite1,4.467,95.533,28.360,71.640,5.42,240,0.882,bicubic,-88.153,-69.720,-46
+mobilenetv2_120d,4.440,95.560,29.067,70.933,5.83,224,0.875,bicubic,-87.960,-68.983,-37
+vit_base_patch32_sam_224,4.307,95.693,24.347,75.653,88.22,224,0.900,bicubic,-85.443,-72.653,+35
+efficientnet_es_pruned,4.120,95.880,26.547,73.453,5.44,224,0.875,bicubic,-87.070,-71.193,+4
+fbnetc_100,4.093,95.907,25.493,74.507,5.57,224,0.875,bilinear,-86.627,-71.717,+18
+gluon_resnet50_v1b,4.027,95.973,26.827,73.173,25.56,224,0.875,bicubic,-88.513,-71.363,-48
+densenet201,3.973,96.027,27.280,72.720,20.01,224,0.875,bicubic,-88.777,-70.960,-64
+dpn68,3.933,96.067,26.000,74.000,12.61,224,0.875,bicubic,-88.087,-72.040,-26
+tf_mixnet_s,3.920,96.080,25.200,74.800,4.13,224,0.875,bicubic,-87.590,-72.410,-9
+resnet26d,3.920,96.080,28.240,71.760,16.01,224,0.875,bicubic,-88.130,-69.720,-31
+semnasnet_100,3.880,96.120,26.840,73.160,3.89,224,0.875,bicubic,-87.400,-70.730,-6
+repvgg_a2,3.800,96.200,27.293,72.707,28.21,224,0.875,bilinear,-88.140,-70.857,-26
+tf_efficientnet_es,3.747,96.253,25.973,74.027,5.44,224,0.875,bicubic,-88.243,-71.897,-29
+regnety_008,3.707,96.293,26.853,73.147,6.26,224,0.875,bicubic,-88.003,-71.327,-16
+ssl_resnet18,3.693,96.307,25.280,74.720,11.69,224,0.875,bilinear,-86.537,-72.280,+17
+densenet169,3.680,96.320,25.520,74.480,14.15,224,0.875,bicubic,-88.230,-72.570,-29
+mobilenetv2_140,3.667,96.333,26.507,73.493,6.11,224,0.875,bicubic,-88.163,-71.353,-24
+tf_mobilenetv3_large_100,3.653,96.347,24.987,75.013,5.48,224,0.875,bilinear,-87.577,-72.673,-12
+dla60,3.587,96.413,27.920,72.080,22.04,224,0.875,bilinear,-88.633,-70.190,-45
+res2net50_48w_2s,3.573,96.427,26.333,73.667,25.29,224,0.875,bilinear,-88.977,-71.747,-63
+spnasnet_100,3.533,96.467,24.213,75.787,4.42,224,0.875,bilinear,-86.817,-72.977,+8
+regnety_006,3.507,96.493,24.893,75.107,6.06,224,0.875,bicubic,-87.873,-72.817,-20
+regnetx_016,3.467,96.533,26.373,73.627,9.19,224,0.875,bicubic,-88.693,-71.837,-47
+legacy_seresnet34,3.293,96.707,23.613,76.387,21.96,224,0.875,bilinear,-87.607,-73.967,-6
+efficientnet_lite0,3.280,96.720,25.720,74.280,4.65,224,0.875,bicubic,-87.860,-71.910,-15
+ghostnet_100,3.253,96.747,24.720,75.280,5.18,224,0.875,bilinear,-86.777,-72.650,+9
+dla34,3.173,96.827,23.587,76.413,15.74,224,0.875,bilinear,-87.597,-74.063,-6
+mobilenetv2_110d,3.107,96.893,24.387,75.613,4.52,224,0.875,bicubic,-87.863,-73.173,-11
+mnasnet_100,3.093,96.907,24.227,75.773,4.38,224,0.875,bicubic,-87.417,-73.243,-2
+regnety_004,3.067,96.933,22.587,77.413,4.34,224,0.875,bicubic,-87.413,-74.973,-2
+tf_efficientnet_lite0,3.067,96.933,22.827,77.173,4.65,224,0.875,bicubic,-87.983,-74.743,-17
+skresnet18,2.960,97.040,22.733,77.267,11.96,224,0.875,bicubic,-86.700,-74.487,+10
+resnet34,2.893,97.107,23.560,76.440,21.80,224,0.875,bilinear,-88.227,-74.070,-21
+tf_mobilenetv3_large_075,2.867,97.133,21.600,78.400,3.99,224,0.875,bilinear,-86.843,-75.620,+5
+vgg19_bn,2.867,97.133,23.547,76.453,143.68,224,0.875,bilinear,-87.233,-74.033,-2
+regnetx_008,2.733,97.267,22.333,77.667,7.26,224,0.875,bicubic,-88.317,-75.377,-23
+gluon_resnet34_v1b,2.653,97.347,21.533,78.467,21.80,224,0.875,bicubic,-88.337,-76.117,-21
+hrnet_w18_small_v2,2.627,97.373,23.587,76.413,15.60,224,0.875,bilinear,-88.563,-74.313,-29
+vgg16,2.560,97.440,19.960,80.040,138.36,224,0.875,bilinear,-85.990,-76.830,+14
+vgg16_bn,2.547,97.453,23.587,76.413,138.37,224,0.875,bilinear,-87.543,-73.783,-6
+repvgg_b0,2.533,97.467,23.920,76.080,15.82,224,0.875,bilinear,-88.917,-74.060,-40
+resnet18d,2.493,97.507,21.600,78.400,11.71,224,0.875,bicubic,-86.797,-75.540,+2
+tv_densenet121,2.453,97.547,22.533,77.467,7.98,224,0.875,bicubic,-88.447,-75.167,-24
 regnetx_006,2.453,97.547,20.600,79.400,6.20,224,0.875,bicubic,-87.867,-76.830,-14
-tv_densenet121,2.453,97.547,22.533,77.467,7.98,224,0.875,bicubic,-88.447,-75.167,-27
-legacy_seresnet18,2.440,97.560,19.827,80.173,11.78,224,0.875,bicubic,-86.440,-77.143,+3
-resnet26,2.387,97.613,22.733,77.267,16.00,224,0.875,bicubic,-88.743,-75.007,-37
-mobilenetv2_100,2.147,97.853,19.653,80.347,3.50,224,0.875,bicubic,-87.463,-77.497,-5
+legacy_seresnet18,2.440,97.560,19.827,80.173,11.78,224,0.875,bicubic,-86.440,-77.143,+4
+resnet26,2.387,97.613,22.733,77.267,16.00,224,0.875,bicubic,-88.743,-75.007,-35
+mobilenetv2_100,2.147,97.853,19.653,80.347,3.50,224,0.875,bicubic,-87.463,-77.497,-4
 regnety_002,2.080,97.920,18.600,81.400,3.16,224,0.875,bicubic,-85.280,-77.970,+9
-vgg13_bn,2.080,97.920,20.040,79.960,133.05,224,0.875,bilinear,-86.700,-76.930,+1
+vgg13_bn,2.080,97.920,20.040,79.960,133.05,224,0.875,bilinear,-86.700,-76.930,+2
 vgg19,2.027,97.973,20.480,79.520,143.67,224,0.875,bilinear,-87.033,-76.390,-4
 tf_mobilenetv3_small_100,2.000,98.000,15.880,84.120,2.54,224,0.875,bilinear,-83.210,-79.900,+12
 tf_mobilenetv3_small_075,1.973,98.027,14.840,85.160,2.04,224,0.875,bilinear,-81.507,-79.960,+14
-regnetx_004,1.960,98.040,19.067,80.933,5.16,224,0.875,bicubic,-86.920,-78.053,-4
+regnetx_004,1.960,98.040,19.067,80.933,5.16,224,0.875,bicubic,-86.920,-78.053,-3
+vgg13,1.840,98.160,17.880,82.120,133.05,224,0.875,bilinear,-85.190,-78.430,+5
 tv_resnet34,1.840,98.160,19.800,80.200,21.80,224,0.875,bilinear,-88.080,-77.540,-18
-vgg13,1.840,98.160,17.880,82.120,133.05,224,0.875,bilinear,-85.190,-78.430,+4
-vgg11_bn,1.720,98.280,18.000,82.000,132.87,224,0.875,bilinear,-85.800,-78.810,-2
+vgg11_bn,1.720,98.280,18.000,82.000,132.87,224,0.875,bilinear,-85.800,-78.810,-1
 dla46x_c,1.693,98.307,16.373,83.627,1.07,224,0.875,bilinear,-82.557,-78.907,+7
-tf_mobilenetv3_large_minimal_100,1.627,98.373,17.187,82.813,3.92,224,0.875,bilinear,-87.323,-79.683,-11
-dla60x_c,1.587,98.413,17.800,82.200,1.32,224,0.875,bilinear,-84.693,-78.360,+2
-vgg11,1.587,98.413,15.907,84.093,132.86,224,0.875,bilinear,-84.993,-80.383,0
-gluon_resnet18_v1b,1.547,98.453,16.600,83.400,11.69,224,0.875,bicubic,-86.833,-80.100,-8
-hrnet_w18_small,1.507,98.493,18.107,81.893,13.19,224,0.875,bilinear,-87.553,-78.993,-17
+tf_mobilenetv3_large_minimal_100,1.627,98.373,17.187,82.813,3.92,224,0.875,bilinear,-87.323,-79.683,-10
+vgg11,1.587,98.413,15.907,84.093,132.86,224,0.875,bilinear,-84.993,-80.383,+1
+dla60x_c,1.587,98.413,17.800,82.200,1.32,224,0.875,bilinear,-84.693,-78.360,+1
+gluon_resnet18_v1b,1.547,98.453,16.600,83.400,11.69,224,0.875,bicubic,-86.833,-80.100,-7
+hrnet_w18_small,1.507,98.493,18.107,81.893,13.19,224,0.875,bilinear,-87.553,-78.993,-15
 dla46_c,1.453,98.547,15.027,84.973,1.30,224,0.875,bilinear,-82.187,-79.883,+2
 regnetx_002,1.253,98.747,14.827,85.173,2.68,224,0.875,bicubic,-84.947,-81.143,-2
 resnet18,1.120,98.880,16.173,83.827,11.69,224,0.875,bilinear,-86.250,-80.087,-9
 tf_mobilenetv3_small_minimal_100,1.027,98.973,11.400,88.600,2.04,224,0.875,bilinear,-80.363,-82.270,+1
-tv_resnet50,0.027,99.973,14.320,85.680,25.56,224,0.875,bilinear,-91.863,-83.720,-80
+tv_resnet50,0.027,99.973,14.320,85.680,25.56,224,0.875,bilinear,-91.863,-83.720,-78

results/results-imagenet-r-clean.csv

@@ -1,7 +1,7 @@
 model,top1,top1_err,top5,top5_err,param_count,img_size,cropt_pct,interpolation
 beit_large_patch16_384,97.820,2.180,99.790,0.210,305.00,384,1.000,bicubic
-tf_efficientnet_l2_ns,97.770,2.230,99.890,0.110,480.31,800,0.960,bicubic
 beit_large_patch16_512,97.770,2.230,99.810,0.190,305.67,512,1.000,bicubic
+tf_efficientnet_l2_ns,97.770,2.230,99.890,0.110,480.31,800,0.960,bicubic
 tf_efficientnet_l2_ns_475,97.750,2.250,99.820,0.180,480.31,475,0.936,bicubic
 beit_large_patch16_224,97.470,2.530,99.690,0.310,304.43,224,0.900,bicubic
 vit_large_patch16_384,97.420,2.580,99.780,0.220,304.72,384,1.000,bicubic
@@ -35,8 +35,8 @@ vit_large_patch16_224,96.710,3.290,99.650,0.350,304.33,224,0.900,bicubic
 tf_efficientnet_b8,96.700,3.300,99.550,0.450,87.41,672,0.954,bicubic
 xcit_medium_24_p16_384_dist,96.690,3.310,99.600,0.400,84.40,384,1.000,bicubic
 swin_base_patch4_window7_224,96.670,3.330,99.670,0.330,87.77,224,0.900,bicubic
-tf_efficientnetv2_l,96.650,3.350,99.570,0.430,118.52,480,1.000,bicubic
 beit_base_patch16_224,96.650,3.350,99.660,0.340,86.53,224,0.900,bicubic
+tf_efficientnetv2_l,96.650,3.350,99.570,0.430,118.52,480,1.000,bicubic
 cait_s36_384,96.630,3.370,99.590,0.410,68.37,384,1.000,bicubic
 xcit_large_24_p8_224_dist,96.620,3.380,99.460,0.540,188.93,224,1.000,bicubic
 cait_s24_384,96.580,3.420,99.550,0.450,47.06,384,1.000,bicubic
@@ -49,9 +49,9 @@ xcit_medium_24_p8_224_dist,96.500,3.500,99.500,0.500,84.32,224,1.000,bicubic
 deit_base_distilled_patch16_384,96.490,3.510,99.590,0.410,87.63,384,1.000,bicubic
 xcit_small_12_p8_384_dist,96.480,3.520,99.480,0.520,26.21,384,1.000,bicubic
 vit_base_r50_s16_384,96.470,3.530,99.660,0.340,98.95,384,1.000,bicubic
+ecaresnet269d,96.460,3.540,99.610,0.390,102.09,352,1.000,bicubic
 tf_efficientnetv2_s_in21ft1k,96.460,3.540,99.570,0.430,21.46,384,1.000,bicubic
 eca_nfnet_l2,96.460,3.540,99.630,0.370,56.72,384,1.000,bicubic
-ecaresnet269d,96.460,3.540,99.610,0.390,102.09,352,1.000,bicubic
 dm_nfnet_f2,96.450,3.550,99.540,0.460,193.78,352,0.920,bicubic
 ig_resnext101_32x16d,96.430,3.570,99.540,0.460,194.03,224,0.875,bilinear
 resnetrs420,96.400,3.600,99.540,0.460,191.89,416,1.000,bicubic
@@ -64,10 +64,10 @@ seresnet152d,96.330,3.670,99.510,0.490,66.84,320,1.000,bicubic
 xcit_small_12_p16_384_dist,96.330,3.670,99.490,0.510,26.25,384,1.000,bicubic
 xcit_large_24_p16_224_dist,96.310,3.690,99.500,0.500,189.10,224,1.000,bicubic
 vit_base_patch16_224,96.300,3.700,99.560,0.440,86.57,224,0.900,bicubic
-resnetv2_101x3_bitm,96.290,3.710,99.580,0.420,387.93,448,1.000,bilinear
 resnetv2_50x3_bitm,96.290,3.710,99.630,0.370,217.32,448,1.000,bilinear
-swsl_resnext101_32x16d,96.280,3.720,99.500,0.500,194.03,224,0.875,bilinear
+resnetv2_101x3_bitm,96.290,3.710,99.580,0.420,387.93,448,1.000,bilinear
 tf_efficientnet_b6,96.280,3.720,99.520,0.480,43.04,528,0.942,bicubic
+swsl_resnext101_32x16d,96.280,3.720,99.500,0.500,194.03,224,0.875,bilinear
 efficientnetv2_rw_m,96.270,3.730,99.560,0.440,53.24,416,1.000,bicubic
 xcit_medium_24_p16_224_dist,96.260,3.740,99.400,0.600,84.40,224,1.000,bicubic
 xcit_tiny_24_p8_384_dist,96.250,3.750,99.440,0.560,12.11,384,1.000,bicubic
@@ -83,8 +83,8 @@ tf_efficientnet_b5_ap,96.080,3.920,99.540,0.460,30.39,456,0.934,bicubic
 resnest200e,96.080,3.920,99.470,0.530,70.20,320,0.909,bicubic
 pit_b_distilled_224,96.080,3.920,99.380,0.620,74.79,224,0.900,bicubic
 resnetrs270,96.070,3.930,99.480,0.520,129.86,352,1.000,bicubic
-vit_small_r26_s32_384,96.060,3.940,99.550,0.450,36.47,384,1.000,bicubic
 xcit_large_24_p8_224,96.060,3.940,99.150,0.850,188.93,224,1.000,bicubic
+vit_small_r26_s32_384,96.060,3.940,99.550,0.450,36.47,384,1.000,bicubic
 swsl_resnext101_32x4d,96.050,3.950,99.540,0.460,44.18,224,0.875,bilinear
 vit_base_patch16_224_miil,96.040,3.960,99.350,0.650,86.54,224,0.875,bilinear
 cait_xs24_384,96.010,3.990,99.430,0.570,26.67,384,1.000,bicubic
@@ -98,8 +98,8 @@ eca_nfnet_l1,95.920,4.080,99.500,0.500,41.41,320,1.000,bicubic
 xcit_small_24_p8_224,95.910,4.090,99.180,0.820,47.63,224,1.000,bicubic
 vit_base_patch32_384,95.910,4.090,99.440,0.560,88.30,384,1.000,bicubic
 regnety_160,95.900,4.100,99.560,0.440,83.59,288,1.000,bicubic
-resmlp_big_24_distilled_224,95.870,4.130,99.440,0.560,129.14,224,0.875,bicubic
 xcit_medium_24_p8_224,95.870,4.130,99.090,0.910,84.32,224,1.000,bicubic
+resmlp_big_24_distilled_224,95.870,4.130,99.440,0.560,129.14,224,0.875,bicubic
 regnetz_d,95.860,4.140,99.440,0.560,27.58,320,0.950,bicubic
 resnet152d,95.850,4.150,99.430,0.570,60.21,320,1.000,bicubic
 crossvit_15_dagger_408,95.820,4.180,99.300,0.700,28.50,408,1.000,bicubic
@@ -108,16 +108,16 @@ deit_base_distilled_patch16_224,95.780,4.220,99.280,0.720,87.34,224,0.900,bicubi
 resnet101d,95.750,4.250,99.440,0.560,44.57,320,1.000,bicubic
 xcit_small_12_p16_224_dist,95.750,4.250,99.290,0.710,26.25,224,1.000,bicubic
 resnetv2_152x2_bit_teacher,95.730,4.270,99.430,0.570,236.34,224,0.875,bicubic
-swin_small_patch4_window7_224,95.720,4.280,99.290,0.710,49.61,224,0.900,bicubic
 twins_pcpvt_large,95.720,4.280,99.490,0.510,60.99,224,0.900,bicubic
 twins_svt_large,95.720,4.280,99.370,0.630,99.27,224,0.900,bicubic
+swin_small_patch4_window7_224,95.720,4.280,99.290,0.710,49.61,224,0.900,bicubic
 tf_efficientnetv2_s,95.710,4.290,99.400,0.600,21.46,384,1.000,bicubic
 dm_nfnet_f0,95.710,4.290,99.330,0.670,71.49,256,0.900,bicubic
 efficientnetv2_rw_s,95.700,4.300,99.380,0.620,23.94,384,1.000,bicubic
 deit_base_patch16_384,95.660,4.340,99.240,0.760,86.86,384,1.000,bicubic
 cait_s24_224,95.640,4.360,99.390,0.610,46.92,224,1.000,bicubic
-swsl_resnext50_32x4d,95.590,4.410,99.440,0.560,25.03,224,0.875,bilinear
 tf_efficientnet_b4,95.590,4.410,99.320,0.680,19.34,380,0.922,bicubic
+swsl_resnext50_32x4d,95.590,4.410,99.440,0.560,25.03,224,0.875,bilinear
 resnest101e,95.580,4.420,99.270,0.730,48.28,256,0.875,bilinear
 twins_svt_base,95.570,4.430,99.230,0.770,56.07,224,0.900,bicubic
 efficientnet_b4,95.540,4.460,99.400,0.600,19.34,384,1.000,bicubic
@@ -167,11 +167,11 @@ xcit_small_24_p16_224,95.070,4.930,99.060,0.940,47.67,224,1.000,bicubic
 crossvit_base_240,95.060,4.940,98.980,1.020,105.03,240,0.875,bicubic
 crossvit_18_240,95.050,4.950,99.120,0.880,43.27,240,0.875,bicubic
 deit_base_patch16_224,95.020,4.980,98.970,1.030,86.57,224,0.900,bicubic
-crossvit_15_dagger_240,94.970,5.030,99.150,0.850,28.21,240,0.875,bicubic
 visformer_small,94.970,5.030,99.210,0.790,40.22,224,0.900,bicubic
+crossvit_15_dagger_240,94.970,5.030,99.150,0.850,28.21,240,0.875,bicubic
 tf_efficientnet_b3_ap,94.960,5.040,99.110,0.890,12.23,300,0.904,bicubic
-convmixer_1536_20,94.950,5.050,99.170,0.830,51.63,224,0.960,bicubic
 xcit_large_24_p16_224,94.950,5.050,98.830,1.170,189.10,224,1.000,bicubic
+convmixer_1536_20,94.950,5.050,99.170,0.830,51.63,224,0.960,bicubic
 cait_xxs24_384,94.940,5.060,99.130,0.870,12.03,384,1.000,bicubic
 jx_nest_tiny,94.940,5.060,99.100,0.900,17.06,224,0.875,bicubic
 resnetv2_101,94.930,5.070,99.110,0.890,44.54,224,0.950,bicubic
@@ -182,8 +182,8 @@ vit_small_patch16_224,94.900,5.100,99.280,0.720,22.05,224,0.900,bicubic
 tresnet_l,94.900,5.100,99.030,0.970,55.99,224,0.875,bilinear
 mixer_b16_224_miil,94.890,5.110,99.080,0.920,59.88,224,0.875,bilinear
 tf_efficientnet_b1_ns,94.880,5.120,99.250,0.750,7.79,240,0.882,bicubic
-tf_efficientnet_lite4,94.870,5.130,99.090,0.910,13.01,380,0.920,bilinear
 xcit_tiny_24_p8_224,94.870,5.130,99.190,0.810,12.11,224,1.000,bicubic
+tf_efficientnet_lite4,94.870,5.130,99.090,0.910,13.01,380,0.920,bilinear
 xcit_small_12_p16_224,94.810,5.190,99.060,0.940,26.25,224,1.000,bicubic
 seresnext50_32x4d,94.800,5.200,99.130,0.870,27.56,224,0.875,bicubic
 pit_b_224,94.790,5.210,98.810,1.190,73.76,224,0.900,bicubic
@@ -194,8 +194,8 @@ pit_s_distilled_224,94.750,5.250,99.180,0.820,24.04,224,0.900,bicubic
 xcit_tiny_12_p8_224_dist,94.740,5.260,99.180,0.820,6.71,224,1.000,bicubic
 legacy_senet154,94.730,5.270,99.100,0.900,115.09,224,0.875,bilinear
 resnest50d_4s2x40d,94.710,5.290,99.130,0.870,30.42,224,0.875,bicubic
-gluon_senet154,94.700,5.300,98.970,1.030,115.09,224,0.875,bicubic
 ssl_resnext50_32x4d,94.700,5.300,99.240,0.760,25.03,224,0.875,bilinear
+gluon_senet154,94.700,5.300,98.970,1.030,115.09,224,0.875,bicubic
 gluon_resnet152_v1s,94.690,5.310,99.050,0.950,60.32,224,0.875,bicubic
 regnetz_b,94.690,5.310,99.160,0.840,9.72,288,0.940,bicubic
 crossvit_15_240,94.680,5.320,99.070,0.930,27.53,240,0.875,bicubic
@@ -204,29 +204,32 @@ rexnet_200,94.670,5.330,99.090,0.910,16.37,224,0.875,bicubic
 tresnet_m_448,94.670,5.330,99.170,0.830,31.39,448,0.875,bilinear
 gluon_seresnext101_64x4d,94.660,5.340,98.970,1.030,88.23,224,0.875,bicubic
 wide_resnet50_2,94.650,5.350,99.050,0.950,68.88,224,0.875,bicubic
-halonet50ts,94.640,5.360,98.900,1.100,22.73,256,0.940,bicubic
 swin_tiny_patch4_window7_224,94.640,5.360,99.120,0.880,28.29,224,0.900,bicubic
 resnest50d,94.620,5.380,99.030,0.970,27.48,224,0.875,bilinear
 gcresnet50t,94.610,5.390,98.990,1.010,25.90,256,0.900,bicubic
+lamhalobotnet50ts_256,94.610,5.390,98.610,1.390,22.57,256,0.950,bicubic
 twins_pcpvt_small,94.600,5.400,99.140,0.860,24.11,224,0.900,bicubic
+deit_small_distilled_patch16_224,94.590,5.410,99.090,0.910,22.44,224,0.900,bicubic
 pit_s_224,94.590,5.410,98.930,1.070,23.46,224,0.900,bicubic
 crossvit_small_240,94.590,5.410,99.120,0.880,26.86,240,0.875,bicubic
-deit_small_distilled_patch16_224,94.590,5.410,99.090,0.910,22.44,224,0.900,bicubic
 efficientnet_b3_pruned,94.580,5.420,99.070,0.930,9.86,300,0.904,bicubic
 tnt_s_patch16_224,94.570,5.430,99.180,0.820,23.76,224,0.900,bicubic
 vit_small_patch32_384,94.570,5.430,99.140,0.860,22.92,384,1.000,bicubic
+lambda_resnet50ts,94.560,5.440,98.650,1.350,21.54,256,0.950,bicubic
 repvgg_b3,94.560,5.440,98.910,1.090,123.09,224,0.875,bilinear
 gernet_m,94.550,5.450,98.920,1.080,21.14,224,0.875,bilinear
+halo2botnet50ts_256,94.550,5.450,98.760,1.240,22.64,256,0.950,bicubic
 resmlp_36_distilled_224,94.550,5.450,99.160,0.840,44.69,224,0.875,bicubic
 xcit_tiny_12_p16_384_dist,94.540,5.460,99.170,0.830,6.72,384,1.000,bicubic
 sehalonet33ts,94.530,5.470,98.780,1.220,13.69,256,0.940,bicubic
-haloregnetz_b,94.500,5.500,98.960,1.040,11.68,224,0.940,bicubic
 regnety_320,94.500,5.500,99.170,0.830,145.05,224,0.875,bicubic
+haloregnetz_b,94.500,5.500,98.960,1.040,11.68,224,0.940,bicubic
 repvgg_b3g4,94.490,5.510,99.020,0.980,83.83,224,0.875,bilinear
 gluon_resnet152_v1d,94.460,5.540,99.000,1.000,60.21,224,0.875,bicubic
 ecaresnet101d_pruned,94.440,5.560,99.100,0.900,24.88,224,0.875,bicubic
 gluon_seresnext101_32x4d,94.430,5.570,99.090,0.910,48.96,224,0.875,bicubic
 convmixer_768_32,94.430,5.570,99.110,0.890,21.11,224,0.960,bicubic
+halonet50ts,94.420,5.580,98.760,1.240,22.73,256,0.940,bicubic
 gcresnext50ts,94.410,5.590,98.990,1.010,15.67,256,0.900,bicubic
 levit_256,94.410,5.590,99.060,0.940,18.89,224,0.900,bicubic
 nf_resnet50,94.380,5.620,99.070,0.930,25.56,288,0.940,bicubic
@@ -240,67 +243,67 @@ resmlp_24_distilled_224,94.340,5.660,99.090,0.910,30.02,224,0.875,bicubic
 gluon_resnext101_64x4d,94.330,5.670,98.880,1.120,83.46,224,0.875,bicubic
 inception_resnet_v2,94.320,5.680,98.800,1.200,55.84,299,0.897,bicubic
 ssl_resnet50,94.320,5.680,99.160,0.840,25.56,224,0.875,bilinear
-regnetx_120,94.290,5.710,99.200,0.800,46.11,224,0.875,bicubic
 resnetv2_50,94.290,5.710,98.930,1.070,25.55,224,0.950,bicubic
+regnetx_120,94.290,5.710,99.200,0.800,46.11,224,0.875,bicubic
 tf_efficientnet_b2_ap,94.280,5.720,98.950,1.050,9.11,260,0.890,bicubic
-resmlp_big_24_224,94.270,5.730,98.820,1.180,129.14,224,0.875,bicubic
 rexnet_150,94.270,5.730,99.090,0.910,9.73,224,0.875,bicubic
+resmlp_big_24_224,94.270,5.730,98.820,1.180,129.14,224,0.875,bicubic
 seresnet33ts,94.260,5.740,98.780,1.220,19.78,256,0.900,bicubic
 mixnet_xl,94.220,5.780,98.810,1.190,11.90,224,0.875,bicubic
 xcit_tiny_24_p16_224_dist,94.220,5.780,98.960,1.040,12.12,224,1.000,bicubic
 ecaresnet50d,94.210,5.790,99.010,0.990,25.58,224,0.875,bicubic
 regnetx_320,94.210,5.790,99.050,0.950,107.81,224,0.875,bicubic
 tf_efficientnet_b2,94.200,5.800,99.030,0.970,9.11,260,0.890,bicubic
-dpn92,94.180,5.820,98.930,1.070,37.67,224,0.875,bicubic
-gluon_resnet101_v1d,94.180,5.820,98.950,1.050,44.57,224,0.875,bicubic
 gluon_resnet101_v1s,94.180,5.820,99.020,0.980,44.67,224,0.875,bicubic
+gluon_resnet101_v1d,94.180,5.820,98.950,1.050,44.57,224,0.875,bicubic
+dpn92,94.180,5.820,98.930,1.070,37.67,224,0.875,bicubic
 gluon_seresnext50_32x4d,94.180,5.820,98.910,1.090,27.56,224,0.875,bicubic
 legacy_seresnext101_32x4d,94.170,5.830,98.970,1.030,48.96,224,0.875,bilinear
-ens_adv_inception_resnet_v2,94.140,5.860,98.790,1.210,55.84,299,0.897,bicubic
 regnety_064,94.140,5.860,99.030,0.970,30.58,224,0.875,bicubic
 ecaresnetlight,94.140,5.860,98.950,1.050,30.16,224,0.875,bicubic
+ens_adv_inception_resnet_v2,94.140,5.860,98.790,1.210,55.84,299,0.897,bicubic
 gluon_resnext101_32x4d,94.120,5.880,98.940,1.060,44.18,224,0.875,bicubic
 tf_efficientnet_lite3,94.110,5.890,98.960,1.040,8.20,300,0.904,bilinear
 cspdarknet53,94.100,5.900,98.980,1.020,27.64,256,0.887,bilinear
 seresnet50,94.080,5.920,98.950,1.050,28.09,224,0.875,bicubic
 resnet50d,94.070,5.930,98.920,1.080,25.58,224,0.875,bicubic
-efficientnet_el_pruned,94.060,5.940,99.020,0.980,10.59,300,0.904,bicubic
 regnety_120,94.060,5.940,99.020,0.980,51.82,224,0.875,bicubic
 tf_efficientnetv2_b2,94.060,5.940,98.940,1.060,10.10,260,0.890,bicubic
+efficientnet_el_pruned,94.060,5.940,99.020,0.980,10.59,300,0.904,bicubic
 gluon_xception65,94.040,5.960,99.030,0.970,39.92,299,0.903,bicubic
-hrnet_w48,94.030,5.970,99.030,0.970,77.47,224,0.875,bilinear
 resnetrs50,94.030,5.970,98.830,1.170,35.69,224,0.910,bicubic
+hrnet_w48,94.030,5.970,99.030,0.970,77.47,224,0.875,bilinear
 gluon_resnet152_v1b,94.020,5.980,98.750,1.250,60.19,224,0.875,bicubic
 dla102x2,94.010,5.990,99.030,0.970,41.28,224,0.875,bilinear
 deit_small_patch16_224,93.990,6.010,98.960,1.040,22.05,224,0.900,bicubic
 dpn107,93.960,6.040,98.840,1.160,86.92,224,0.875,bicubic
-skresnext50_32x4d,93.950,6.050,98.830,1.170,27.48,224,0.875,bicubic
 resnet50,93.950,6.050,98.470,1.530,25.56,224,0.950,bicubic
+skresnext50_32x4d,93.950,6.050,98.830,1.170,27.48,224,0.875,bicubic
 cait_xxs36_224,93.940,6.060,98.880,1.120,17.30,224,1.000,bicubic
-dpn98,93.930,6.070,98.920,1.080,61.57,224,0.875,bicubic
 ecaresnet26t,93.930,6.070,98.930,1.070,16.01,320,0.950,bicubic
-regnetx_160,93.900,6.100,99.080,0.920,54.28,224,0.875,bicubic
-regnety_080,93.900,6.100,98.990,1.010,39.18,224,0.875,bicubic
+dpn98,93.930,6.070,98.920,1.080,61.57,224,0.875,bicubic
 xception71,93.900,6.100,98.950,1.050,42.34,299,0.903,bicubic
-nf_regnet_b1,93.890,6.110,98.750,1.250,10.22,288,0.900,bicubic
+regnety_080,93.900,6.100,98.990,1.010,39.18,224,0.875,bicubic
+regnetx_160,93.900,6.100,99.080,0.920,54.28,224,0.875,bicubic
 vit_base_patch16_sam_224,93.890,6.110,98.890,1.110,86.57,224,0.900,bicubic
+nf_regnet_b1,93.890,6.110,98.750,1.250,10.22,288,0.900,bicubic
 gluon_resnet152_v1c,93.880,6.120,98.800,1.200,60.21,224,0.875,bicubic
 eca_resnet33ts,93.870,6.130,98.890,1.110,19.68,256,0.900,bicubic
-hrnet_w64,93.850,6.150,98.930,1.070,128.06,224,0.875,bilinear
-xcit_tiny_24_p16_224,93.850,6.150,98.770,1.230,12.12,224,1.000,bicubic
 resnext50_32x4d,93.850,6.150,98.820,1.180,25.03,224,0.875,bicubic
-ese_vovnet39b,93.850,6.150,98.900,1.100,24.57,224,0.875,bicubic
 cspresnet50,93.850,6.150,98.870,1.130,21.62,256,0.887,bilinear
-ecaresnet50d_pruned,93.820,6.180,99.000,1.000,19.94,224,0.875,bicubic
+xcit_tiny_24_p16_224,93.850,6.150,98.770,1.230,12.12,224,1.000,bicubic
+hrnet_w64,93.850,6.150,98.930,1.070,128.06,224,0.875,bilinear
+ese_vovnet39b,93.850,6.150,98.900,1.100,24.57,224,0.875,bicubic
 gcresnet33ts,93.820,6.180,98.930,1.070,19.88,256,0.900,bicubic
+ecaresnet50d_pruned,93.820,6.180,99.000,1.000,19.94,224,0.875,bicubic
 repvgg_b2g4,93.820,6.180,98.920,1.080,61.76,224,0.875,bilinear
-efficientnet_b2_pruned,93.800,6.200,98.910,1.090,8.31,260,0.890,bicubic
 resnext50d_32x4d,93.800,6.200,98.730,1.270,25.05,224,0.875,bicubic
+efficientnet_b2_pruned,93.800,6.200,98.910,1.090,8.31,260,0.890,bicubic
 regnetx_080,93.790,6.210,98.900,1.100,39.57,224,0.875,bicubic
 dla169,93.780,6.220,98.830,1.170,53.39,224,0.875,bilinear
-cspresnext50,93.770,6.230,98.840,1.160,20.57,224,0.875,bilinear
-gluon_resnet101_v1b,93.770,6.230,98.720,1.280,44.55,224,0.875,bicubic
 resnext101_32x8d,93.770,6.230,98.950,1.050,88.79,224,0.875,bilinear
+gluon_resnet101_v1b,93.770,6.230,98.720,1.280,44.55,224,0.875,bicubic
+cspresnext50,93.770,6.230,98.840,1.160,20.57,224,0.875,bilinear
 dpn131,93.760,6.240,98.850,1.150,79.25,224,0.875,bicubic
 tf_efficientnet_b0_ns,93.760,6.240,98.980,1.020,5.29,224,0.875,bicubic
 efficientnet_em,93.750,6.250,98.920,1.080,6.90,240,0.882,bicubic
@@ -312,20 +315,20 @@ resnetblur50,93.710,6.290,98.800,1.200,25.56,224,0.875,bicubic
 tf_efficientnet_b1,93.710,6.290,98.800,1.200,7.79,240,0.882,bicubic
 tf_efficientnetv2_b1,93.700,6.300,98.810,1.190,8.14,240,0.882,bicubic
 rexnet_130,93.690,6.310,98.720,1.280,7.56,224,0.875,bicubic
-gluon_resnext50_32x4d,93.670,6.330,98.700,1.300,25.03,224,0.875,bicubic
 regnetx_040,93.670,6.330,98.950,1.050,22.12,224,0.875,bicubic
 resmlp_36_224,93.670,6.330,98.950,1.050,44.69,224,0.875,bicubic
+gluon_resnext50_32x4d,93.670,6.330,98.700,1.300,25.03,224,0.875,bicubic
 gluon_resnet101_v1c,93.660,6.340,98.760,1.240,44.57,224,0.875,bicubic
-regnetx_064,93.650,6.350,99.050,0.950,26.21,224,0.875,bicubic
 xception,93.650,6.350,98.770,1.230,22.86,299,0.897,bicubic
+regnetx_064,93.650,6.350,99.050,0.950,26.21,224,0.875,bicubic
 tf_efficientnet_b1_ap,93.640,6.360,98.780,1.220,7.79,240,0.882,bicubic
 hrnet_w44,93.620,6.380,98.950,1.050,67.06,224,0.875,bilinear
 resnet33ts,93.620,6.380,98.770,1.230,19.68,256,0.900,bicubic
-regnety_040,93.610,6.390,98.960,1.040,20.65,224,0.875,bicubic
 halonet26t,93.610,6.390,98.640,1.360,12.48,256,0.950,bicubic
+regnety_040,93.610,6.390,98.960,1.040,20.65,224,0.875,bicubic
 dpn68b,93.600,6.400,98.710,1.290,12.61,224,0.875,bicubic
-gluon_inception_v3,93.590,6.410,98.840,1.160,23.83,299,0.875,bicubic
 gluon_resnet50_v1s,93.590,6.410,98.830,1.170,25.68,224,0.875,bicubic
+gluon_inception_v3,93.590,6.410,98.840,1.160,23.83,299,0.875,bicubic
 res2net50_26w_6s,93.580,6.420,98.740,1.260,37.05,224,0.875,bilinear
 tf_efficientnet_cc_b1_8e,93.580,6.420,98.690,1.310,39.72,240,0.882,bicubic
 repvgg_b2,93.570,6.430,99.070,0.930,89.02,224,0.875,bilinear
@@ -338,10 +341,11 @@ gmlp_s16_224,93.510,6.490,98.780,1.220,19.42,224,0.875,bicubic
 coat_tiny,93.500,6.500,98.680,1.320,5.50,224,0.900,bicubic
 cait_xxs24_224,93.490,6.510,98.770,1.230,11.96,224,1.000,bicubic
 coat_lite_mini,93.490,6.510,98.780,1.220,11.01,224,0.900,bicubic
-xception41,93.480,6.520,98.760,1.240,26.97,299,0.903,bicubic
 selecsls60b,93.480,6.520,98.840,1.160,32.77,224,0.875,bicubic
+xception41,93.480,6.520,98.760,1.240,26.97,299,0.903,bicubic
 legacy_seresnet152,93.460,6.540,98.850,1.150,66.82,224,0.875,bilinear
 lambda_resnet26rpt_256,93.440,6.560,98.880,1.120,10.99,256,0.940,bicubic
+botnet26t_256,93.440,6.560,98.660,1.340,12.49,256,0.950,bicubic
 res2net50_26w_8s,93.430,6.570,98.670,1.330,48.40,224,0.875,bilinear
 resmlp_24_224,93.430,6.570,98.810,1.190,30.02,224,0.875,bicubic
 vit_tiny_patch16_384,93.430,6.570,98.840,1.160,5.79,384,1.000,bicubic
@@ -350,6 +354,7 @@ legacy_seresnext50_32x4d,93.410,6.590,98.800,1.200,27.56,224,0.875,bilinear
 repvgg_b1,93.410,6.590,98.780,1.220,57.42,224,0.875,bilinear
 lambda_resnet26t,93.400,6.600,98.760,1.240,10.96,256,0.940,bicubic
 dla60_res2net,93.380,6.620,98.830,1.170,20.85,224,0.875,bilinear
+eca_botnext26ts_256,93.360,6.640,98.690,1.310,10.59,256,0.950,bicubic
 xcit_tiny_12_p16_224_dist,93.340,6.660,98.750,1.250,6.72,224,1.000,bicubic
 dla102,93.290,6.710,98.780,1.220,33.27,224,0.875,bilinear
 legacy_seresnet101,93.290,6.710,98.750,1.250,49.33,224,0.875,bilinear
@@ -359,8 +364,8 @@ resnest26d,93.260,6.740,98.840,1.160,17.07,224,0.875,bilinear
 tv_resnet152,93.260,6.740,98.750,1.250,60.19,224,0.875,bilinear
 xcit_nano_12_p8_384_dist,93.250,6.750,98.850,1.150,3.05,384,1.000,bicubic
 pit_xs_distilled_224,93.230,6.770,98.820,1.180,11.00,224,0.900,bicubic
-dla60x,93.210,6.790,98.720,1.280,17.35,224,0.875,bilinear
 tf_inception_v3,93.210,6.790,98.490,1.510,23.83,299,0.875,bicubic
+dla60x,93.210,6.790,98.720,1.280,17.35,224,0.875,bilinear
 tf_efficientnet_em,93.200,6.800,98.680,1.320,6.90,240,0.882,bicubic
 res2net50_26w_4s,93.180,6.820,98.670,1.330,25.70,224,0.875,bilinear
 eca_halonext26ts,93.140,6.860,98.690,1.310,10.76,256,0.940,bicubic
@@ -371,21 +376,21 @@ tf_mixnet_l,93.050,6.950,98.540,1.460,7.33,224,0.875,bicubic
 levit_128,93.040,6.960,98.690,1.310,9.21,224,0.900,bicubic
 repvgg_b1g4,93.040,6.960,98.820,1.180,39.97,224,0.875,bilinear
 regnety_016,93.030,6.970,98.690,1.310,11.20,224,0.875,bicubic
-res2net50_14w_8s,93.020,6.980,98.700,1.300,25.06,224,0.875,bilinear
 efficientnet_b1,93.020,6.980,98.710,1.290,7.79,256,1.000,bicubic
+res2net50_14w_8s,93.020,6.980,98.700,1.300,25.06,224,0.875,bilinear
 selecsls60,93.000,7.000,98.830,1.170,30.67,224,0.875,bicubic
 adv_inception_v3,92.990,7.010,98.480,1.520,23.83,299,0.875,bicubic
 hardcorenas_f,92.980,7.020,98.620,1.380,8.20,224,0.875,bilinear
-efficientnet_b1_pruned,92.960,7.040,98.520,1.480,6.33,240,0.882,bicubic
 hardcorenas_e,92.960,7.040,98.570,1.430,8.07,224,0.875,bilinear
+efficientnet_b1_pruned,92.960,7.040,98.520,1.480,6.33,240,0.882,bicubic
 hrnet_w32,92.950,7.050,98.840,1.160,41.23,224,0.875,bilinear
 efficientnet_es,92.940,7.060,98.690,1.310,5.44,224,0.875,bicubic
 gluon_resnet50_v1c,92.920,7.080,98.710,1.290,25.58,224,0.875,bicubic
 tv_resnext50_32x4d,92.910,7.090,98.730,1.270,25.03,224,0.875,bilinear
-inception_v3,92.900,7.100,98.320,1.680,23.83,299,0.875,bicubic
 pit_xs_224,92.900,7.100,98.790,1.210,10.62,224,0.900,bicubic
-densenet161,92.880,7.120,98.810,1.190,28.68,224,0.875,bicubic
+inception_v3,92.900,7.100,98.320,1.680,23.83,299,0.875,bicubic
 tv_resnet101,92.880,7.120,98.660,1.340,44.55,224,0.875,bilinear
+densenet161,92.880,7.120,98.810,1.190,28.68,224,0.875,bicubic
 resmlp_12_distilled_224,92.870,7.130,98.630,1.370,15.35,224,0.875,bicubic
 tf_efficientnet_cc_b0_8e,92.850,7.150,98.460,1.540,24.01,224,0.875,bicubic
 rexnet_100,92.840,7.160,98.620,1.380,4.80,224,0.875,bicubic
@@ -394,10 +399,10 @@ coat_lite_tiny,92.830,7.170,98.640,1.360,5.72,224,0.900,bicubic
 res2net50_48w_2s,92.800,7.200,98.470,1.530,25.29,224,0.875,bilinear
 seresnext26ts,92.790,7.210,98.600,1.400,10.39,256,0.900,bicubic
 seresnext26t_32x4d,92.770,7.230,98.550,1.450,16.81,224,0.875,bicubic
-crossvit_9_dagger_240,92.750,7.250,98.510,1.490,8.78,240,0.875,bicubic
 hrnet_w18,92.750,7.250,98.650,1.350,21.30,224,0.875,bilinear
-densenet201,92.690,7.310,98.660,1.340,20.01,224,0.875,bicubic
+crossvit_9_dagger_240,92.750,7.250,98.510,1.490,8.78,240,0.875,bicubic
 dla60,92.690,7.310,98.630,1.370,22.04,224,0.875,bilinear
+densenet201,92.690,7.310,98.660,1.340,20.01,224,0.875,bicubic
 resnet26t,92.680,7.320,98.600,1.400,16.01,256,0.940,bicubic
 gmixer_24_224,92.670,7.330,98.260,1.740,24.72,224,0.875,bicubic
 legacy_seresnet50,92.670,7.330,98.660,1.340,28.09,224,0.875,bilinear
@@ -412,8 +417,8 @@ regnetx_016,92.560,7.440,98.550,1.450,9.19,224,0.875,bicubic
 skresnet34,92.560,7.440,98.510,1.490,22.28,224,0.875,bicubic
 gluon_resnet50_v1b,92.550,7.450,98.550,1.450,25.56,224,0.875,bicubic
 selecsls42b,92.480,7.520,98.440,1.560,32.46,224,0.875,bicubic
-efficientnet_b0,92.470,7.530,98.680,1.320,5.29,224,0.875,bicubic
 gcresnext26ts,92.470,7.530,98.500,1.500,10.48,256,0.900,bicubic
+efficientnet_b0,92.470,7.530,98.680,1.320,5.29,224,0.875,bicubic
 xcit_tiny_12_p16_224,92.460,7.540,98.630,1.370,6.72,224,1.000,bicubic
 gernet_s,92.440,7.560,98.490,1.510,8.17,224,0.875,bilinear
 seresnext26d_32x4d,92.430,7.570,98.540,1.460,16.81,224,0.875,bicubic
@@ -425,17 +430,17 @@ convmixer_1024_20_ks9_p14,92.350,7.650,98.420,1.580,24.38,224,0.960,bicubic
 hardcorenas_c,92.330,7.670,98.340,1.660,5.52,224,0.875,bilinear
 tf_efficientnet_lite1,92.320,7.680,98.490,1.510,5.42,240,0.882,bicubic
 densenet169,92.290,7.710,98.590,1.410,14.15,224,0.875,bicubic
-dpn68,92.260,7.740,98.600,1.400,12.61,224,0.875,bicubic
 mixnet_m,92.260,7.740,98.370,1.630,5.01,224,0.875,bicubic
-mobilenetv3_large_100_miil,92.250,7.750,98.250,1.750,5.48,224,0.875,bilinear
+dpn68,92.260,7.740,98.600,1.400,12.61,224,0.875,bicubic
 resnet26d,92.250,7.750,98.470,1.530,16.01,224,0.875,bicubic
+mobilenetv3_large_100_miil,92.250,7.750,98.250,1.750,5.48,224,0.875,bilinear
 resnext26ts,92.210,7.790,98.280,1.720,10.30,256,0.900,bicubic
 tf_mixnet_m,92.170,7.830,98.420,1.580,5.01,224,0.875,bicubic
 vit_small_patch32_224,92.150,7.850,98.510,1.490,22.88,224,0.900,bicubic
 resmlp_12_224,92.130,7.870,98.570,1.430,15.35,224,0.875,bicubic
 tv_resnet50,92.110,7.890,98.420,1.580,25.56,224,0.875,bilinear
-tf_efficientnet_es,92.100,7.900,98.430,1.570,5.44,224,0.875,bicubic
 xcit_nano_12_p16_384_dist,92.100,7.900,98.520,1.480,3.05,384,1.000,bicubic
+tf_efficientnet_es,92.100,7.900,98.430,1.570,5.44,224,0.875,bicubic
 mobilenetv2_140,92.030,7.970,98.250,1.750,6.11,224,0.875,bicubic
 ese_vovnet19b_dw,92.020,7.980,98.520,1.480,6.54,224,0.875,bicubic
 hardcorenas_b,91.970,8.030,98.400,1.600,5.18,224,0.875,bilinear
@@ -452,8 +457,8 @@ hardcorenas_a,91.610,8.390,98.170,1.830,5.26,224,0.875,bilinear
 regnety_006,91.580,8.420,98.430,1.570,6.06,224,0.875,bicubic
 mobilenetv3_rw,91.550,8.450,98.270,1.730,5.48,224,0.875,bicubic
 levit_128s,91.500,8.500,98.400,1.600,7.78,224,0.900,bicubic
-mobilenetv3_large_100,91.480,8.520,98.330,1.670,5.48,224,0.875,bicubic
 legacy_seresnet34,91.480,8.520,98.200,1.800,21.96,224,0.875,bilinear
+mobilenetv3_large_100,91.480,8.520,98.330,1.670,5.48,224,0.875,bicubic
 resnet26,91.460,8.540,98.270,1.730,16.00,224,0.875,bicubic
 tf_mobilenetv3_large_100,91.410,8.590,98.250,1.750,5.48,224,0.875,bilinear
 tv_densenet121,91.400,8.600,98.250,1.750,7.98,224,0.875,bicubic
@@ -463,19 +468,18 @@ fbnetc_100,91.260,8.740,97.820,2.180,5.57,224,0.875,bilinear
 dla34,91.250,8.750,98.180,1.820,15.74,224,0.875,bilinear
 efficientnet_lite0,91.250,8.750,98.250,1.750,4.65,224,0.875,bicubic
 mnasnet_100,91.200,8.800,98.040,1.960,4.38,224,0.875,bicubic
-regnetx_008,91.190,8.810,98.370,1.630,7.26,224,0.875,bicubic
 resnet34,91.190,8.810,98.230,1.770,21.80,224,0.875,bilinear
+regnetx_008,91.190,8.810,98.370,1.630,7.26,224,0.875,bicubic
 hrnet_w18_small_v2,91.170,8.830,98.350,1.650,15.60,224,0.875,bilinear
 resnest14d,91.150,8.850,98.350,1.650,10.61,224,0.875,bilinear
 mixer_b16_224,91.130,8.870,97.410,2.590,59.88,224,0.875,bicubic
 xcit_nano_12_p8_224,91.100,8.900,98.240,1.760,3.05,224,1.000,bicubic
 swsl_resnet18,91.090,8.910,98.210,1.790,11.69,224,0.875,bilinear
-deit_tiny_distilled_patch16_224,91.090,8.910,98.270,1.730,5.91,224,0.900,bicubic
 gluon_resnet34_v1b,91.090,8.910,98.180,1.820,21.80,224,0.875,bicubic
+deit_tiny_distilled_patch16_224,91.090,8.910,98.270,1.730,5.91,224,0.900,bicubic
 crossvit_9_240,91.070,8.930,98.310,1.690,8.55,240,0.875,bicubic
 vgg19_bn,90.990,9.010,98.120,1.880,143.68,224,0.875,bilinear
 pit_ti_distilled_224,90.900,9.100,98.230,1.770,5.10,224,0.900,bicubic
-eca_botnext26ts_256,90.850,9.150,97.750,2.250,10.59,256,0.950,bicubic
 regnetx_006,90.750,9.250,98.100,1.900,6.20,224,0.875,bicubic
 regnety_004,90.750,9.250,98.080,1.920,4.34,224,0.875,bicubic
 ssl_resnet18,90.700,9.300,98.030,1.970,11.69,224,0.875,bilinear
@@ -485,8 +489,8 @@ crossvit_tiny_240,90.530,9.470,97.950,2.050,7.01,240,0.875,bicubic
 vgg16_bn,90.520,9.480,97.990,2.010,138.37,224,0.875,bilinear
 ghostnet_100,90.440,9.560,97.840,2.160,5.18,224,0.875,bilinear
 pit_ti_224,90.440,9.560,98.020,1.980,4.85,224,0.900,bicubic
-tv_resnet34,90.310,9.690,97.970,2.030,21.80,224,0.875,bilinear
 tf_mobilenetv3_large_075,90.310,9.690,97.880,2.120,3.99,224,0.875,bilinear
+tv_resnet34,90.310,9.690,97.970,2.030,21.80,224,0.875,bilinear
 xcit_nano_12_p16_224_dist,90.190,9.810,97.760,2.240,3.05,224,1.000,bicubic
 skresnet18,90.170,9.830,97.780,2.220,11.96,224,0.875,bicubic
 resnet18d,89.990,10.010,97.840,2.160,11.71,224,0.875,bicubic
@@ -509,7 +513,6 @@ resnet18,88.160,11.840,97.120,2.880,11.69,224,0.875,bilinear
 vgg13,87.550,12.450,97.120,2.880,133.05,224,0.875,bilinear
 regnetx_002,87.360,12.640,96.990,3.010,2.68,224,0.875,bicubic
 vgg11,87.330,12.670,97.110,2.890,132.86,224,0.875,bilinear
-botnet26t_256,87.240,12.760,96.750,3.250,12.49,256,0.950,bicubic
 dla60x_c,87.080,12.920,97.140,2.860,1.32,224,0.875,bilinear
 mixer_l16_224,86.960,13.040,94.030,5.970,208.20,224,0.875,bicubic
 tf_mobilenetv3_small_100,85.990,14.010,96.410,3.590,2.54,224,0.875,bilinear

results/results-imagenet-r.csv

@@ -3,15 +3,15 @@ ig_resnext101_32x48d,79.727,20.273,89.523,10.477,828.41,224,0.875,bilinear,-17.2
 ig_resnext101_32x32d,79.510,20.490,89.230,10.770,468.53,224,0.875,bilinear,-17.270,-10.300,+26
 ig_resnext101_32x16d,78.823,21.177,88.457,11.543,194.03,224,0.875,bilinear,-17.607,-11.083,+52
 tf_efficientnet_l2_ns_475,76.370,23.630,88.540,11.460,480.31,475,0.936,bicubic,-21.380,-11.280,0
-swsl_resnext101_32x16d,76.230,23.770,87.750,12.250,194.03,224,0.875,bilinear,-20.050,-11.750,+63
+swsl_resnext101_32x16d,76.230,23.770,87.750,12.250,194.03,224,0.875,bilinear,-20.050,-11.750,+64
 ig_resnext101_32x8d,75.890,24.110,86.243,13.757,88.79,224,0.875,bilinear,-20.060,-13.147,+89
 swsl_resnext101_32x8d,75.583,24.417,87.063,12.937,88.79,224,0.875,bilinear,-20.647,-12.527,+67
-tf_efficientnet_l2_ns,74.623,25.377,87.497,12.503,480.31,800,0.960,bicubic,-23.147,-12.313,-6
+tf_efficientnet_l2_ns,74.623,25.377,87.497,12.503,480.31,800,0.960,bicubic,-23.147,-12.313,-5
 beit_large_patch16_384,73.100,26.900,84.797,15.203,305.00,384,1.000,bicubic,-24.720,-14.993,-8
-beit_large_patch16_512,73.030,26.970,84.943,15.057,305.67,512,1.000,bicubic,-24.740,-14.947,-7
+beit_large_patch16_512,73.030,26.970,84.943,15.057,305.67,512,1.000,bicubic,-24.740,-14.947,-8
 swsl_resnext101_32x4d,72.703,27.297,85.197,14.803,44.18,224,0.875,bilinear,-23.347,-14.343,+76
 beit_large_patch16_224,71.030,28.970,83.300,16.700,304.43,224,0.900,bicubic,-26.440,-16.390,-7
-swsl_resnext50_32x4d,69.097,30.903,82.873,17.127,25.03,224,0.875,bilinear,-26.493,-16.567,+105
+swsl_resnext50_32x4d,69.097,30.903,82.873,17.127,25.03,224,0.875,bilinear,-26.493,-16.567,+106
 swsl_resnet50,68.370,31.630,83.380,16.620,25.56,224,0.875,bilinear,-26.850,-16.020,+134
 vit_large_patch16_384,67.107,32.893,78.723,21.277,304.72,384,1.000,bicubic,-30.313,-21.057,-9
 tf_efficientnet_b7_ns,67.043,32.957,81.090,18.910,66.35,600,0.949,bicubic,-30.167,-18.610,-8
@@ -27,7 +27,7 @@ tf_efficientnet_b4_ns,61.090,38.910,76.057,23.943,19.34,380,0.922,bicubic,-35.62
 tf_efficientnetv2_l_in21ft1k,60.963,39.037,75.887,24.113,118.52,480,1.000,bicubic,-36.147,-23.813,-15
 tf_efficientnetv2_xl_in21ft1k,60.710,39.290,74.393,25.607,208.12,512,1.000,bicubic,-36.440,-25.227,-17
 vit_base_patch16_384,60.197,39.803,73.840,26.160,86.86,384,1.000,bicubic,-36.823,-25.860,-14
-beit_base_patch16_224,60.143,39.857,75.367,24.633,86.53,224,0.900,bicubic,-36.507,-24.203,+9
+beit_base_patch16_224,60.143,39.857,75.367,24.633,86.53,224,0.900,bicubic,-36.507,-24.203,+8
 swin_base_patch4_window7_224,59.293,40.707,73.890,26.110,87.77,224,0.900,bicubic,-37.377,-25.780,+6
 vit_large_r50_s32_224,58.677,41.323,71.857,28.143,328.99,224,0.900,bicubic,-37.513,-27.673,+44
 tf_efficientnetv2_m_in21ft1k,58.653,41.347,74.017,25.983,54.14,480,1.000,bicubic,-38.297,-25.593,-15
@@ -42,7 +42,7 @@ xcit_large_24_p16_384_dist,54.850,45.150,69.857,30.143,189.10,384,1.000,bicubic,
 vit_base_r50_s16_384,54.340,45.660,69.510,30.490,98.95,384,1.000,bicubic,-42.130,-30.150,+9
 resnetv2_152x4_bitm,54.220,45.780,70.290,29.710,936.53,480,1.000,bilinear,-42.660,-29.370,-21
 xcit_large_24_p16_224_dist,54.217,45.783,68.950,31.050,189.10,224,1.000,bicubic,-42.093,-30.550,+21
-vit_small_r26_s32_384,54.097,45.903,68.793,31.207,36.47,384,1.000,bicubic,-41.963,-30.757,+41
+vit_small_r26_s32_384,54.097,45.903,68.793,31.207,36.47,384,1.000,bicubic,-41.963,-30.757,+42
 tf_efficientnet_b5_ap,53.923,46.077,69.180,30.820,30.39,456,0.934,bicubic,-42.157,-30.200,+36
 xcit_medium_24_p8_224_dist,53.650,46.350,68.327,31.673,84.32,224,1.000,bicubic,-42.850,-31.173,+1
 tf_efficientnet_b6_ap,53.560,46.440,68.580,31.420,43.04,528,0.942,bicubic,-42.800,-30.970,+11
@@ -51,7 +51,7 @@ tf_efficientnet_b2_ns,53.503,46.497,70.393,29.607,9.11,260,0.890,bicubic,-42.027
 vit_base_patch32_384,53.340,46.660,68.133,31.867,88.30,384,1.000,bicubic,-42.570,-31.047,+48
 tf_efficientnet_b7_ap,53.320,46.680,68.900,31.100,66.35,600,0.949,bicubic,-43.030,-30.700,+9
 xcit_medium_24_p8_384_dist,53.297,46.703,68.067,31.933,84.32,384,1.000,bicubic,-43.483,-31.553,-23
-tf_efficientnetv2_s_in21ft1k,53.253,46.747,69.057,30.943,21.46,384,1.000,bicubic,-43.207,-30.573,-2
+tf_efficientnetv2_s_in21ft1k,53.253,46.747,69.057,30.943,21.46,384,1.000,bicubic,-43.207,-30.573,-1
 xcit_medium_24_p16_384_dist,53.210,46.790,68.047,31.953,84.40,384,1.000,bicubic,-43.480,-31.553,-19
 tf_efficientnet_b8,53.200,46.800,68.953,31.047,87.41,672,0.954,bicubic,-43.500,-30.597,-21
 tf_efficientnet_b4_ap,53.073,46.927,68.237,31.763,19.34,380,0.922,bicubic,-42.427,-31.153,+71
@@ -59,9 +59,9 @@ dm_nfnet_f5,52.717,47.283,67.250,32.750,377.21,544,0.954,bicubic,-44.083,-32.420
 efficientnetv2_rw_m,52.347,47.653,67.260,32.740,53.24,416,1.000,bicubic,-43.923,-32.300,+12
 tf_efficientnet_b7,52.303,47.697,68.230,31.770,66.35,600,0.949,bicubic,-44.277,-31.280,-17
 xcit_small_24_p8_384_dist,52.283,47.717,66.753,33.247,47.63,384,1.000,bicubic,-44.547,-32.877,-36
-tf_efficientnetv2_l,52.277,47.723,67.197,32.803,118.52,480,1.000,bicubic,-44.373,-32.463,-24
+tf_efficientnetv2_l,52.277,47.723,67.197,32.803,118.52,480,1.000,bicubic,-44.373,-32.463,-23
 dm_nfnet_f6,52.250,47.750,66.963,33.037,438.36,576,0.956,bicubic,-44.660,-32.757,-42
-swsl_resnet18,52.243,47.757,70.503,29.497,11.69,224,0.875,bilinear,-38.847,-27.767,+408
+swsl_resnet18,52.243,47.757,70.503,29.497,11.69,224,0.875,bilinear,-38.847,-27.707,+413
 xcit_medium_24_p16_224_dist,52.210,47.790,66.883,33.117,84.40,224,1.000,bicubic,-44.050,-32.517,+7
 deit_base_distilled_patch16_384,52.180,47.820,67.693,32.307,87.63,384,1.000,bicubic,-44.310,-31.897,-17
 xcit_small_24_p8_224_dist,52.133,47.867,66.717,33.283,47.63,224,1.000,bicubic,-44.417,-32.843,-21
@@ -71,7 +71,7 @@ resmlp_big_24_224_in22ft1k,51.893,48.107,68.423,31.577,129.14,224,0.875,bicubic,
 xcit_small_24_p16_384_dist,51.883,48.117,66.307,33.693,47.67,384,1.000,bicubic,-44.477,-33.283,-11
 resnetv2_152x2_bitm,51.780,48.220,69.353,30.647,236.34,448,1.000,bilinear,-44.740,-30.237,-25
 cait_s24_384,51.727,48.273,66.330,33.670,47.06,384,1.000,bicubic,-44.853,-33.220,-31
-ecaresnet269d,51.590,48.410,66.087,33.913,102.09,352,1.000,bicubic,-44.870,-33.483,-20
+ecaresnet269d,51.590,48.410,66.087,33.913,102.09,352,1.000,bicubic,-44.870,-33.483,-22
 vit_base_patch16_224_miil,51.557,48.443,65.253,34.747,86.54,224,0.875,bilinear,-44.483,-34.097,+14
 pit_b_distilled_224,51.163,48.837,66.773,33.227,74.79,224,0.900,bicubic,-44.917,-32.767,+8
 xcit_small_12_p8_384_dist,51.040,48.960,65.710,34.290,26.21,384,1.000,bicubic,-45.440,-33.770,-27
@@ -80,11 +80,11 @@ tf_efficientnet_b1_ns,50.767,49.233,67.963,32.037,7.79,240,0.882,bicubic,-44.113
 xcit_small_24_p16_224_dist,50.700,49.300,65.007,34.993,47.67,224,1.000,bicubic,-45.110,-34.333,+26
 tf_efficientnetv2_m,50.570,49.430,66.013,33.987,54.14,480,1.000,bicubic,-45.980,-33.557,-36
 efficientnet_b4,50.523,49.477,65.800,34.200,19.34,384,1.000,bicubic,-45.017,-33.600,+41
-resnetv2_101x3_bitm,50.520,49.480,67.963,32.037,387.93,448,1.000,bilinear,-45.770,-31.667,-16
+resnetv2_101x3_bitm,50.520,49.480,67.963,32.037,387.93,448,1.000,bilinear,-45.770,-31.667,-15
 xcit_small_12_p16_384_dist,50.447,49.553,65.287,34.713,26.25,384,1.000,bicubic,-45.883,-34.203,-20
 xcit_small_12_p8_224_dist,50.400,49.600,65.440,34.560,26.21,224,1.000,bicubic,-45.560,-33.980,+10
 cait_s24_224,50.230,49.770,65.033,34.967,46.92,224,1.000,bicubic,-45.410,-34.357,+32
-eca_nfnet_l2,50.227,49.773,65.463,34.537,56.72,384,1.000,bicubic,-46.233,-34.147,-34
+eca_nfnet_l2,50.227,49.773,65.463,34.537,56.72,384,1.000,bicubic,-46.233,-34.147,-33
 ssl_resnext101_32x16d,50.220,49.780,66.073,33.927,194.03,224,0.875,bilinear,-45.180,-33.337,+49
 vit_small_patch16_384,50.153,49.847,65.883,34.117,22.20,384,1.000,bicubic,-45.827,-33.717,+4
 resnest269e,50.137,49.863,64.713,35.287,110.93,416,0.928,bicubic,-45.983,-34.807,-12
@@ -95,15 +95,15 @@ cait_xs24_384,49.510,50.490,64.843,35.157,26.67,384,1.000,bicubic,-46.500,-34.58
 tf_efficientnet_b5,49.503,50.497,65.597,34.403,30.39,456,0.934,bicubic,-46.477,-33.853,-3
 xcit_small_12_p16_224_dist,49.443,50.557,63.893,36.107,26.25,224,1.000,bicubic,-46.307,-35.397,+13
 resnet200d,49.427,50.573,64.303,35.697,64.69,320,1.000,bicubic,-46.683,-35.157,-17
-vit_base_patch32_224,49.383,50.617,64.450,35.550,88.22,224,0.900,bicubic,-44.997,-34.610,+136
+vit_base_patch32_224,49.383,50.617,64.450,35.550,88.22,224,0.900,bicubic,-44.997,-34.610,+139
 resnest101e,49.377,50.623,65.527,34.473,48.28,256,0.875,bilinear,-46.203,-33.743,+22
 resnet152d,49.257,50.743,64.427,35.573,60.21,320,1.000,bicubic,-46.593,-35.003,+4
 seresnet152d,49.217,50.783,64.277,35.723,66.84,320,1.000,bicubic,-47.113,-35.233,-38
 resnetv2_152x2_bit_teacher,49.190,50.810,65.430,34.570,236.34,224,0.875,bicubic,-46.540,-34.000,+8
 ssl_resnext101_32x8d,49.153,50.847,65.503,34.497,88.79,224,0.875,bilinear,-46.167,-33.807,+41
-xcit_large_24_p8_224,49.143,50.857,62.727,37.273,188.93,224,1.000,bicubic,-46.917,-36.423,-17
-resmlp_big_24_distilled_224,49.047,50.953,65.463,34.537,129.14,224,0.875,bicubic,-46.823,-33.977,-4
-repvgg_b3,49.023,50.977,64.877,35.123,123.09,224,0.875,bilinear,-45.537,-34.033,+112
+xcit_large_24_p8_224,49.143,50.857,62.727,37.273,188.93,224,1.000,bicubic,-46.917,-36.423,-18
+resmlp_big_24_distilled_224,49.047,50.953,65.463,34.537,129.14,224,0.875,bicubic,-46.823,-33.977,-3
+repvgg_b3,49.023,50.977,64.877,35.123,123.09,224,0.875,bilinear,-45.537,-34.033,+113
 resnetrs420,48.817,51.183,63.453,36.547,191.89,416,1.000,bicubic,-47.583,-36.087,-50
 efficientnetv2_rw_s,48.673,51.327,63.863,36.137,23.94,384,1.000,bicubic,-47.027,-35.517,+8
 regnetz_d,48.633,51.367,65.220,34.780,27.58,320,0.950,bicubic,-47.227,-34.220,-6
@@ -111,14 +111,14 @@ efficientnet_b3,48.580,51.420,64.343,35.657,12.23,320,1.000,bicubic,-46.570,-34.
 ecaresnet101d,48.473,51.527,64.090,35.910,44.57,224,0.875,bicubic,-46.687,-35.140,+43
 vit_small_r26_s32_224,48.417,51.583,63.927,36.073,36.43,224,0.900,bicubic,-46.703,-35.293,+47
 vit_large_patch32_384,48.353,51.647,61.907,38.093,306.63,384,1.000,bicubic,-46.897,-37.413,+33
-repvgg_b3g4,48.270,51.730,64.820,35.180,83.83,224,0.875,bilinear,-46.220,-34.200,+111
+repvgg_b3g4,48.270,51.730,64.820,35.180,83.83,224,0.875,bilinear,-46.220,-34.200,+113
 convit_base,48.243,51.757,63.003,36.997,86.54,224,0.875,bicubic,-46.857,-36.127,+48
 dm_nfnet_f2,48.203,51.797,63.200,36.800,193.78,352,0.920,bicubic,-48.247,-36.340,-61
 resnetrs350,47.963,52.037,62.577,37.423,163.96,384,1.000,bicubic,-48.277,-36.893,-43
-twins_svt_large,47.907,52.093,62.860,37.140,99.27,224,0.900,bicubic,-47.813,-36.510,-5
+twins_svt_large,47.907,52.093,62.860,37.140,99.27,224,0.900,bicubic,-47.813,-36.510,-6
 mixer_b16_224_miil,47.827,52.173,63.363,36.637,59.88,224,0.875,bilinear,-47.063,-35.717,+64
-repvgg_b2g4,47.773,52.227,64.427,35.573,61.76,224,0.875,bilinear,-46.047,-34.493,+176
-resnetv2_50x3_bitm,47.757,52.243,65.667,34.333,217.32,448,1.000,bilinear,-48.533,-33.913,-53
+repvgg_b2g4,47.773,52.227,64.427,35.573,61.76,224,0.875,bilinear,-46.047,-34.493,+179
+resnetv2_50x3_bitm,47.757,52.243,65.667,34.333,217.32,448,1.000,bilinear,-48.533,-33.913,-54
 eca_nfnet_l1,47.610,52.390,62.650,37.350,41.41,320,1.000,bicubic,-48.310,-36.850,-25
 pit_s_distilled_224,47.603,52.397,63.543,36.457,24.04,224,0.900,bicubic,-47.147,-35.637,+70
 resnest50d_4s2x40d,47.503,52.497,63.863,36.137,30.42,224,0.875,bicubic,-47.207,-35.267,+72
@@ -127,32 +127,32 @@ crossvit_18_dagger_408,47.353,52.647,60.900,39.100,44.61,408,1.000,bicubic,-48.7
 xcit_small_24_p8_224,47.340,52.660,61.097,38.903,47.63,224,1.000,bicubic,-48.570,-38.343,-29
 tresnet_m,47.297,52.703,62.087,37.913,31.39,224,0.875,bilinear,-48.103,-37.063,+10
 ssl_resnext101_32x4d,47.167,52.833,63.390,36.610,44.18,224,0.875,bilinear,-47.973,-35.920,+27
-tf_efficientnet_b6,47.150,52.850,63.057,36.943,43.04,528,0.942,bicubic,-49.130,-36.463,-60
+tf_efficientnet_b6,47.150,52.850,63.057,36.943,43.04,528,0.942,bicubic,-49.130,-36.463,-61
 resnetrs270,47.147,52.853,62.057,37.943,129.86,352,1.000,bicubic,-48.923,-37.423,-46
-xcit_small_12_p8_224,47.057,52.943,60.570,39.430,26.21,224,1.000,bicubic,-48.363,-38.630,+3
-tf_efficientnet_b4,47.027,52.973,62.907,37.093,19.34,380,0.922,bicubic,-48.563,-36.413,-13
+xcit_small_12_p8_224,47.057,52.943,60.570,39.430,26.21,224,1.000,bicubic,-48.363,-38.860,+3
+tf_efficientnet_b4,47.027,52.973,62.907,37.093,19.34,380,0.922,bicubic,-48.563,-36.413,-14
 resnet101d,46.907,53.093,62.357,37.643,44.57,320,1.000,bicubic,-48.843,-37.083,-26
-xcit_large_24_p16_224,46.877,53.123,60.770,39.230,189.10,224,1.000,bicubic,-48.073,-38.060,+39
+xcit_large_24_p16_224,46.877,53.123,60.770,39.230,189.10,224,1.000,bicubic,-48.073,-38.400,+38
 resnetrs200,46.867,53.133,62.480,37.520,93.21,320,1.000,bicubic,-49.133,-36.960,-45
 gluon_seresnext101_64x4d,46.677,53.323,61.363,38.637,88.23,224,0.875,bicubic,-47.983,-37.607,+68
-twins_pcpvt_large,46.557,53.443,62.170,37.830,60.99,224,0.900,bicubic,-49.163,-37.320,-26
+twins_pcpvt_large,46.557,53.443,62.170,37.830,60.99,224,0.900,bicubic,-49.163,-37.320,-27
 dm_nfnet_f1,46.457,53.543,61.450,38.550,132.63,320,0.910,bicubic,-49.913,-38.030,-81
-xcit_medium_24_p8_224,46.427,53.573,59.607,40.393,84.32,224,1.000,bicubic,-49.443,-39.483,-38
+xcit_medium_24_p8_224,46.427,53.573,59.607,40.393,84.32,224,1.000,bicubic,-49.443,-39.483,-39
 crossvit_15_dagger_408,46.367,53.633,60.537,39.463,28.50,408,1.000,bicubic,-49.453,-38.763,-36
 tresnet_xl,46.277,53.723,61.907,38.093,78.44,224,0.875,bilinear,-48.803,-37.313,+22
 xcit_tiny_24_p8_224_dist,46.250,53.750,60.627,39.373,12.11,224,1.000,bicubic,-49.210,-38.723,-11
 xcit_tiny_24_p8_384_dist,46.233,53.767,60.660,39.340,12.11,384,1.000,bicubic,-50.017,-38.780,-71
-gernet_m,46.157,53.843,62.720,37.280,21.14,224,0.875,bilinear,-48.393,-36.200,+74
-deit_small_distilled_patch16_224,46.150,53.850,62.447,37.553,22.44,224,0.900,bicubic,-48.440,-36.483,+68
-resnest50d_1s4x24d,46.133,53.867,62.483,37.517,25.68,224,0.875,bicubic,-48.247,-36.577,+86
+gernet_m,46.157,53.843,62.720,37.280,21.14,224,0.875,bilinear,-48.393,-36.200,+75
+deit_small_distilled_patch16_224,46.150,53.850,62.447,37.553,22.44,224,0.900,bicubic,-48.440,-36.673,+66
+resnest50d_1s4x24d,46.133,53.867,62.483,37.517,25.68,224,0.875,bicubic,-48.247,-36.577,+89
 regnety_160,46.123,53.877,61.803,38.197,83.59,288,1.000,bicubic,-49.777,-37.757,-48
 crossvit_base_240,46.087,53.913,60.247,39.753,105.03,240,0.875,bicubic,-48.973,-38.733,+18
-tf_efficientnet_b0_ns,46.047,53.953,63.280,36.720,5.29,224,0.875,bicubic,-47.713,-35.700,+155
+tf_efficientnet_b0_ns,46.047,53.953,63.280,36.720,5.29,224,0.875,bicubic,-47.713,-35.700,+158
 vit_small_patch16_224,46.027,53.973,61.850,38.150,22.05,224,0.900,bicubic,-48.873,-37.180,+30
 resnet51q,46.017,53.983,60.917,39.083,35.70,288,1.000,bilinear,-49.173,-38.363,-1
 jx_nest_base,45.973,54.027,60.113,39.887,67.72,224,0.875,bicubic,-49.557,-39.187,-28
 crossvit_18_240,45.923,54.077,60.380,39.620,43.27,240,0.875,bicubic,-49.127,-38.740,+14
-resnest50d,45.900,54.100,62.673,37.327,27.48,224,0.875,bilinear,-48.720,-36.357,+54
+resnest50d,45.900,54.100,62.673,37.327,27.48,224,0.875,bilinear,-48.720,-36.357,+53
 twins_pcpvt_base,45.890,54.110,61.357,38.643,43.83,224,0.900,bicubic,-49.580,-38.023,-26
 regnety_032,45.887,54.113,61.520,38.480,19.44,288,1.000,bicubic,-49.583,-37.800,-28
 twins_svt_base,45.863,54.137,60.903,39.097,56.07,224,0.900,bicubic,-49.707,-38.327,-36
@@ -160,360 +160,363 @@ crossvit_18_dagger_240,45.820,54.180,59.963,40.037,44.27,240,0.875,bicubic,-49.3
 levit_384,45.783,54.217,61.727,38.273,39.13,224,0.900,bicubic,-49.417,-37.433,-10
 gc_efficientnetv2_rw_t,45.703,54.297,60.197,39.803,13.68,288,1.000,bicubic,-49.577,-39.023,-16
 regnetz_c,45.667,54.333,62.437,37.563,13.46,320,0.940,bicubic,-49.743,-36.873,-26
-convmixer_1536_20,45.647,54.353,61.740,38.260,51.63,224,0.960,bicubic,-49.303,-37.430,+10
+convmixer_1536_20,45.647,54.353,61.740,38.260,51.63,224,0.960,bicubic,-49.303,-37.090,+11
 efficientnetv2_rw_t,45.593,54.407,60.160,39.840,13.65,288,1.000,bicubic,-49.487,-39.090,+1
-crossvit_15_dagger_240,45.580,54.420,60.053,39.947,28.21,240,0.875,bicubic,-49.390,-39.097,+5
+crossvit_15_dagger_240,45.580,54.420,60.053,39.947,28.21,240,0.875,bicubic,-49.390,-39.097,+6
 xcit_tiny_24_p16_384_dist,45.563,54.437,60.473,39.527,12.12,384,1.000,bicubic,-49.897,-38.897,-35
 xcit_medium_24_p16_224,45.560,54.440,58.993,41.007,84.40,224,1.000,bicubic,-49.570,-39.937,-10
 dm_nfnet_f0,45.543,54.457,61.013,38.987,71.49,256,0.900,bicubic,-50.167,-38.387,-53
-gluon_seresnext101_32x4d,45.517,54.483,61.147,38.853,48.96,224,0.875,bicubic,-48.913,-37.963,+59
+gluon_seresnext101_32x4d,45.517,54.483,61.147,38.853,48.96,224,0.875,bicubic,-48.913,-37.963,+61
 xcit_small_24_p16_224,45.493,54.507,58.910,41.090,47.67,224,1.000,bicubic,-49.577,-40.150,-4
-gluon_resnet152_v1d,45.433,54.567,60.093,39.907,60.21,224,0.875,bicubic,-49.027,-38.907,+55
+gluon_resnet152_v1d,45.433,54.567,60.093,39.907,60.21,224,0.875,bicubic,-49.027,-38.907,+57
 xcit_small_12_p16_224,45.433,54.567,59.407,40.593,26.25,224,1.000,bicubic,-49.377,-39.653,+15
-nfnet_l0,45.367,54.633,62.073,37.927,35.07,288,1.000,bicubic,-50.053,-37.357,-39
-ssl_resnext50_32x4d,45.363,54.637,61.973,38.027,25.03,224,0.875,bilinear,-49.337,-37.267,+24
+nfnet_l0,45.367,54.633,62.073,37.927,35.07,288,1.000,bicubic,-50.053,-37.127,-39
+ssl_resnext50_32x4d,45.363,54.637,61.973,38.027,25.03,224,0.875,bilinear,-49.337,-36.997,+23
 resnetv2_50x1_bit_distilled,45.330,54.670,62.290,37.710,25.55,224,0.875,bicubic,-50.060,-37.140,-36
 jx_nest_small,45.317,54.683,59.017,40.983,38.35,224,0.875,bicubic,-50.223,-40.213,-52
 resnet61q,45.277,54.723,59.350,40.650,36.85,288,1.000,bicubic,-49.833,-39.730,-15
 convit_small,45.227,54.773,60.530,39.470,27.78,224,0.875,bicubic,-49.693,-38.590,0
 nasnetalarge,45.197,54.803,57.960,42.040,88.75,331,0.911,bicubic,-49.973,-41.170,-26
 tresnet_xl_448,45.163,54.837,61.440,38.560,78.44,448,0.875,bilinear,-50.357,-37.900,-53
-swin_small_patch4_window7_224,45.133,54.867,60.270,39.730,49.61,224,0.900,bicubic,-50.587,-39.020,-70
+swin_small_patch4_window7_224,45.133,54.867,60.270,39.730,49.61,224,0.900,bicubic,-50.587,-39.020,-68
 tf_efficientnet_b3,45.100,54.900,60.677,39.323,12.23,300,0.904,bicubic,-49.810,-38.423,-2
 rexnet_200,45.067,54.933,62.223,37.777,16.37,224,0.875,bicubic,-49.603,-36.867,+20
 resnetrs152,44.990,55.010,59.683,40.317,86.62,320,1.000,bicubic,-50.970,-39.697,-90
-ecaresnetlight,44.907,55.093,60.763,39.237,30.16,224,0.875,bicubic,-49.233,-38.267,+76
+ecaresnetlight,44.907,55.093,60.763,39.237,30.16,224,0.875,bicubic,-49.233,-38.027,+78
 deit_base_patch16_224,44.893,55.107,59.203,40.797,86.57,224,0.900,bicubic,-50.127,-39.767,-17
 resnetv2_101,44.817,55.183,58.843,41.157,44.54,224,0.950,bicubic,-50.113,-40.267,-10
-resmlp_24_distilled_224,44.787,55.213,61.517,38.483,30.02,224,0.875,bicubic,-49.553,-37.573,+51
+resmlp_24_distilled_224,44.787,55.213,61.517,38.483,30.02,224,0.875,bicubic,-49.553,-37.573,+54
 cait_xxs36_384,44.750,55.250,59.410,40.590,17.37,384,1.000,bicubic,-50.490,-39.920,-42
-tf_efficientnet_b2_ap,44.743,55.257,60.693,39.307,9.11,260,0.890,bicubic,-49.537,-38.257,+55
-resmlp_36_distilled_224,44.720,55.280,61.110,38.890,44.69,224,0.875,bicubic,-49.830,-38.050,+29
+tf_efficientnet_b2_ap,44.743,55.257,60.693,39.307,9.11,260,0.890,bicubic,-49.537,-38.257,+58
+resmlp_36_distilled_224,44.720,55.280,61.110,38.890,44.69,224,0.875,bicubic,-49.830,-38.050,+31
 gernet_l,44.697,55.303,59.007,40.993,31.08,256,0.875,bilinear,-50.223,-40.193,-13
-xcit_tiny_24_p16_224_dist,44.690,55.310,59.397,40.603,12.12,224,1.000,bicubic,-49.530,-39.563,+57
+xcit_tiny_24_p16_224_dist,44.690,55.310,59.397,40.603,12.12,224,1.000,bicubic,-49.530,-39.563,+60
 deit_base_patch16_384,44.660,55.340,59.570,40.430,86.86,384,1.000,bicubic,-51.000,-39.670,-77
-gmlp_s16_224,44.487,55.513,58.667,41.333,19.42,224,0.875,bicubic,-49.023,-40.113,+142
-ens_adv_inception_resnet_v2,44.407,55.593,58.153,41.847,55.84,299,0.897,bicubic,-49.733,-40.797,+63
+gmlp_s16_224,44.487,55.513,58.667,41.333,19.42,224,0.875,bicubic,-49.023,-40.113,+145
+ens_adv_inception_resnet_v2,44.407,55.593,58.153,41.847,55.84,299,0.897,bicubic,-49.733,-40.877,+68
 tresnet_l,44.360,55.640,59.953,40.047,55.99,224,0.875,bilinear,-50.540,-39.327,-15
-gluon_resnext101_32x4d,44.330,55.670,59.097,40.903,44.18,224,0.875,bicubic,-49.790,-39.843,+64
-cspresnext50,44.180,55.820,60.463,39.537,20.57,224,0.875,bilinear,-49.590,-38.377,+102
+gluon_resnext101_32x4d,44.330,55.670,59.097,40.903,44.18,224,0.875,bicubic,-49.790,-39.843,+67
+cspresnext50,44.180,55.820,60.463,39.537,20.57,224,0.875,bilinear,-49.590,-38.377,+107
 wide_resnet50_2,44.157,55.843,59.657,40.343,68.88,224,0.875,bicubic,-50.493,-39.393,+6
 crossvit_15_240,44.140,55.860,59.153,40.847,27.53,240,0.875,bicubic,-50.540,-39.917,0
 resnetv2_101x1_bitm,44.113,55.887,62.063,37.937,44.54,448,1.000,bilinear,-51.217,-37.317,-59
 gluon_resnet152_v1s,44.090,55.910,58.743,41.257,60.32,224,0.875,bicubic,-50.600,-40.307,-4
 pit_b_224,44.080,55.920,57.990,42.010,73.76,224,0.900,bicubic,-50.710,-40.820,-15
 seresnext50_32x4d,44.077,55.923,59.413,40.587,27.56,224,0.875,bicubic,-50.723,-39.717,-17
-inception_resnet_v2,44.057,55.943,57.930,42.070,55.84,299,0.897,bicubic,-50.263,-40.870,+35
+inception_resnet_v2,44.057,55.943,57.930,42.070,55.84,299,0.897,bicubic,-50.263,-40.870,+38
 pnasnet5large,43.993,56.007,56.770,43.230,86.06,331,0.911,bicubic,-51.377,-42.360,-66
-ssl_resnet50,43.903,56.097,61.940,38.060,25.56,224,0.875,bilinear,-50.417,-37.220,+34
-gluon_resnext101_64x4d,43.900,56.100,58.703,41.297,83.46,224,0.875,bicubic,-50.430,-40.177,+31
-pit_s_224,43.893,56.107,58.663,41.337,23.46,224,0.900,bicubic,-50.697,-40.457,+2
+ssl_resnet50,43.903,56.097,61.940,38.060,25.56,224,0.875,bilinear,-50.417,-37.220,+37
+gluon_resnext101_64x4d,43.900,56.100,58.703,41.297,83.46,224,0.875,bicubic,-50.430,-40.177,+34
+pit_s_224,43.893,56.107,58.663,41.337,23.46,224,0.900,bicubic,-50.697,-40.427,+3
 tf_efficientnetv2_s,43.853,56.147,58.710,41.290,21.46,384,1.000,bicubic,-51.857,-40.620,-97
-cait_xxs36_224,43.823,56.177,58.773,41.227,17.30,224,1.000,bicubic,-50.117,-40.107,+67
-ecaresnet101d_pruned,43.787,56.213,59.647,40.353,24.88,224,0.875,bicubic,-50.653,-39.453,+14
+cait_xxs36_224,43.823,56.177,58.773,41.227,17.30,224,1.000,bicubic,-50.117,-40.107,+70
+ecaresnet101d_pruned,43.787,56.213,59.647,40.353,24.88,224,0.875,bicubic,-50.653,-39.453,+16
 coat_lite_small,43.780,56.220,56.930,43.070,19.84,224,0.900,bicubic,-51.330,-42.100,-54
 tnt_s_patch16_224,43.767,56.233,59.223,40.777,23.76,224,0.900,bicubic,-50.803,-39.957,+1
-ecaresnet50d,43.703,56.297,60.380,39.620,25.58,224,0.875,bicubic,-50.507,-38.630,+35
-pit_xs_distilled_224,43.683,56.317,60.680,39.320,11.00,224,0.900,bicubic,-49.547,-38.140,+144
+ecaresnet50d,43.703,56.297,60.380,39.620,25.58,224,0.875,bicubic,-50.507,-38.630,+38
+pit_xs_distilled_224,43.683,56.317,60.680,39.320,11.00,224,0.900,bicubic,-49.547,-38.140,+149
 xcit_tiny_12_p8_224_dist,43.597,56.403,58.480,41.520,6.71,224,1.000,bicubic,-51.143,-40.700,-24
-rexnet_150,43.587,56.413,60.837,39.163,9.73,224,0.875,bicubic,-50.683,-38.253,+28
-crossvit_small_240,43.510,56.490,58.980,41.020,26.86,240,0.875,bicubic,-51.080,-40.110,-7
+rexnet_150,43.587,56.413,60.837,39.163,9.73,224,0.875,bicubic,-50.683,-38.253,+30
+crossvit_small_240,43.510,56.490,58.980,41.020,26.86,240,0.875,bicubic,-51.080,-39.950,-6
 ecaresnet50t,43.420,56.580,59.327,40.673,25.57,320,0.950,bicubic,-51.690,-39.963,-60
-gluon_resnet101_v1d,43.420,56.580,58.560,41.440,44.57,224,0.875,bicubic,-50.760,-40.390,+33
-gluon_resnet101_v1s,43.410,56.590,58.703,41.297,44.67,224,0.875,bicubic,-50.770,-40.317,+33
-cspdarknet53,43.330,56.670,59.487,40.513,27.64,256,0.887,bilinear,-50.770,-39.493,+40
+gluon_resnet101_v1d,43.420,56.580,58.560,41.440,44.57,224,0.875,bicubic,-50.760,-40.390,+36
+gluon_resnet101_v1s,43.410,56.590,58.703,41.297,44.67,224,0.875,bicubic,-50.770,-40.317,+34
+cspdarknet53,43.330,56.670,59.487,40.513,27.64,256,0.887,bilinear,-50.770,-39.493,+43
 eca_nfnet_l0,43.297,56.703,59.910,40.090,24.14,288,1.000,bicubic,-52.153,-39.480,-92
-convmixer_768_32,43.263,56.737,59.270,40.730,21.11,224,0.960,bicubic,-51.167,-39.820,+3
-xcit_tiny_24_p8_224,43.263,56.737,57.297,42.703,12.11,224,1.000,bicubic,-51.607,-41.893,-41
-dpn68b,43.257,56.743,58.610,41.390,12.61,224,0.875,bicubic,-50.343,-40.100,+98
+convmixer_768_32,43.263,56.737,59.270,40.730,21.11,224,0.960,bicubic,-51.167,-39.820,+5
+xcit_tiny_24_p8_224,43.263,56.737,57.297,42.703,12.11,224,1.000,bicubic,-51.607,-41.893,-42
+dpn68b,43.257,56.743,58.610,41.390,12.61,224,0.875,bicubic,-50.343,-40.100,+101
 xcit_tiny_12_p8_384_dist,43.253,56.747,58.160,41.840,6.71,384,1.000,bicubic,-52.087,-41.180,-87
-visformer_small,43.187,56.813,57.970,42.030,40.22,224,0.900,bicubic,-51.783,-41.240,-59
+visformer_small,43.187,56.813,57.970,42.030,40.22,224,0.900,bicubic,-51.783,-41.240,-60
 vit_small_patch32_384,43.137,56.863,59.273,40.727,22.92,384,1.000,bicubic,-51.433,-39.867,-14
-cspresnet50,43.130,56.870,59.230,40.770,21.62,256,0.887,bilinear,-50.720,-39.540,+61
-resnest26d,43.107,56.893,60.597,39.403,17.07,224,0.875,bilinear,-50.153,-38.243,+125
+cspresnet50,43.130,56.870,59.230,40.770,21.62,256,0.887,bilinear,-50.720,-39.700,+61
+resnest26d,43.107,56.893,60.597,39.403,17.07,224,0.875,bilinear,-50.153,-38.243,+130
 twins_pcpvt_small,43.080,56.920,58.913,41.087,24.11,224,0.900,bicubic,-51.520,-40.227,-23
-dpn131,43.003,56.997,57.420,42.580,79.25,224,0.875,bicubic,-50.757,-41.430,+69
-resmlp_36_224,43.003,56.997,59.417,40.583,44.69,224,0.875,bicubic,-50.667,-39.533,+81
-gluon_resnet152_v1b,42.987,57.013,57.727,42.273,60.19,224,0.875,bicubic,-51.033,-41.023,+36
-dpn107,42.883,57.117,57.533,42.467,86.92,224,0.875,bicubic,-51.077,-41.307,+38
-tf_efficientnet_lite4,42.860,57.140,57.723,42.277,13.01,380,0.920,bilinear,-52.010,-41.367,-54
-gcresnet50t,42.840,57.160,59.237,40.763,25.90,256,0.900,bicubic,-51.770,-39.753,-30
-gluon_resnet152_v1c,42.830,57.170,57.807,42.193,60.21,224,0.875,bicubic,-51.050,-40.993,+46
+dpn131,43.003,56.997,57.420,42.580,79.25,224,0.875,bicubic,-50.757,-41.430,+72
+resmlp_36_224,43.003,56.997,59.417,40.583,44.69,224,0.875,bicubic,-50.667,-39.533,+83
+gluon_resnet152_v1b,42.987,57.013,57.727,42.273,60.19,224,0.875,bicubic,-51.033,-41.023,+39
+dpn107,42.883,57.117,57.533,42.467,86.92,224,0.875,bicubic,-51.077,-41.307,+41
+tf_efficientnet_lite4,42.860,57.140,57.723,42.277,13.01,380,0.920,bilinear,-52.010,-41.367,-53
+gcresnet50t,42.840,57.160,59.237,40.763,25.90,256,0.900,bicubic,-51.770,-39.753,-31
+gluon_resnet152_v1c,42.830,57.170,57.807,42.193,60.21,224,0.875,bicubic,-51.050,-40.993,+49
 twins_svt_small,42.830,57.170,58.473,41.527,24.06,224,0.900,bicubic,-51.940,-40.607,-52
-tf_efficientnet_b1_ap,42.823,57.177,58.853,41.147,7.79,240,0.882,bicubic,-50.817,-39.927,+78
-levit_256,42.807,57.193,57.913,42.087,18.89,224,0.900,bicubic,-51.603,-41.147,-13
+tf_efficientnet_b1_ap,42.823,57.177,58.853,41.147,7.79,240,0.882,bicubic,-50.817,-39.927,+81
+levit_256,42.807,57.193,57.913,42.087,18.89,224,0.900,bicubic,-51.603,-41.147,-10
 tresnet_l_448,42.780,57.220,58.937,41.063,55.99,448,0.875,bilinear,-52.610,-40.343,-105
-gluon_xception65,42.730,57.270,58.867,41.133,39.92,299,0.903,bicubic,-51.310,-40.163,+24
-resnet50d,42.703,57.297,58.770,41.230,25.58,224,0.875,bicubic,-51.367,-40.150,+19
-gluon_seresnext50_32x4d,42.693,57.307,58.713,41.287,27.56,224,0.875,bicubic,-51.487,-40.197,+9
-resnext101_32x8d,42.577,57.423,58.337,41.663,88.79,224,0.875,bilinear,-51.193,-40.613,+54
-xcit_tiny_12_p16_384_dist,42.563,57.437,58.057,41.943,6.72,384,1.000,bicubic,-51.977,-41.113,-29
-seresnet50,42.507,57.493,58.760,41.240,28.09,224,0.875,bicubic,-51.573,-40.190,+14
-nf_resnet50,42.490,57.510,59.593,40.407,25.56,288,0.940,bicubic,-51.890,-39.477,-20
+gluon_xception65,42.730,57.270,58.867,41.133,39.92,299,0.903,bicubic,-51.310,-40.163,+27
+resnet50d,42.703,57.297,58.770,41.230,25.58,224,0.875,bicubic,-51.367,-40.150,+22
+gluon_seresnext50_32x4d,42.693,57.307,58.713,41.287,27.56,224,0.875,bicubic,-51.487,-40.197,+12
+resnext101_32x8d,42.577,57.423,58.337,41.663,88.79,224,0.875,bilinear,-51.193,-40.613,+55
+xcit_tiny_12_p16_384_dist,42.563,57.437,58.057,41.943,6.72,384,1.000,bicubic,-51.977,-41.113,-27
+seresnet50,42.507,57.493,58.760,41.240,28.09,224,0.875,bicubic,-51.573,-40.190,+17
+nf_resnet50,42.490,57.510,59.593,40.407,25.56,288,0.940,bicubic,-51.890,-39.477,-17
 resnetrs101,42.447,57.553,57.300,42.700,63.62,288,0.940,bicubic,-52.783,-41.910,-105
 tf_efficientnetv2_b3,42.317,57.683,58.000,42.000,14.36,300,0.904,bicubic,-52.803,-41.190,-96
 jx_nest_tiny,42.313,57.687,57.023,42.977,17.06,224,0.875,bicubic,-52.627,-42.077,-79
 legacy_senet154,42.283,57.717,56.573,43.427,115.09,224,0.875,bilinear,-52.447,-42.527,-61
-dpn98,42.277,57.723,56.927,43.073,61.57,224,0.875,bicubic,-51.653,-41.993,+23
-tf_efficientnet_cc_b1_8e,42.273,57.727,58.527,41.473,39.72,240,0.882,bicubic,-51.307,-40.163,+72
-xcit_tiny_24_p16_224,42.273,57.727,56.780,43.220,12.12,224,1.000,bicubic,-51.577,-42.120,+31
-convmixer_1024_20_ks9_p14,42.270,57.730,59.693,40.307,24.38,224,0.960,bicubic,-50.080,-38.727,+164
-deit_small_patch16_224,42.257,57.743,58.027,41.973,22.05,224,0.900,bicubic,-51.733,-40.933,+14
-tf_efficientnet_b2,42.197,57.803,58.203,41.797,9.11,260,0.890,bicubic,-52.003,-40.827,-9
+dpn98,42.277,57.723,56.927,43.073,61.57,224,0.875,bicubic,-51.653,-41.993,+27
+tf_efficientnet_cc_b1_8e,42.273,57.727,58.527,41.473,39.72,240,0.882,bicubic,-51.307,-40.163,+75
+xcit_tiny_24_p16_224,42.273,57.727,56.780,43.220,12.12,224,1.000,bicubic,-51.577,-42.040,+35
+convmixer_1024_20_ks9_p14,42.270,57.730,59.693,40.307,24.38,224,0.960,bicubic,-50.080,-38.727,+169
+deit_small_patch16_224,42.257,57.743,58.027,41.973,22.05,224,0.900,bicubic,-51.733,-40.933,+17
+tf_efficientnet_b2,42.197,57.803,58.203,41.797,9.11,260,0.890,bicubic,-52.003,-40.827,-6
 cait_xxs24_384,42.177,57.823,57.513,42.487,12.03,384,1.000,bicubic,-52.763,-41.617,-88
-gluon_resnext50_32x4d,42.100,57.900,57.690,42.310,25.03,224,0.875,bicubic,-51.570,-41.010,+51
-ecaresnet50d_pruned,41.993,58.007,58.323,41.677,19.94,224,0.875,bicubic,-51.827,-40.677,+29
-efficientnet_b2,41.937,58.063,58.300,41.700,9.11,288,1.000,bicubic,-52.433,-40.750,-31
-xcit_tiny_12_p16_224_dist,41.883,58.117,57.213,42.787,6.72,224,1.000,bicubic,-51.457,-41.537,+86
-gluon_senet154,41.700,58.300,56.480,43.520,115.09,224,0.875,bicubic,-53.000,-42.490,-71
-dla102x2,41.677,58.323,58.033,41.967,41.28,224,0.875,bilinear,-52.333,-40.997,+5
-inception_v4,41.647,58.353,55.367,44.633,42.68,299,0.875,bicubic,-52.723,-43.453,-34
-hrnet_w64,41.617,58.383,57.173,42.827,128.06,224,0.875,bilinear,-52.233,-41.697,+18
-haloregnetz_b,41.590,58.410,57.073,42.927,11.68,224,0.940,bicubic,-52.910,-41.887,-49
-tf_efficientnet_cc_b0_8e,41.533,58.467,57.393,42.607,24.01,224,0.875,bicubic,-51.317,-41.067,+117
+gluon_resnext50_32x4d,42.100,57.900,57.690,42.310,25.03,224,0.875,bicubic,-51.570,-41.010,+56
+ecaresnet50d_pruned,41.993,58.007,58.323,41.677,19.94,224,0.875,bicubic,-51.827,-40.677,+33
+efficientnet_b2,41.937,58.063,58.300,41.700,9.11,288,1.000,bicubic,-52.433,-40.750,-28
+xcit_tiny_12_p16_224_dist,41.883,58.117,57.213,42.787,6.72,224,1.000,bicubic,-51.457,-41.537,+91
+gluon_senet154,41.700,58.300,56.480,43.520,115.09,224,0.875,bicubic,-53.000,-42.760,-70
+dla102x2,41.677,58.323,58.033,41.967,41.28,224,0.875,bilinear,-52.333,-40.997,+8
+inception_v4,41.647,58.353,55.367,44.633,42.68,299,0.875,bicubic,-52.723,-43.453,-31
+hrnet_w64,41.617,58.383,57.173,42.827,128.06,224,0.875,bilinear,-52.233,-41.597,+24
+haloregnetz_b,41.590,58.410,57.073,42.927,11.68,224,0.940,bicubic,-52.910,-41.887,-46
+tf_efficientnet_cc_b0_8e,41.533,58.467,57.393,42.607,24.01,224,0.875,bicubic,-51.317,-41.067,+122
 efficientnet_el,41.503,58.497,58.317,41.683,10.59,300,0.904,bicubic,-53.167,-40.813,-72
-efficientnet_em,41.477,58.523,58.873,41.127,6.90,240,0.882,bicubic,-52.273,-40.047,+31
-resnetv2_50,41.447,58.553,56.750,43.250,25.55,224,0.950,bicubic,-52.843,-42.180,-32
-swin_tiny_patch4_window7_224,41.403,58.597,57.333,42.667,28.29,224,0.900,bicubic,-53.237,-41.787,-69
-cait_xxs24_224,41.387,58.613,57.523,42.477,11.96,224,1.000,bicubic,-52.103,-41.247,+61
-resnext50_32x4d,41.373,58.627,56.940,43.060,25.03,224,0.875,bicubic,-52.477,-41.990,+12
-tv_resnet152,41.320,58.680,57.587,42.413,60.19,224,0.875,bilinear,-51.940,-41.163,+79
-gernet_s,41.317,58.683,58.880,41.120,8.17,224,0.875,bilinear,-51.123,-39.610,+137
-xception71,41.300,58.700,55.940,44.060,42.34,299,0.903,bicubic,-52.600,-43.010,+2
-gcresnext50ts,41.270,58.730,57.090,42.910,15.67,256,0.900,bicubic,-53.140,-41.900,-53
-dpn92,41.263,58.737,56.313,43.687,37.67,224,0.875,bicubic,-52.917,-42.617,-30
-adv_inception_v3,41.220,58.780,56.357,43.643,23.83,299,0.875,bicubic,-51.770,-42.123,+92
-resnetblur50,41.073,58.927,57.080,42.920,25.56,224,0.875,bicubic,-52.637,-41.720,+25
-nf_regnet_b1,41.053,58.947,58.157,41.843,10.22,288,0.900,bicubic,-52.837,-40.593,-2
-gluon_resnet50_v1d,41.017,58.983,57.147,42.853,25.58,224,0.875,bicubic,-52.533,-41.563,+46
-ese_vovnet39b,40.883,59.117,57.023,42.977,24.57,224,0.875,bicubic,-52.967,-41.797,+3
-gluon_inception_v3,40.880,59.120,55.670,44.330,23.83,299,0.875,bicubic,-52.710,-43.170,+37
-resnet34d,40.853,59.147,56.527,43.473,21.82,224,0.875,bicubic,-51.787,-41.913,+114
-regnety_320,40.837,59.163,56.173,43.827,145.05,224,0.875,bicubic,-53.663,-42.997,-68
-levit_192,40.800,59.200,56.663,43.337,10.95,224,0.900,bicubic,-52.910,-42.127,+17
-xception,40.793,59.207,56.507,43.493,22.86,299,0.897,bicubic,-52.857,-42.263,+26
-gluon_resnet101_v1b,40.703,59.297,56.193,43.807,44.55,224,0.875,bicubic,-53.067,-42.527,+7
-skresnext50_32x4d,40.690,59.310,56.017,43.983,27.48,224,0.875,bicubic,-53.260,-42.453,-19
-repvgg_b1,40.683,59.317,57.830,42.170,57.42,224,0.875,bilinear,-52.727,-40.950,+53
-hrnet_w40,40.660,59.340,56.860,43.140,57.56,224,0.875,bilinear,-53.050,-41.940,+11
-resmlp_24_224,40.660,59.340,56.597,43.403,30.02,224,0.875,bicubic,-52.770,-42.213,+47
-tf_efficientnet_lite3,40.613,59.387,56.573,43.427,8.20,300,0.904,bilinear,-53.497,-42.387,-37
-regnetx_320,40.533,59.467,55.667,44.333,107.81,224,0.875,bicubic,-53.677,-43.383,-49
-xcit_tiny_12_p8_224,40.533,59.467,55.583,44.417,6.71,224,1.000,bicubic,-53.837,-43.487,-65
-repvgg_b2,40.523,59.477,57.790,42.210,89.02,224,0.875,bilinear,-53.047,-41.280,+28
+efficientnet_em,41.477,58.523,58.873,41.127,6.90,240,0.882,bicubic,-52.273,-40.047,+34
+resnetv2_50,41.447,58.553,56.750,43.250,25.55,224,0.950,bicubic,-52.843,-42.450,-30
+swin_tiny_patch4_window7_224,41.403,58.597,57.333,42.667,28.29,224,0.900,bicubic,-53.237,-41.787,-70
+cait_xxs24_224,41.387,58.613,57.523,42.477,11.96,224,1.000,bicubic,-52.103,-41.247,+64
+resnext50_32x4d,41.373,58.627,56.940,43.060,25.03,224,0.875,bicubic,-52.477,-41.960,+13
+tv_resnet152,41.320,58.680,57.587,42.413,60.19,224,0.875,bilinear,-51.940,-41.163,+84
+gernet_s,41.317,58.683,58.880,41.120,8.17,224,0.875,bilinear,-51.123,-39.610,+142
+xception71,41.300,58.700,55.940,44.060,42.34,299,0.903,bicubic,-52.600,-43.010,+3
+gcresnext50ts,41.270,58.730,57.090,42.910,15.67,256,0.900,bicubic,-53.140,-41.900,-50
+dpn92,41.263,58.737,56.313,43.687,37.67,224,0.875,bicubic,-52.917,-42.617,-25
+adv_inception_v3,41.220,58.780,56.357,43.643,23.83,299,0.875,bicubic,-51.770,-42.123,+97
+resnetblur50,41.073,58.927,57.080,42.920,25.56,224,0.875,bicubic,-52.637,-41.720,+28
+nf_regnet_b1,41.053,58.947,58.157,41.843,10.22,288,0.900,bicubic,-52.837,-40.593,+2
+gluon_resnet50_v1d,41.017,58.983,57.147,42.853,25.58,224,0.875,bicubic,-52.533,-41.563,+49
+ese_vovnet39b,40.883,59.117,57.023,42.977,24.57,224,0.875,bicubic,-52.967,-41.847,+7
+gluon_inception_v3,40.880,59.120,55.670,44.330,23.83,299,0.875,bicubic,-52.710,-43.170,+41
+resnet34d,40.853,59.147,56.527,43.473,21.82,224,0.875,bicubic,-51.787,-41.913,+119
+regnety_320,40.837,59.163,56.173,43.827,145.05,224,0.875,bicubic,-53.663,-42.997,-67
+levit_192,40.800,59.200,56.663,43.337,10.95,224,0.900,bicubic,-52.910,-42.127,+20
+xception,40.793,59.207,56.507,43.493,22.86,299,0.897,bicubic,-52.857,-42.263,+28
+gluon_resnet101_v1b,40.703,59.297,56.193,43.807,44.55,224,0.875,bicubic,-53.067,-42.527,+10
+skresnext50_32x4d,40.690,59.310,56.017,43.983,27.48,224,0.875,bicubic,-53.260,-42.453,-15
+repvgg_b1,40.683,59.317,57.830,42.170,57.42,224,0.875,bilinear,-52.727,-40.950,+57
+hrnet_w40,40.660,59.340,56.860,43.140,57.56,224,0.875,bilinear,-53.050,-41.940,+14
+resmlp_24_224,40.660,59.340,56.597,43.403,30.02,224,0.875,bicubic,-52.770,-42.213,+51
+tf_efficientnet_lite3,40.613,59.387,56.573,43.427,8.20,300,0.904,bilinear,-53.497,-42.387,-34
+regnetx_320,40.533,59.467,55.667,44.333,107.81,224,0.875,bicubic,-53.677,-43.383,-46
+xcit_tiny_12_p8_224,40.533,59.467,55.583,44.417,6.71,224,1.000,bicubic,-53.837,-43.487,-62
+repvgg_b2,40.523,59.477,57.790,42.210,89.02,224,0.875,bilinear,-53.047,-41.280,+31
 tresnet_m_448,40.520,59.480,56.673,43.327,31.39,448,0.875,bilinear,-54.150,-42.497,-100
-pit_xs_224,40.513,59.487,56.543,43.457,10.62,224,0.900,bicubic,-52.387,-42.247,+81
-dla169,40.507,59.493,57.320,42.680,53.39,224,0.875,bilinear,-53.273,-41.510,-6
-wide_resnet101_2,40.477,59.523,55.863,44.137,126.89,224,0.875,bilinear,-53.243,-42.947,+1
-efficientnet_b2_pruned,40.457,59.543,56.603,43.397,8.31,260,0.890,bicubic,-53.343,-42.307,-11
-resnet50,40.397,59.603,54.667,45.333,25.56,224,0.950,bicubic,-53.553,-44.163,-31
-skresnet34,40.373,59.627,56.793,43.207,22.28,224,0.875,bicubic,-52.187,-41.717,+102
-tf_efficientnet_b0_ap,40.357,59.643,56.823,43.177,5.29,224,0.875,bicubic,-52.243,-41.607,+96
-regnetx_160,40.350,59.650,56.090,43.910,54.28,224,0.875,bicubic,-53.550,-42.990,-30
-legacy_seresnext101_32x4d,40.323,59.677,54.843,45.157,48.96,224,0.875,bilinear,-53.847,-44.127,-55
-xception65,40.320,59.680,55.263,44.737,39.92,299,0.903,bicubic,-53.420,-43.607,-7
+pit_xs_224,40.513,59.487,56.543,43.457,10.62,224,0.900,bicubic,-52.387,-42.247,+85
+dla169,40.507,59.493,57.320,42.680,53.39,224,0.875,bilinear,-53.273,-41.510,-3
+wide_resnet101_2,40.477,59.523,55.863,44.137,126.89,224,0.875,bilinear,-53.243,-42.947,+4
+efficientnet_b2_pruned,40.457,59.543,56.603,43.397,8.31,260,0.890,bicubic,-53.343,-42.307,-7
+resnet50,40.397,59.603,54.667,45.333,25.56,224,0.950,bicubic,-53.553,-44.163,-29
+skresnet34,40.373,59.627,56.793,43.207,22.28,224,0.875,bicubic,-52.187,-41.717,+107
+tf_efficientnet_b0_ap,40.357,59.643,56.823,43.177,5.29,224,0.875,bicubic,-52.243,-41.547,+101
+regnetx_160,40.350,59.650,56.090,43.910,54.28,224,0.875,bicubic,-53.550,-42.990,-25
+legacy_seresnext101_32x4d,40.323,59.677,54.843,45.157,48.96,224,0.875,bilinear,-53.847,-44.127,-52
+xception65,40.320,59.680,55.263,44.737,39.92,299,0.903,bicubic,-53.420,-43.607,-4
 coat_mini,40.310,59.690,55.153,44.847,10.34,224,0.900,bicubic,-54.450,-43.797,-124
-densenet201,40.297,59.703,56.770,43.230,20.01,224,0.875,bicubic,-52.393,-41.890,+83
-efficientnet_el_pruned,40.293,59.707,56.750,43.250,10.59,300,0.904,bicubic,-53.767,-42.270,-50
-coat_lite_mini,40.280,59.720,55.670,44.330,11.01,224,0.900,bicubic,-53.210,-43.110,+22
-eca_resnet33ts,40.193,59.807,56.963,43.037,19.68,256,0.900,bicubic,-53.677,-41.927,-31
-hrnet_w48,40.160,59.840,56.597,43.403,77.47,224,0.875,bilinear,-53.870,-42.433,-49
-resnext50d_32x4d,40.150,59.850,55.593,44.407,25.05,224,0.875,bicubic,-53.650,-43.137,-23
-vit_base_patch16_sam_224,40.133,59.867,55.530,44.470,86.57,224,0.900,bicubic,-53.757,-43.360,-36
-legacy_seresnet152,40.053,59.947,55.887,44.113,66.82,224,0.875,bilinear,-53.407,-42.963,+20
-tf_efficientnet_b1,40.043,59.957,56.213,43.787,7.79,240,0.882,bicubic,-53.667,-42.587,-12
-hrnet_w30,40.013,59.987,57.123,42.877,37.71,224,0.875,bilinear,-53.397,-41.707,+23
-regnetz_b,39.990,60.010,55.657,44.343,9.72,288,0.940,bicubic,-54.700,-43.503,-126
-halonet50ts,39.967,60.033,54.103,45.897,22.73,256,0.940,bicubic,-54.673,-44.797,-120
-regnetx_080,39.967,60.033,56.057,43.943,39.57,224,0.875,bicubic,-53.823,-42.843,-29
-gluon_resnet101_v1c,39.953,60.047,55.253,44.747,44.57,224,0.875,bicubic,-53.707,-43.507,-11
-resmlp_12_distilled_224,39.880,60.120,57.473,42.527,15.35,224,0.875,bicubic,-52.990,-41.157,+59
-seresnet33ts,39.813,60.187,56.503,43.497,19.78,256,0.900,bicubic,-54.447,-42.277,-83
-tf_efficientnetv2_b0,39.800,60.200,56.297,43.703,7.14,224,0.875,bicubic,-53.260,-42.403,+37
-res2net50_26w_8s,39.747,60.253,54.947,45.053,48.40,224,0.875,bilinear,-53.683,-43.723,+12
-vit_small_patch32_224,39.747,60.253,55.283,44.717,22.88,224,0.900,bicubic,-52.403,-43.227,+100
-res2net101_26w_4s,39.723,60.277,54.613,45.387,45.21,224,0.875,bilinear,-53.797,-44.017,0
-regnetx_120,39.707,60.293,55.693,44.307,46.11,224,0.875,bicubic,-54.583,-43.507,-93
-hrnet_w44,39.660,60.340,55.313,44.687,67.06,224,0.875,bilinear,-53.960,-43.637,-15
-xception41,39.660,60.340,54.977,45.023,26.97,299,0.903,bicubic,-53.820,-43.863,+3
-sehalonet33ts,39.640,60.360,53.967,46.033,13.69,256,0.940,bicubic,-54.890,-44.813,-117
-resmlp_big_24_224,39.610,60.390,54.767,45.233,129.14,224,0.875,bicubic,-54.660,-44.053,-94
-tf_efficientnetv2_b1,39.607,60.393,55.490,44.510,8.14,240,0.882,bicubic,-54.093,-43.320,-28
-dla102x,39.593,60.407,56.337,43.663,26.31,224,0.875,bilinear,-53.917,-42.513,-6
-densenet161,39.590,60.410,56.180,43.820,28.68,224,0.875,bicubic,-53.290,-42.630,+44
-mixnet_xl,39.553,60.447,55.827,44.173,11.90,224,0.875,bicubic,-54.667,-42.983,-95
-hrnet_w32,39.523,60.477,56.267,43.733,41.23,224,0.875,bilinear,-53.427,-42.573,+36
+densenet201,40.297,59.703,56.770,43.230,20.01,224,0.875,bicubic,-52.393,-41.890,+89
+efficientnet_el_pruned,40.293,59.707,56.750,43.250,10.59,300,0.904,bicubic,-53.767,-42.270,-45
+coat_lite_mini,40.280,59.720,55.670,44.330,11.01,224,0.900,bicubic,-53.210,-43.110,+25
+eca_resnet33ts,40.193,59.807,56.963,43.037,19.68,256,0.900,bicubic,-53.677,-41.927,-28
+hrnet_w48,40.160,59.840,56.597,43.403,77.47,224,0.875,bilinear,-53.870,-42.433,-45
+resnext50d_32x4d,40.150,59.850,55.593,44.407,25.05,224,0.875,bicubic,-53.650,-43.137,-21
+vit_base_patch16_sam_224,40.133,59.867,55.530,44.470,86.57,224,0.900,bicubic,-53.757,-43.360,-34
+halonet50ts,40.113,59.887,54.453,45.547,22.73,256,0.940,bicubic,-54.307,-44.307,-91
+legacy_seresnet152,40.053,59.947,55.887,44.113,66.82,224,0.875,bilinear,-53.407,-42.963,+22
+tf_efficientnet_b1,40.043,59.957,56.213,43.787,7.79,240,0.882,bicubic,-53.667,-42.587,-10
+hrnet_w30,40.013,59.987,57.123,42.877,37.71,224,0.875,bilinear,-53.397,-41.707,+26
+regnetz_b,39.990,60.010,55.657,44.343,9.72,288,0.940,bicubic,-54.700,-43.503,-127
+regnetx_080,39.967,60.033,56.057,43.943,39.57,224,0.875,bicubic,-53.823,-42.843,-26
+gluon_resnet101_v1c,39.953,60.047,55.253,44.747,44.57,224,0.875,bicubic,-53.707,-43.507,-8
+resmlp_12_distilled_224,39.880,60.120,57.473,42.527,15.35,224,0.875,bicubic,-52.990,-41.157,+64
+seresnet33ts,39.813,60.187,56.503,43.497,19.78,256,0.900,bicubic,-54.447,-42.277,-80
+tf_efficientnetv2_b0,39.800,60.200,56.297,43.703,7.14,224,0.875,bicubic,-53.260,-42.403,+42
+res2net50_26w_8s,39.747,60.253,54.947,45.053,48.40,224,0.875,bilinear,-53.683,-43.723,+16
+vit_small_patch32_224,39.747,60.253,55.283,44.717,22.88,224,0.900,bicubic,-52.403,-43.227,+105
+lambda_resnet50ts,39.723,60.277,54.367,45.633,21.54,256,0.950,bicubic,-54.837,-44.283,-117
+res2net101_26w_4s,39.723,60.277,54.613,45.387,45.21,224,0.875,bilinear,-53.797,-44.017,+2
+regnetx_120,39.707,60.293,55.693,44.307,46.11,224,0.875,bicubic,-54.583,-43.237,-90
+hrnet_w44,39.660,60.340,55.313,44.687,67.06,224,0.875,bilinear,-53.960,-43.637,-13
+xception41,39.660,60.340,54.977,45.023,26.97,299,0.903,bicubic,-53.820,-43.863,+6
+sehalonet33ts,39.640,60.360,53.967,46.033,13.69,256,0.940,bicubic,-54.890,-44.813,-116
+resmlp_big_24_224,39.610,60.390,54.767,45.233,129.14,224,0.875,bicubic,-54.660,-44.053,-91
+tf_efficientnetv2_b1,39.607,60.393,55.490,44.510,8.14,240,0.882,bicubic,-54.093,-43.320,-26
+dla102x,39.593,60.407,56.337,43.663,26.31,224,0.875,bilinear,-53.917,-42.513,-4
+densenet161,39.590,60.410,56.180,43.820,28.68,224,0.875,bicubic,-53.290,-42.480,+49
+mixnet_xl,39.553,60.447,55.827,44.173,11.90,224,0.875,bicubic,-54.667,-42.983,-93
+hrnet_w32,39.523,60.477,56.267,43.733,41.23,224,0.875,bilinear,-53.427,-42.573,+40
+lamhalobotnet50ts_256,39.517,60.483,53.860,46.140,22.57,256,0.950,bicubic,-55.093,-44.750,-137
 gcresnet33ts,39.507,60.493,55.863,44.137,19.88,256,0.900,bicubic,-54.313,-43.067,-51
+xcit_tiny_12_p16_224,39.477,60.523,55.023,44.977,6.72,224,1.000,bicubic,-52.983,-43.607,+73
 rexnet_130,39.477,60.523,56.633,43.367,7.56,224,0.875,bicubic,-54.213,-42.087,-33
-xcit_tiny_12_p16_224,39.477,60.523,55.023,44.977,6.72,224,1.000,bicubic,-52.983,-43.607,+69
-levit_128,39.453,60.547,55.460,44.540,9.21,224,0.900,bicubic,-53.587,-43.230,+22
-resnetv2_50x1_bitm,39.407,60.593,57.873,42.127,25.55,448,1.000,bilinear,-55.353,-41.307,-158
-regnety_064,39.390,60.610,55.817,44.183,30.58,224,0.875,bicubic,-54.750,-42.973,-91
+levit_128,39.453,60.547,55.460,44.540,9.21,224,0.900,bicubic,-53.587,-43.360,+25
+resnetv2_50x1_bitm,39.407,60.593,57.873,42.127,25.55,448,1.000,bilinear,-55.353,-41.307,-160
+regnety_064,39.390,60.610,55.817,44.183,30.58,224,0.875,bicubic,-54.750,-43.133,-91
 regnety_120,39.377,60.623,55.347,44.653,51.82,224,0.875,bicubic,-54.683,-43.673,-84
-tf_efficientnet_el,39.353,60.647,55.443,44.557,10.59,300,0.904,bicubic,-54.997,-43.647,-115
-tf_inception_v3,39.353,60.647,54.373,45.627,23.83,299,0.875,bicubic,-53.857,-44.117,+9
-densenetblur121d,39.310,60.690,56.650,43.350,8.00,224,0.875,bicubic,-53.090,-41.820,+68
-gluon_resnet50_v1s,39.283,60.717,55.100,44.900,25.68,224,0.875,bicubic,-54.307,-43.730,-28
-tv_resnet101,39.273,60.727,55.833,44.167,44.55,224,0.875,bilinear,-53.607,-42.827,+31
-tf_efficientnetv2_b2,39.190,60.810,54.620,45.380,10.10,260,0.890,bicubic,-54.870,-44.320,-89
-densenet169,39.177,60.823,55.850,44.150,14.15,224,0.875,bicubic,-53.113,-42.740,+68
-legacy_seresnet101,39.123,60.877,55.100,44.900,49.33,224,0.875,bilinear,-54.167,-43.650,-5
-repvgg_b1g4,39.000,61.000,56.433,43.567,39.97,224,0.875,bilinear,-54.040,-42.387,+11
+tf_efficientnet_el,39.353,60.647,55.443,44.557,10.59,300,0.904,bicubic,-54.997,-43.647,-114
+tf_inception_v3,39.353,60.647,54.373,45.627,23.83,299,0.875,bicubic,-53.857,-44.117,+11
+halo2botnet50ts_256,39.313,60.687,53.643,46.357,22.64,256,0.950,bicubic,-55.237,-45.117,-136
+densenetblur121d,39.310,60.690,56.650,43.350,8.00,224,0.875,bicubic,-53.090,-41.820,+70
+gluon_resnet50_v1s,39.283,60.717,55.100,44.900,25.68,224,0.875,bicubic,-54.307,-43.730,-29
+tv_resnet101,39.273,60.727,55.833,44.167,44.55,224,0.875,bilinear,-53.607,-42.977,+32
+tf_efficientnetv2_b2,39.190,60.810,54.620,45.380,10.10,260,0.890,bicubic,-54.870,-44.320,-90
+densenet169,39.177,60.823,55.850,44.150,14.15,224,0.875,bicubic,-53.113,-42.740,+70
+legacy_seresnet101,39.123,60.877,55.100,44.900,49.33,224,0.875,bilinear,-54.167,-43.650,-3
+repvgg_b1g4,39.000,61.000,56.433,43.567,39.97,224,0.875,bilinear,-54.040,-42.257,+13
 regnety_080,38.973,61.027,55.193,44.807,39.18,224,0.875,bicubic,-54.927,-43.797,-79
-dpn68,38.967,61.033,54.977,45.023,12.61,224,0.875,bicubic,-53.293,-43.623,+65
-efficientnet_b1_pruned,38.967,61.033,55.607,44.393,6.33,240,0.882,bicubic,-53.993,-42.913,+15
-inception_v3,38.953,61.047,53.850,46.150,23.83,299,0.875,bicubic,-53.947,-44.470,+20
-crossvit_9_dagger_240,38.947,61.053,54.913,45.087,8.78,240,0.875,bicubic,-53.803,-43.597,+31
-legacy_seresnext50_32x4d,38.897,61.103,54.637,45.363,27.56,224,0.875,bilinear,-54.513,-44.163,-18
+dpn68,38.967,61.033,54.977,45.023,12.61,224,0.875,bicubic,-53.293,-43.623,+68
+efficientnet_b1_pruned,38.967,61.033,55.607,44.393,6.33,240,0.882,bicubic,-53.993,-42.913,+18
+inception_v3,38.953,61.047,53.850,46.150,23.83,299,0.875,bicubic,-53.947,-44.470,+23
+crossvit_9_dagger_240,38.947,61.053,54.913,45.087,8.78,240,0.875,bicubic,-53.803,-43.597,+34
+legacy_seresnext50_32x4d,38.897,61.103,54.637,45.363,27.56,224,0.875,bilinear,-54.513,-44.163,-17
 resnet33ts,38.890,61.110,55.550,44.450,19.68,256,0.900,bicubic,-54.730,-43.220,-45
-dla102,38.883,61.117,55.333,44.667,33.27,224,0.875,bilinear,-54.407,-43.447,-15
-regnety_040,38.833,61.167,55.600,44.400,20.65,224,0.875,bicubic,-54.777,-43.040,-46
-regnetx_040,38.803,61.197,55.493,44.507,22.12,224,0.875,bicubic,-54.867,-43.457,-55
+dla102,38.883,61.117,55.333,44.667,33.27,224,0.875,bilinear,-54.407,-43.377,-13
+regnety_040,38.833,61.167,55.600,44.400,20.65,224,0.875,bicubic,-54.777,-43.040,-45
+regnetx_040,38.803,61.197,55.493,44.507,22.12,224,0.875,bicubic,-54.867,-43.457,-56
 resnet32ts,38.767,61.233,55.847,44.153,17.96,256,0.900,bicubic,-54.803,-42.903,-40
-regnetx_032,38.760,61.240,55.160,44.840,15.30,224,0.875,bicubic,-54.510,-43.580,-16
-densenet121,38.753,61.247,56.250,43.750,7.98,224,0.875,bicubic,-53.187,-42.030,+68
-res2net50_14w_8s,38.720,61.280,54.197,45.803,25.06,224,0.875,bilinear,-54.300,-44.513,-1
-dla60_res2net,38.687,61.313,54.613,45.387,20.85,224,0.875,bilinear,-54.693,-44.217,-24
+regnetx_032,38.760,61.240,55.160,44.840,15.30,224,0.875,bicubic,-54.510,-43.580,-14
+densenet121,38.753,61.247,56.250,43.750,7.98,224,0.875,bicubic,-53.187,-42.030,+70
+res2net50_14w_8s,38.720,61.280,54.197,45.803,25.06,224,0.875,bilinear,-54.300,-44.503,+2
+dla60_res2net,38.687,61.313,54.613,45.387,20.85,224,0.875,bilinear,-54.693,-44.217,-23
 res2net50_26w_6s,38.660,61.340,53.810,46.190,37.05,224,0.875,bilinear,-54.920,-44.930,-48
-selecsls60,38.623,61.377,55.693,44.307,30.67,224,0.875,bicubic,-54.377,-43.137,-2
-dla60x,38.617,61.383,55.500,44.500,17.35,224,0.875,bilinear,-54.593,-43.220,-17
-selecsls60b,38.573,61.427,55.327,44.673,32.77,224,0.875,bicubic,-54.907,-43.433,-38
-tf_efficientnet_b0,38.550,61.450,56.083,43.917,5.29,224,0.875,bicubic,-53.850,-42.337,+41
+selecsls60,38.623,61.377,55.693,44.307,30.67,224,0.875,bicubic,-54.377,-43.137,0
+dla60x,38.617,61.383,55.500,44.500,17.35,224,0.875,bilinear,-54.593,-43.220,-14
+selecsls60b,38.573,61.427,55.327,44.673,32.77,224,0.875,bicubic,-54.907,-43.433,-39
+tf_efficientnet_b0,38.550,61.450,56.083,43.917,5.29,224,0.875,bicubic,-53.850,-42.337,+43
 dla60_res2next,38.530,61.470,55.003,44.997,17.03,224,0.875,bilinear,-55.030,-43.797,-49
-hardcorenas_f,38.507,61.493,55.743,44.257,8.20,224,0.875,bilinear,-54.473,-42.877,-5
-repvgg_a2,38.507,61.493,55.827,44.173,28.21,224,0.875,bilinear,-54.153,-42.703,+20
-regnetx_064,38.493,61.507,55.027,44.973,26.21,224,0.875,bicubic,-55.157,-44.023,-66
-gluon_resnet50_v1b,38.457,61.543,54.897,45.103,25.56,224,0.875,bicubic,-54.093,-43.653,+27
-resmlp_12_224,38.453,61.547,56.387,43.613,15.35,224,0.875,bicubic,-53.677,-42.183,+48
-tf_efficientnet_cc_b0_4e,38.427,61.573,55.200,44.800,13.31,224,0.875,bicubic,-54.413,-43.240,+4
-hrnet_w18,38.380,61.620,55.750,44.250,21.30,224,0.875,bilinear,-54.370,-42.900,+9
-mixnet_l,38.233,61.767,54.857,45.143,7.33,224,0.875,bicubic,-55.057,-43.853,-34
-hardcorenas_e,38.130,61.870,55.193,44.807,8.07,224,0.875,bilinear,-54.830,-43.377,-11
-efficientnet_b1,38.107,61.893,54.090,45.910,7.79,256,1.000,bicubic,-54.913,-44.610,-17
-coat_lite_tiny,38.080,61.920,53.467,46.533,5.72,224,0.900,bicubic,-54.750,-45.173,0
-eca_halonext26ts,38.067,61.933,54.167,45.833,10.76,256,0.940,bicubic,-55.073,-44.523,-28
-gmixer_24_224,37.977,62.023,52.117,47.883,24.72,224,0.875,bicubic,-54.693,-46.143,+7
-resnetrs50,37.907,62.093,53.320,46.680,35.69,224,0.910,bicubic,-56.123,-45.510,-124
-hardcorenas_c,37.887,62.113,55.720,44.280,5.52,224,0.875,bilinear,-54.443,-42.620,+28
-gluon_resnet50_v1c,37.867,62.133,54.150,45.850,25.58,224,0.875,bicubic,-55.053,-44.560,-15
-efficientnet_es,37.837,62.163,54.987,45.013,5.44,224,0.875,bicubic,-55.103,-43.703,-17
-res2net50_26w_4s,37.820,62.180,53.113,46.887,25.70,224,0.875,bilinear,-55.360,-45.557,-35
-resnest14d,37.790,62.210,56.570,43.430,10.61,224,0.875,bilinear,-53.360,-41.780,+68
-tv_resnext50_32x4d,37.783,62.217,54.153,45.847,25.03,224,0.875,bilinear,-55.127,-44.577,-18
-resnet26t,37.753,62.247,55.300,44.700,16.01,256,0.940,bicubic,-54.927,-43.300,-2
-ecaresnet26t,37.597,62.403,54.353,45.647,16.01,320,0.950,bicubic,-56.333,-44.577,-123
-hardcorenas_d,37.550,62.450,54.723,45.277,7.50,224,0.875,bilinear,-55.050,-43.647,+3
-res2next50,37.537,62.463,52.883,47.117,24.67,224,0.875,bilinear,-55.573,-45.777,-39
-resnet34,37.497,62.503,54.327,45.673,21.80,224,0.875,bilinear,-53.693,-43.903,+60
-lambda_resnet26t,37.370,62.630,53.550,46.450,10.96,256,0.940,bicubic,-56.030,-45.210,-57
-pit_ti_distilled_224,37.320,62.680,55.183,44.817,5.10,224,0.900,bicubic,-53.580,-43.047,+68
-hardcorenas_b,37.280,62.720,55.040,44.960,5.18,224,0.875,bilinear,-54.690,-43.360,+31
-mobilenetv3_large_100_miil,37.247,62.753,53.560,46.440,5.48,224,0.875,bilinear,-55.003,-44.690,+19
-regnety_016,37.143,62.857,54.147,45.853,11.20,224,0.875,bicubic,-55.887,-44.543,-39
-res2net50_48w_2s,37.143,62.857,53.410,46.590,25.29,224,0.875,bilinear,-55.657,-45.060,-19
+repvgg_a2,38.507,61.493,55.827,44.173,28.21,224,0.875,bilinear,-54.153,-42.703,+23
+hardcorenas_f,38.507,61.493,55.743,44.257,8.20,224,0.875,bilinear,-54.473,-42.877,-4
+regnetx_064,38.493,61.507,55.027,44.973,26.21,224,0.875,bicubic,-55.157,-44.023,-65
+gluon_resnet50_v1b,38.457,61.543,54.897,45.103,25.56,224,0.875,bicubic,-54.093,-43.653,+29
+resmlp_12_224,38.453,61.547,56.387,43.613,15.35,224,0.875,bicubic,-53.677,-42.183,+50
+tf_efficientnet_cc_b0_4e,38.427,61.573,55.200,44.800,13.31,224,0.875,bicubic,-54.413,-43.240,+6
+hrnet_w18,38.380,61.620,55.750,44.250,21.30,224,0.875,bilinear,-54.370,-42.900,+10
+mixnet_l,38.233,61.767,54.857,45.143,7.33,224,0.875,bicubic,-55.057,-43.923,-32
+hardcorenas_e,38.130,61.870,55.193,44.807,8.07,224,0.875,bilinear,-54.830,-43.377,-10
+efficientnet_b1,38.107,61.893,54.090,45.910,7.79,256,1.000,bicubic,-54.913,-44.620,-16
+coat_lite_tiny,38.080,61.920,53.467,46.533,5.72,224,0.900,bicubic,-54.750,-45.173,+2
+eca_halonext26ts,38.067,61.933,54.167,45.833,10.76,256,0.940,bicubic,-55.073,-44.523,-26
+gmixer_24_224,37.977,62.023,52.117,47.883,24.72,224,0.875,bicubic,-54.693,-46.143,+9
+resnetrs50,37.907,62.093,53.320,46.680,35.69,224,0.910,bicubic,-56.123,-45.510,-125
+hardcorenas_c,37.887,62.113,55.720,44.280,5.52,224,0.875,bilinear,-54.443,-42.620,+30
+gluon_resnet50_v1c,37.867,62.133,54.150,45.850,25.58,224,0.875,bicubic,-55.053,-44.560,-13
+efficientnet_es,37.837,62.163,54.987,45.013,5.44,224,0.875,bicubic,-55.103,-43.703,-15
+res2net50_26w_4s,37.820,62.180,53.113,46.887,25.70,224,0.875,bilinear,-55.360,-45.557,-33
+resnest14d,37.790,62.210,56.570,43.430,10.61,224,0.875,bilinear,-53.360,-41.780,+70
+tv_resnext50_32x4d,37.783,62.217,54.153,45.847,25.03,224,0.875,bilinear,-55.127,-44.577,-16
+resnet26t,37.753,62.247,55.300,44.700,16.01,256,0.940,bicubic,-54.927,-43.300,0
+ecaresnet26t,37.597,62.403,54.353,45.647,16.01,320,0.950,bicubic,-56.333,-44.577,-124
+hardcorenas_d,37.550,62.450,54.723,45.277,7.50,224,0.875,bilinear,-55.050,-43.707,+5
+res2next50,37.537,62.463,52.883,47.117,24.67,224,0.875,bilinear,-55.573,-45.777,-37
+resnet34,37.497,62.503,54.327,45.673,21.80,224,0.875,bilinear,-53.693,-43.903,+61
+lambda_resnet26t,37.370,62.630,53.550,46.450,10.96,256,0.940,bicubic,-56.030,-45.210,-56
+pit_ti_distilled_224,37.320,62.680,55.183,44.817,5.10,224,0.900,bicubic,-53.580,-43.047,+70
+hardcorenas_b,37.280,62.720,55.040,44.960,5.18,224,0.875,bilinear,-54.690,-43.360,+33
+mobilenetv3_large_100_miil,37.247,62.753,53.560,46.440,5.48,224,0.875,bilinear,-55.003,-44.690,+22
+regnety_016,37.143,62.857,54.147,45.853,11.20,224,0.875,bicubic,-55.887,-44.543,-37
+res2net50_48w_2s,37.143,62.857,53.410,46.590,25.29,224,0.875,bilinear,-55.657,-45.060,-17
 lambda_resnet26rpt_256,37.113,62.887,53.843,46.157,10.99,256,0.940,bicubic,-56.327,-45.037,-70
-dla60,37.110,62.890,54.297,45.703,22.04,224,0.875,bilinear,-55.580,-44.333,-15
-bat_resnext26ts,37.090,62.910,53.750,46.250,10.73,256,0.900,bicubic,-56.010,-44.970,-48
-rexnet_100,37.060,62.940,54.070,45.930,4.80,224,0.875,bicubic,-55.780,-44.550,-26
-tf_mixnet_l,37.040,62.960,52.710,47.290,7.33,224,0.875,bicubic,-56.010,-45.830,-48
-legacy_seresnet50,36.933,63.067,53.517,46.483,28.09,224,0.875,bilinear,-55.737,-45.143,-16
-tf_efficientnet_lite2,36.890,63.110,53.367,46.633,6.09,260,0.890,bicubic,-55.680,-45.183,-10
-halonet26t,36.783,63.217,52.267,47.733,12.48,256,0.950,bicubic,-56.827,-46.693,-96
-regnetx_016,36.767,63.233,53.293,46.707,9.19,224,0.875,bicubic,-55.793,-45.257,-11
-tv_densenet121,36.747,63.253,54.000,46.000,7.98,224,0.875,bicubic,-54.653,-44.250,+36
-mobilenetv2_120d,36.717,63.283,53.967,46.033,5.83,224,0.875,bicubic,-55.893,-44.543,-18
-hardcorenas_a,36.707,63.293,54.923,45.077,5.26,224,0.875,bilinear,-54.903,-43.247,+26
+dla60,37.110,62.890,54.297,45.703,22.04,224,0.875,bilinear,-55.580,-44.333,-14
+bat_resnext26ts,37.090,62.910,53.750,46.250,10.73,256,0.900,bicubic,-56.010,-44.970,-46
+rexnet_100,37.060,62.940,54.070,45.930,4.80,224,0.875,bicubic,-55.780,-44.550,-24
+tf_mixnet_l,37.040,62.960,52.710,47.290,7.33,224,0.875,bicubic,-56.010,-45.830,-46
+botnet26t_256,36.963,63.037,53.070,46.930,12.49,256,0.950,bicubic,-56.477,-45.590,-74
+legacy_seresnet50,36.933,63.067,53.517,46.483,28.09,224,0.875,bilinear,-55.737,-45.143,-15
+tf_efficientnet_lite2,36.890,63.110,53.367,46.633,6.09,260,0.890,bicubic,-55.680,-45.183,-9
+halonet26t,36.783,63.217,52.267,47.733,12.48,256,0.950,bicubic,-56.827,-46.693,-98
+regnetx_016,36.767,63.233,53.293,46.707,9.19,224,0.875,bicubic,-55.793,-45.257,-10
+tv_densenet121,36.747,63.253,54.000,46.000,7.98,224,0.875,bicubic,-54.653,-44.250,+37
+mobilenetv2_120d,36.717,63.283,53.967,46.033,5.83,224,0.875,bicubic,-55.893,-44.543,-17
+hardcorenas_a,36.707,63.293,54.923,45.077,5.26,224,0.875,bilinear,-54.903,-43.247,+27
+eca_botnext26ts_256,36.673,63.327,52.493,47.507,10.59,256,0.950,bicubic,-56.687,-46.197,-73
 tf_efficientnet_lite1,36.667,63.333,53.687,46.313,5.42,240,0.882,bicubic,-55.653,-44.803,0
-efficientnet_b0,36.603,63.397,53.490,46.510,5.29,224,0.875,bicubic,-55.867,-45.190,-12
-levit_128s,36.593,63.407,53.083,46.917,7.78,224,0.900,bicubic,-54.907,-45.317,+26
+efficientnet_b0,36.603,63.397,53.490,46.510,5.29,224,0.875,bicubic,-55.867,-45.190,-11
 vit_base_patch32_sam_224,36.593,63.407,53.087,46.913,88.22,224,0.900,bicubic,-53.277,-44.513,+65
+levit_128s,36.593,63.407,53.083,46.917,7.78,224,0.900,bicubic,-54.907,-45.317,+25
 xcit_nano_12_p8_224_dist,36.503,63.497,52.780,47.220,3.05,224,1.000,bicubic,-55.907,-45.730,-9
 tf_efficientnet_em,36.450,63.550,52.860,47.140,6.90,240,0.882,bicubic,-56.750,-45.820,-67
-skresnet18,36.343,63.657,54.267,45.733,11.96,224,0.875,bicubic,-53.827,-43.513,+59
+skresnet18,36.343,63.657,54.267,45.733,11.96,224,0.875,bicubic,-53.827,-43.513,+58
 repvgg_b0,36.317,63.683,54.113,45.887,15.82,224,0.875,bilinear,-55.353,-44.337,+16
-xcit_nano_12_p16_384_dist,36.153,63.847,53.217,46.783,3.05,384,1.000,bicubic,-55.947,-45.303,+4
-legacy_seresnet34,36.147,63.853,52.547,47.453,21.96,224,0.875,bilinear,-55.333,-45.783,+21
+xcit_nano_12_p16_384_dist,36.153,63.847,53.217,46.783,3.05,384,1.000,bicubic,-55.947,-45.213,+3
+legacy_seresnet34,36.147,63.853,52.547,47.453,21.96,224,0.875,bilinear,-55.333,-45.653,+20
 tv_resnet50,36.143,63.857,52.873,47.127,25.56,224,0.875,bilinear,-55.967,-45.547,0
-coat_tiny,36.100,63.900,51.073,48.927,5.50,224,0.900,bicubic,-57.400,-47.607,-99
-deit_tiny_distilled_patch16_224,36.093,63.907,54.273,45.727,5.91,224,0.900,bicubic,-54.997,-43.907,+35
-tv_resnet34,36.057,63.943,53.530,46.470,21.80,224,0.875,bilinear,-54.253,-44.350,+49
+coat_tiny,36.100,63.900,51.073,48.927,5.50,224,0.900,bicubic,-57.400,-47.607,-101
+deit_tiny_distilled_patch16_224,36.093,63.907,54.273,45.727,5.91,224,0.900,bicubic,-54.997,-43.997,+36
+tv_resnet34,36.057,63.943,53.530,46.470,21.80,224,0.875,bilinear,-54.253,-44.440,+49
 tf_efficientnet_lite0,36.020,63.980,53.520,46.480,4.65,224,0.875,bicubic,-55.260,-44.570,+21
 mobilenetv2_140,35.980,64.020,53.920,46.080,6.11,224,0.875,bicubic,-56.050,-44.330,-2
 selecsls42b,35.830,64.170,52.537,47.463,32.46,224,0.875,bicubic,-56.650,-45.903,-28
 seresnext26ts,35.807,64.193,53.990,46.010,10.39,256,0.900,bicubic,-56.983,-44.610,-48
-gluon_resnet34_v1b,35.750,64.250,52.290,47.710,21.80,224,0.875,bicubic,-55.340,-45.920,+30
+gluon_resnet34_v1b,35.750,64.250,52.290,47.710,21.80,224,0.875,bicubic,-55.340,-45.890,+29
 xcit_nano_12_p8_384_dist,35.730,64.270,52.297,47.703,3.05,384,1.000,bicubic,-57.520,-46.553,-85
-mixnet_m,35.677,64.323,52.447,47.553,5.01,224,0.875,bicubic,-56.583,-45.923,-17
+mixnet_m,35.677,64.323,52.447,47.553,5.01,224,0.875,bicubic,-56.583,-45.923,-18
 efficientnet_lite0,35.653,64.347,53.693,46.307,4.65,224,0.875,bicubic,-55.597,-44.557,+17
 dla34,35.647,64.353,52.817,47.183,15.74,224,0.875,bilinear,-55.603,-45.363,+15
-ssl_resnet18,35.630,64.370,53.813,46.187,11.69,224,0.875,bilinear,-55.070,-44.217,+32
+ssl_resnet18,35.630,64.370,53.813,46.187,11.69,224,0.875,bilinear,-55.070,-44.217,+31
 mobilenetv3_rw,35.620,64.380,53.740,46.260,5.48,224,0.875,bicubic,-55.930,-44.530,+3
 efficientnet_es_pruned,35.373,64.627,52.853,47.147,5.44,224,0.875,bicubic,-56.337,-45.547,-4
 mobilenetv2_110d,35.277,64.723,52.823,47.177,4.52,224,0.875,bicubic,-56.043,-45.357,+8
 hrnet_w18_small_v2,35.227,64.773,52.500,47.500,15.60,224,0.875,bilinear,-55.943,-45.850,+15
 tf_mixnet_m,35.217,64.783,50.977,49.023,5.01,224,0.875,bicubic,-56.953,-47.443,-21
-resnet18d,35.120,64.880,52.883,47.117,11.71,224,0.875,bicubic,-54.870,-44.957,+37
-xcit_nano_12_p16_224_dist,35.103,64.897,52.500,47.500,3.05,224,1.000,bicubic,-55.087,-45.260,+33
-convit_tiny,35.103,64.897,51.850,48.150,5.71,224,0.875,bicubic,-55.447,-46.360,+27
+resnet18d,35.120,64.880,52.883,47.117,11.71,224,0.875,bicubic,-54.870,-44.957,+36
+convit_tiny,35.103,64.897,51.850,48.150,5.71,224,0.875,bicubic,-55.447,-46.360,+26
+xcit_nano_12_p16_224_dist,35.103,64.897,52.500,47.500,3.05,224,1.000,bicubic,-55.087,-45.260,+32
 resnext26ts,35.097,64.903,53.447,46.553,10.30,256,0.900,bicubic,-57.113,-44.833,-26
-gcresnext26ts,34.973,65.027,51.613,48.387,10.48,256,0.900,bicubic,-57.497,-46.887,-43
+gcresnext26ts,34.973,65.027,51.613,48.387,10.48,256,0.900,bicubic,-57.497,-46.887,-44
 eca_resnext26ts,34.970,65.030,52.323,47.677,10.30,256,0.900,bicubic,-57.450,-46.287,-40
 regnety_008,34.883,65.117,51.863,48.137,6.26,224,0.875,bicubic,-57.007,-46.557,-17
 ese_vovnet19b_dw,34.830,65.170,51.997,48.003,6.54,224,0.875,bicubic,-57.190,-46.523,-22
 crossvit_9_240,34.680,65.320,51.793,48.207,8.55,240,0.875,bicubic,-56.390,-46.517,+12
-pit_ti_224,34.637,65.363,52.127,47.873,4.85,224,0.900,bicubic,-55.803,-45.893,+23
-mobilenetv3_large_100,34.570,65.430,52.917,47.083,5.48,224,0.875,bicubic,-56.910,-45.283,-10
+pit_ti_224,34.637,65.363,52.127,47.873,4.85,224,0.900,bicubic,-55.803,-45.713,+22
+mobilenetv3_large_100,34.570,65.430,52.917,47.083,5.48,224,0.875,bicubic,-56.910,-45.413,-9
 seresnext26t_32x4d,34.560,65.440,51.480,48.520,16.81,224,0.875,bicubic,-58.210,-47.070,-70
 seresnext26d_32x4d,34.527,65.473,51.570,48.430,16.81,224,0.875,bicubic,-57.903,-46.970,-48
-resnet26d,34.333,65.667,51.857,48.143,16.01,224,0.875,bicubic,-57.917,-46.613,-37
+resnet26d,34.333,65.667,51.857,48.143,16.01,224,0.875,bicubic,-57.917,-46.613,-38
 mixer_b16_224,34.327,65.673,48.050,51.950,59.88,224,0.875,bicubic,-56.803,-49.360,+1
 fbnetc_100,34.320,65.680,51.240,48.760,5.57,224,0.875,bilinear,-56.940,-46.580,-8
-tf_efficientnet_es,34.273,65.727,51.467,48.533,5.44,224,0.875,bicubic,-57.827,-46.963,-34
+tf_efficientnet_es,34.273,65.727,51.467,48.533,5.44,224,0.875,bicubic,-57.827,-47.053,-33
 regnety_006,34.243,65.757,51.297,48.703,6.06,224,0.875,bicubic,-57.337,-47.133,-20
 tf_mobilenetv3_large_100,33.977,66.023,51.520,48.480,5.48,224,0.875,bilinear,-57.433,-46.730,-15
 mnasnet_100,33.847,66.153,51.247,48.753,4.38,224,0.875,bicubic,-57.353,-46.793,-9
-regnetx_008,33.733,66.267,50.590,49.410,7.26,224,0.875,bicubic,-57.457,-47.780,-9
+regnetx_008,33.733,66.267,50.590,49.410,7.26,224,0.875,bicubic,-57.457,-47.780,-8
 xcit_nano_12_p8_224,33.610,66.390,50.230,49.770,3.05,224,1.000,bicubic,-57.490,-48.010,-5
-resnet26,33.593,66.407,51.017,48.983,16.00,224,0.875,bicubic,-57.867,-47.253,-20
-vit_tiny_r_s16_p8_384,33.593,66.407,50.650,49.350,6.36,384,1.000,bicubic,-58.127,-47.780,-32
+vit_tiny_r_s16_p8_384,33.593,66.407,50.650,49.350,6.36,384,1.000,bicubic,-58.127,-47.780,-31
+resnet26,33.593,66.407,51.017,48.983,16.00,224,0.875,bicubic,-57.867,-47.253,-21
 mixnet_s,33.587,66.413,51.030,48.970,4.13,224,0.875,bicubic,-58.193,-47.270,-34
 semnasnet_100,33.550,66.450,50.837,49.163,3.89,224,0.875,bicubic,-58.110,-47.423,-30
-vit_tiny_patch16_384,33.547,66.453,51.003,48.997,5.79,384,1.000,bicubic,-59.883,-47.837,-134
-spnasnet_100,33.513,66.487,51.303,48.697,4.42,224,0.875,bilinear,-57.097,-46.647,0
-crossvit_tiny_240,33.380,66.620,49.917,50.083,7.01,240,0.875,bicubic,-57.150,-48.033,+1
+vit_tiny_patch16_384,33.547,66.453,51.003,48.997,5.79,384,1.000,bicubic,-59.883,-47.837,-135
+spnasnet_100,33.513,66.487,51.303,48.697,4.42,224,0.875,bilinear,-57.097,-46.647,-1
+crossvit_tiny_240,33.380,66.620,49.917,50.083,7.01,240,0.875,bicubic,-57.150,-48.033,0
 vgg19_bn,33.313,66.687,50.877,49.123,143.68,224,0.875,bilinear,-57.677,-47.243,-8
-regnetx_006,33.207,66.793,50.300,49.700,6.20,224,0.875,bicubic,-57.543,-47.800,-6
-ghostnet_100,33.180,66.820,51.143,48.857,5.18,224,0.875,bilinear,-57.260,-46.697,0
-xcit_nano_12_p16_224,33.060,66.940,50.070,49.930,3.05,224,1.000,bicubic,-55.900,-47.340,+17
-resnet18,33.040,66.960,51.127,48.873,11.69,224,0.875,bilinear,-55.120,-45.993,+20
+regnetx_006,33.207,66.793,50.300,49.700,6.20,224,0.875,bicubic,-57.543,-47.800,-7
+ghostnet_100,33.180,66.820,51.143,48.857,5.18,224,0.875,bilinear,-57.260,-46.877,-1
+xcit_nano_12_p16_224,33.060,66.940,50.070,49.930,3.05,224,1.000,bicubic,-55.900,-47.340,+16
+resnet18,33.040,66.960,51.127,48.873,11.69,224,0.875,bilinear,-55.120,-45.993,+19
 legacy_seresnext26_32x4d,32.747,67.253,49.210,50.790,16.79,224,0.875,bicubic,-59.843,-49.210,-80
-hrnet_w18_small,32.720,67.280,50.673,49.327,13.19,224,0.875,bilinear,-57.180,-47.227,+3
-deit_tiny_patch16_224,32.703,67.297,50.323,49.677,5.72,224,0.900,bicubic,-56.897,-47.637,+6
-legacy_seresnet18,32.637,67.363,50.360,49.640,11.78,224,0.875,bicubic,-56.613,-47.330,+9
-regnetx_004,32.577,67.423,49.390,50.610,5.16,224,0.875,bicubic,-56.873,-48.390,+5
-mobilenetv2_100,32.570,67.430,50.867,49.133,3.50,224,0.875,bicubic,-57.270,-46.973,+1
-regnety_004,32.407,67.593,49.500,50.500,4.34,224,0.875,bicubic,-58.343,-48.580,-15
-gluon_resnet18_v1b,32.393,67.607,49.710,50.290,11.69,224,0.875,bicubic,-56.277,-47.400,+9
+hrnet_w18_small,32.720,67.280,50.673,49.327,13.19,224,0.875,bilinear,-57.180,-47.227,+2
+deit_tiny_patch16_224,32.703,67.297,50.323,49.677,5.72,224,0.900,bicubic,-56.897,-47.637,+5
+legacy_seresnet18,32.637,67.363,50.360,49.640,11.78,224,0.875,bicubic,-56.613,-47.330,+8
+regnetx_004,32.577,67.423,49.390,50.610,5.16,224,0.875,bicubic,-56.873,-48.390,+4
+mobilenetv2_100,32.570,67.430,50.867,49.133,3.50,224,0.875,bicubic,-57.270,-46.973,0
+regnety_004,32.407,67.593,49.500,50.500,4.34,224,0.875,bicubic,-58.343,-48.580,-16
+gluon_resnet18_v1b,32.393,67.607,49.710,50.290,11.69,224,0.875,bicubic,-56.277,-47.400,+8
 tf_mixnet_s,32.223,67.777,48.610,51.390,4.13,224,0.875,bicubic,-59.467,-49.630,-49
 vit_tiny_patch16_224,32.147,67.853,49.103,50.897,5.72,224,0.900,bicubic,-59.783,-49.227,-55
-tf_mobilenetv3_large_075,31.947,68.053,49.147,50.853,3.99,224,0.875,bilinear,-58.363,-48.823,-10
-tf_mobilenetv3_large_minimal_100,31.603,68.397,49.407,50.593,3.92,224,0.875,bilinear,-57.557,-47.913,+3
-vit_tiny_r_s16_p8_224,30.850,69.150,47.673,52.327,6.34,224,0.900,bicubic,-58.550,-50.017,-2
-vgg16_bn,30.363,69.637,47.267,52.733,138.37,224,0.875,bilinear,-60.157,-50.723,-17
-regnety_002,29.683,70.317,46.887,53.113,3.16,224,0.875,bicubic,-58.527,-50.533,+4
-vgg13_bn,28.970,71.030,46.827,53.173,133.05,224,0.875,bilinear,-60.240,-50.713,-2
-regnetx_002,28.887,71.113,45.587,54.413,2.68,224,0.875,bicubic,-58.473,-51.403,+5
-vgg19,28.687,71.313,45.257,54.743,143.67,224,0.875,bilinear,-61.003,-52.293,-10
-dla60x_c,28.520,71.480,46.260,53.740,1.32,224,0.875,bilinear,-58.560,-50.880,+6
-vgg11_bn,28.380,71.620,46.507,53.493,132.87,224,0.875,bilinear,-60.010,-50.773,-2
-vgg16,27.990,72.010,44.743,55.257,138.36,224,0.875,bilinear,-61.390,-52.777,-9
-tf_mobilenetv3_small_100,27.350,72.650,44.490,55.510,2.54,224,0.875,bilinear,-58.640,-51.920,+5
-mixer_l16_224,26.797,73.203,37.860,62.140,208.20,224,0.875,bicubic,-60.163,-56.170,+3
-eca_botnext26ts_256,26.743,73.257,41.953,58.047,10.59,256,0.950,bicubic,-64.107,-55.797,-34
+tf_mobilenetv3_large_075,31.947,68.053,49.147,50.853,3.99,224,0.875,bilinear,-58.363,-48.733,-12
+tf_mobilenetv3_large_minimal_100,31.603,68.397,49.407,50.593,3.92,224,0.875,bilinear,-57.557,-47.913,+2
+vit_tiny_r_s16_p8_224,30.850,69.150,47.673,52.327,6.34,224,0.900,bicubic,-58.550,-50.017,-3
+vgg16_bn,30.363,69.637,47.267,52.733,138.37,224,0.875,bilinear,-60.157,-50.723,-18
+regnety_002,29.683,70.317,46.887,53.113,3.16,224,0.875,bicubic,-58.527,-50.533,+3
+vgg13_bn,28.970,71.030,46.827,53.173,133.05,224,0.875,bilinear,-60.240,-50.713,-3
+regnetx_002,28.887,71.113,45.587,54.413,2.68,224,0.875,bicubic,-58.473,-51.403,+4
+vgg19,28.687,71.313,45.257,54.743,143.67,224,0.875,bilinear,-61.003,-52.293,-11
+dla60x_c,28.520,71.480,46.260,53.740,1.32,224,0.875,bilinear,-58.560,-50.880,+4
+vgg11_bn,28.380,71.620,46.507,53.493,132.87,224,0.875,bilinear,-60.010,-50.773,-3
+vgg16,27.990,72.010,44.743,55.257,138.36,224,0.875,bilinear,-61.390,-52.777,-10
+tf_mobilenetv3_small_100,27.350,72.650,44.490,55.510,2.54,224,0.875,bilinear,-58.640,-51.920,+3
+mixer_l16_224,26.797,73.203,37.860,62.140,208.20,224,0.875,bicubic,-60.163,-56.170,+1
 vgg11,26.610,73.390,43.510,56.490,132.86,224,0.875,bilinear,-60.720,-53.600,-2
 vgg13,26.317,73.683,43.463,56.537,133.05,224,0.875,bilinear,-61.233,-53.657,-5
-dla46x_c,26.283,73.717,43.907,56.093,1.07,224,0.875,bilinear,-59.187,-52.543,+1
-tf_mobilenetv3_small_075,26.273,73.727,43.710,56.290,2.04,224,0.875,bilinear,-58.257,-52.180,+2
-dla46_c,25.493,74.507,43.953,56.047,1.30,224,0.875,bilinear,-59.217,-52.257,0
-tf_mobilenetv3_small_minimal_100,25.107,74.893,42.987,57.013,2.04,224,0.875,bilinear,-57.573,-52.023,+1
-botnet26t_256,22.097,77.903,37.240,62.760,12.49,256,0.950,bicubic,-65.143,-59.510,-7
+dla46x_c,26.283,73.717,43.907,56.093,1.07,224,0.875,bilinear,-59.187,-52.543,0
+tf_mobilenetv3_small_075,26.273,73.727,43.710,56.290,2.04,224,0.875,bilinear,-58.257,-52.180,+1
+dla46_c,25.493,74.507,43.953,56.047,1.30,224,0.875,bilinear,-59.217,-52.257,-1
+tf_mobilenetv3_small_minimal_100,25.107,74.893,42.987,57.013,2.04,224,0.875,bilinear,-57.573,-52.023,0

results/results-imagenet-real.csv

@@ -7,21 +7,21 @@ beit_base_patch16_384,90.388,9.612,98.730,1.270,86.74,384,1.000,bicubic,+3.580,+
 vit_large_patch16_384,90.202,9.798,98.655,1.345,304.72,384,1.000,bicubic,+3.110,+0.349,+1
 cait_m48_448,90.194,9.806,98.484,1.516,356.46,448,1.000,bicubic,+3.700,+0.734,+3
 beit_large_patch16_224,90.157,9.843,98.730,1.270,304.43,224,0.900,bicubic,+2.681,+0.412,-3
-tf_efficientnet_b7_ns,90.134,9.866,98.617,1.383,66.35,600,0.949,bicubic,+3.304,+0.532,-1
-swin_large_patch4_window12_384,90.066,9.934,98.668,1.332,196.74,384,1.000,bicubic,+2.915,+0.430,-4
+tf_efficientnet_b7_ns,90.134,9.866,98.617,1.383,66.35,600,0.949,bicubic,+3.304,+0.533,-1
+swin_large_patch4_window12_384,90.066,9.934,98.668,1.332,196.74,384,1.000,bicubic,+2.916,+0.430,-4
 swin_base_patch4_window12_384,90.063,9.937,98.713,1.287,87.90,384,1.000,bicubic,+3.627,+0.647,+1
 cait_m36_384,90.046,9.954,98.497,1.503,271.22,384,1.000,bicubic,+3.990,+0.767,+7
 dm_nfnet_f6,90.025,9.975,98.542,1.458,438.36,576,0.956,bicubic,+3.895,+0.802,+4
 tf_efficientnetv2_l_in21ft1k,89.999,10.001,98.621,1.379,118.52,480,1.000,bicubic,+3.707,+0.637,+1
 vit_base_patch16_384,89.965,10.035,98.680,1.319,86.86,384,1.000,bicubic,+3.965,+0.674,+5
 xcit_large_24_p8_384_dist,89.893,10.107,98.373,1.627,188.93,384,1.000,bicubic,+3.897,+0.685,+5
-cait_s36_384,89.837,10.163,98.427,1.573,68.37,384,1.000,bicubic,+4.383,+0.944,+14
+cait_s36_384,89.837,10.163,98.427,1.573,68.37,384,1.000,bicubic,+4.383,+0.945,+14
 xcit_medium_24_p8_384_dist,89.805,10.195,98.358,1.642,84.32,384,1.000,bicubic,+3.985,+0.764,+5
 swin_large_patch4_window7_224,89.796,10.204,98.646,1.354,196.53,224,0.900,bicubic,+3.480,+0.756,-5
 vit_large_r50_s32_384,89.790,10.210,98.516,1.484,329.09,384,1.000,bicubic,+3.610,+0.592,-4
 tf_efficientnetv2_m_in21ft1k,89.777,10.223,98.501,1.499,54.14,480,1.000,bicubic,+4.179,+0.749,+6
-tf_efficientnet_b6_ns,89.760,10.240,98.505,1.494,43.04,528,0.942,bicubic,+3.314,+0.626,-11
-xcit_small_24_p8_384_dist,89.737,10.263,98.427,1.573,47.63,384,1.000,bicubic,+4.171,+0.850,+5
+tf_efficientnet_b6_ns,89.760,10.240,98.505,1.494,43.04,528,0.942,bicubic,+3.314,+0.625,-11
+xcit_small_24_p8_384_dist,89.737,10.263,98.427,1.573,47.63,384,1.000,bicubic,+4.171,+0.851,+5
 xcit_large_24_p16_384_dist,89.660,10.340,98.405,1.595,189.10,384,1.000,bicubic,+3.890,+0.871,+1
 tf_efficientnet_b5_ns,89.658,10.342,98.488,1.512,30.39,456,0.934,bicubic,+3.582,+0.736,-7
 tf_efficientnet_b8_ap,89.589,10.411,98.298,1.702,87.41,672,0.954,bicubic,+4.215,+1.000,+10
@@ -34,12 +34,12 @@ dm_nfnet_f3,89.478,10.522,98.392,1.608,254.92,416,0.940,bicubic,+3.946,+0.934,-3
 xcit_medium_24_p16_384_dist,89.476,10.524,98.296,1.704,84.40,384,1.000,bicubic,+4.050,+0.888,0
 dm_nfnet_f5,89.451,10.549,98.309,1.691,377.21,544,0.954,bicubic,+3.645,+0.827,-10
 beit_base_patch16_224,89.438,10.562,98.520,1.480,86.53,224,0.900,bicubic,+4.198,+0.866,+4
-deit_base_distilled_patch16_384,89.431,10.569,98.444,1.556,87.63,384,1.000,bicubic,+4.009,+1.111,-2
+deit_base_distilled_patch16_384,89.431,10.569,98.444,1.556,87.63,384,1.000,bicubic,+4.009,+1.112,-2
 tf_efficientnet_b7_ap,89.419,10.581,98.341,1.659,66.35,600,0.949,bicubic,+4.299,+1.091,+4
 tf_efficientnetv2_l,89.361,10.639,98.273,1.727,118.52,480,1.000,bicubic,+3.859,+0.903,-8
 tf_efficientnet_b6_ap,89.338,10.662,98.281,1.719,43.04,528,0.942,bicubic,+4.554,+1.143,+18
 tf_efficientnet_b8,89.338,10.662,98.305,1.695,87.41,672,0.954,bicubic,+3.988,+0.913,-3
-tf_efficientnet_b4_ns,89.323,10.678,98.352,1.648,19.34,380,0.922,bicubic,+4.172,+0.882,-1
+tf_efficientnet_b4_ns,89.323,10.678,98.352,1.648,19.34,380,0.922,bicubic,+4.173,+0.882,-1
 vit_large_patch16_224,89.308,10.692,98.397,1.603,304.33,224,0.900,bicubic,+3.470,+0.571,-20
 xcit_small_24_p16_384_dist,89.305,10.694,98.332,1.667,47.67,384,1.000,bicubic,+4.201,+1.016,-1
 xcit_medium_24_p8_224_dist,89.286,10.714,98.194,1.806,84.32,224,1.000,bicubic,+4.218,+0.918,+1
@@ -89,7 +89,7 @@ efficientnetv2_rw_s,88.484,11.517,97.976,2.024,23.94,384,1.000,bicubic,+4.654,+1
 crossvit_18_dagger_408,88.477,11.523,97.895,2.105,44.61,408,1.000,bicubic,+4.293,+1.073,-11
 cait_s24_224,88.451,11.549,97.950,2.050,46.92,224,1.000,bicubic,+4.989,+1.384,+17
 resmlp_big_24_distilled_224,88.447,11.553,97.940,2.060,129.14,224,0.875,bicubic,+4.851,+1.284,+14
-tf_efficientnet_b3_ns,88.441,11.559,98.031,1.968,12.23,300,0.904,bicubic,+4.399,+1.124,-7
+tf_efficientnet_b3_ns,88.441,11.559,98.031,1.968,12.23,300,0.904,bicubic,+4.399,+1.123,-7
 resnetv2_101x3_bitm,88.430,11.570,98.153,1.847,387.93,448,1.000,bilinear,+4.000,+0.781,-25
 resnest200e,88.424,11.576,98.049,1.951,70.20,320,0.909,bicubic,+4.576,+1.159,-2
 vit_large_r50_s32_224,88.424,11.576,98.072,1.928,328.99,224,0.900,bicubic,+3.984,+1.102,-29
@@ -101,7 +101,7 @@ resnet152d,88.347,11.653,97.929,2.071,60.21,320,1.000,bicubic,+4.683,+1.195,+4
 tf_efficientnet_b5,88.315,11.685,97.914,2.086,30.39,456,0.934,bicubic,+4.505,+1.166,-4
 crossvit_15_dagger_408,88.298,11.702,97.874,2.127,28.50,408,1.000,bicubic,+4.472,+1.088,-6
 xcit_small_12_p16_224_dist,88.251,11.749,97.856,2.144,26.25,224,1.000,bicubic,+4.901,+1.434,+9
-resnetrs152,88.246,11.754,97.733,2.267,86.62,320,1.000,bicubic,+4.537,+1.123,-3
+resnetrs152,88.246,11.754,97.733,2.267,86.62,320,1.000,bicubic,+4.536,+1.123,-3
 deit_base_distilled_patch16_224,88.217,11.783,97.920,2.080,87.34,224,0.900,bicubic,+4.829,+1.430,+4
 ig_resnext101_32x8d,88.161,11.839,97.856,2.144,88.79,224,0.875,bilinear,+5.451,+1.216,+28
 xcit_large_24_p8_224,88.161,11.839,97.387,2.613,188.93,224,1.000,bicubic,+3.779,+0.731,-37
@@ -110,7 +110,7 @@ cait_xxs36_384,88.142,11.858,97.914,2.086,17.37,384,1.000,bicubic,+5.952,+1.754,
 resnetv2_152x2_bit_teacher_384,88.142,11.858,98.044,1.956,236.34,384,1.000,bicubic,+4.298,+0.926,-16
 dm_nfnet_f0,88.135,11.865,97.850,2.150,71.49,256,0.900,bicubic,+4.751,+1.270,-1
 xcit_tiny_12_p8_384_dist,88.093,11.907,97.923,2.077,6.71,384,1.000,bicubic,+5.701,+1.705,+36
-swsl_resnext101_32x4d,88.086,11.914,97.974,2.026,44.18,224,0.875,bilinear,+4.860,+1.206,+4
+swsl_resnext101_32x4d,88.086,11.914,97.974,2.026,44.18,224,0.875,bilinear,+4.860,+1.644,+3
 xcit_tiny_24_p8_224_dist,88.048,11.952,97.818,2.182,12.11,224,1.000,bicubic,+5.472,+1.638,+26
 nfnet_l0,87.980,12.020,97.865,2.135,35.07,288,1.000,bicubic,+5.228,+1.349,+16
 xcit_small_24_p8_224,87.975,12.025,97.575,2.425,47.63,224,1.000,bicubic,+4.129,+0.943,-23
@@ -122,14 +122,14 @@ twins_svt_large,87.907,12.093,97.581,2.419,99.27,224,0.900,bicubic,+4.223,+0.971
 vit_base_patch32_384,87.898,12.101,98.021,1.979,88.30,384,1.000,bicubic,+4.552,+1.177,-9
 twins_pcpvt_large,87.879,12.121,97.859,2.142,60.99,224,0.900,bicubic,+4.741,+1.251,-5
 regnetz_c,87.854,12.146,97.816,2.184,13.46,320,0.940,bicubic,+5.338,+1.456,+19
-deit_base_patch16_384,87.852,12.149,97.510,2.490,86.86,384,1.000,bicubic,+4.745,+1.134,-4
+deit_base_patch16_384,87.852,12.149,97.510,2.490,86.86,384,1.000,bicubic,+4.746,+1.134,-4
 xcit_small_12_p8_224,87.832,12.168,97.564,2.436,26.21,224,1.000,bicubic,+4.486,+1.088,-12
 resnetv2_50x1_bit_distilled,87.802,12.198,97.901,2.099,25.55,224,0.875,bicubic,+4.980,+1.377,+2
 tresnet_xl_448,87.792,12.208,97.466,2.534,78.44,448,0.875,bilinear,+4.736,+1.282,-5
 tresnet_m,87.734,12.266,97.530,2.470,31.39,224,0.875,bilinear,+4.658,+1.404,-7
 twins_pcpvt_base,87.728,12.272,97.728,2.272,43.83,224,0.900,bicubic,+5.016,+1.380,+3
 gc_efficientnetv2_rw_t,87.717,12.283,97.805,2.195,13.68,288,1.000,bicubic,+5.239,+1.509,+14
-swin_small_patch4_window7_224,87.678,12.322,97.570,2.430,49.61,224,0.900,bicubic,+4.453,+1.240,-16
+swin_small_patch4_window7_224,87.678,12.322,97.570,2.430,49.61,224,0.900,bicubic,+4.452,+0.802,-15
 resnetv2_101x1_bitm,87.670,12.330,97.942,2.058,44.54,448,1.000,bilinear,+5.340,+1.414,+20
 pnasnet5large,87.657,12.343,97.487,2.513,86.06,331,0.911,bicubic,+4.859,+1.453,-4
 efficientnetv2_rw_t,87.653,12.347,97.681,2.319,13.65,288,1.000,bicubic,+5.315,+1.487,+17
@@ -145,7 +145,7 @@ jx_nest_small,87.495,12.505,97.521,2.479,38.35,224,0.875,bicubic,+4.377,+1.189,-
 resnetv2_152x2_bit_teacher,87.491,12.509,97.807,2.193,236.34,224,0.875,bicubic,+4.589,+1.239,-19
 efficientnet_b3,87.452,12.548,97.679,2.321,12.23,320,1.000,bicubic,+5.194,+1.563,+14
 resnet61q,87.433,12.567,97.605,2.396,36.85,288,1.000,bicubic,+4.911,+1.471,-5
-cait_xxs24_384,87.399,12.601,97.613,2.387,12.03,384,1.000,bicubic,+6.445,+1.975,+67
+cait_xxs24_384,87.399,12.601,97.613,2.387,12.03,384,1.000,bicubic,+6.445,+1.975,+70
 resnet51q,87.388,12.612,97.581,2.419,35.70,288,1.000,bilinear,+5.020,+1.405,+1
 xcit_tiny_24_p8_224,87.375,12.625,97.634,2.366,12.11,224,1.000,bicubic,+5.481,+1.650,+22
 tresnet_l_448,87.373,12.627,97.489,2.511,55.99,448,0.875,bilinear,+5.111,+1.509,+8
@@ -156,87 +156,90 @@ crossvit_18_240,87.307,12.693,97.485,2.515,43.27,240,0.875,bicubic,+4.913,+1.423
 resnetv2_101,87.296,12.704,97.329,2.671,44.54,224,0.950,bicubic,+5.264,+1.465,+11
 ecaresnet101d,87.281,12.719,97.560,2.440,44.57,224,0.875,bicubic,+5.109,+1.506,+6
 pit_s_distilled_224,87.264,12.736,97.504,2.496,24.04,224,0.900,bicubic,+5.270,+1.704,+10
-resnest101e,87.262,12.738,97.558,2.442,48.28,256,0.875,bilinear,+4.386,+1.245,-31
+resnest101e,87.262,12.738,97.558,2.442,48.28,256,0.875,bilinear,+4.386,+1.246,-31
 resnetrs101,87.243,12.757,97.455,2.545,63.62,288,0.940,bicubic,+4.949,+1.453,-3
 mixer_b16_224_miil,87.230,12.770,97.417,2.583,59.88,224,0.875,bilinear,+4.928,+1.703,-5
 tresnet_xl,87.230,12.770,97.400,2.600,78.44,224,0.875,bilinear,+5.172,+1.468,+4
-xcit_tiny_12_p8_224_dist,87.224,12.776,97.442,2.558,6.71,224,1.000,bicubic,+6.010,+1.836,+38
+xcit_tiny_12_p8_224_dist,87.224,12.776,97.442,2.558,6.71,224,1.000,bicubic,+6.010,+1.836,+40
 convit_base,87.205,12.795,97.295,2.705,86.54,224,0.875,bicubic,+4.913,+1.361,-6
+xcit_tiny_12_p16_384_dist,87.198,12.802,97.468,2.532,6.72,384,1.000,bicubic,+6.254,+2.054,+53
 tf_efficientnet_b3_ap,87.198,12.802,97.382,2.618,12.23,300,0.904,bicubic,+5.376,+1.762,+10
-xcit_tiny_12_p16_384_dist,87.198,12.802,97.468,2.532,6.72,384,1.000,bicubic,+6.254,+2.054,+50
-visformer_small,87.185,12.815,97.320,2.679,40.22,224,0.900,bicubic,+5.089,+1.443,-2
+visformer_small,87.185,12.815,97.320,2.679,40.22,224,0.900,bicubic,+5.089,+1.442,-2
 crossvit_15_dagger_240,87.153,12.847,97.440,2.560,28.21,240,0.875,bicubic,+4.843,+1.478,-14
 xcit_small_24_p16_224,87.136,12.864,97.256,2.744,47.67,224,1.000,bicubic,+4.558,+1.256,-30
-convit_small,87.044,12.956,97.348,2.652,27.78,224,0.875,bicubic,+5.632,+1.602,+19
-crossvit_15_240,87.038,12.962,97.423,2.577,27.53,240,0.875,bicubic,+5.512,+1.729,+11
-jx_nest_tiny,87.014,12.986,97.380,2.620,17.06,224,0.875,bicubic,+5.581,+1.760,+16
-tf_efficientnetv2_b3,87.014,12.986,97.303,2.697,14.36,300,0.904,bicubic,+5.061,+1.519,-2
-regnetz_b,87.012,12.988,97.429,2.571,9.72,288,0.940,bicubic,+6.294,+1.955,+53
+convit_small,87.044,12.956,97.348,2.652,27.78,224,0.875,bicubic,+5.632,+1.602,+22
+crossvit_15_240,87.038,12.962,97.423,2.577,27.53,240,0.875,bicubic,+5.512,+1.729,+12
+jx_nest_tiny,87.014,12.986,97.380,2.620,17.06,224,0.875,bicubic,+5.580,+1.760,+18
+tf_efficientnetv2_b3,87.014,12.986,97.303,2.697,14.36,300,0.904,bicubic,+5.060,+1.519,-2
+regnetz_b,87.012,12.988,97.429,2.571,9.72,288,0.940,bicubic,+6.294,+1.955,+56
 xcit_small_12_p16_224,87.000,13.000,97.248,2.752,26.25,224,1.000,bicubic,+5.024,+1.430,-5
-deit_small_distilled_patch16_224,86.993,13.007,97.316,2.684,22.44,224,0.900,bicubic,+5.791,+1.938,+26
-resmlp_36_distilled_224,86.987,13.013,97.273,2.727,44.69,224,0.875,bicubic,+5.833,+1.777,+26
+deit_small_distilled_patch16_224,86.993,13.007,97.316,2.684,22.44,224,0.900,bicubic,+5.791,+1.938,+28
+resmlp_36_distilled_224,86.987,13.013,97.273,2.727,44.69,224,0.875,bicubic,+5.833,+1.777,+29
 xcit_large_24_p16_224,86.961,13.039,96.923,3.077,189.10,224,1.000,bicubic,+4.063,+1.041,-51
 xcit_medium_24_p16_224,86.940,13.060,97.096,2.904,84.40,224,1.000,bicubic,+4.314,+1.120,-43
-tnt_s_patch16_224,86.901,13.099,97.361,2.639,23.76,224,0.900,bicubic,+5.387,+1.617,+3
-convmixer_1536_20,86.861,13.139,97.346,2.654,51.63,224,0.960,bicubic,+5.485,+1.736,+12
+tnt_s_patch16_224,86.901,13.099,97.361,2.639,23.76,224,0.900,bicubic,+5.387,+1.617,+5
+convmixer_1536_20,86.861,13.139,97.346,2.654,51.63,224,0.960,bicubic,+5.485,+1.736,+15
 rexnet_200,86.854,13.146,97.282,2.718,16.37,224,0.875,bicubic,+5.228,+1.610,-3
-vit_small_patch16_224,86.852,13.148,97.598,2.402,22.05,224,0.900,bicubic,+5.466,+1.468,+8
+vit_small_patch16_224,86.852,13.148,97.598,2.402,22.05,224,0.900,bicubic,+5.466,+1.468,+11
 ssl_resnext101_32x16d,86.850,13.150,97.519,2.481,194.03,224,0.875,bilinear,+5.006,+1.429,-11
 tf_efficientnet_b3,86.842,13.158,97.293,2.707,12.23,300,0.904,bicubic,+5.196,+1.573,-7
-vit_small_r26_s32_224,86.840,13.161,97.532,2.468,36.43,224,0.900,bicubic,+5.001,+1.506,-12
+vit_small_r26_s32_224,86.840,13.161,97.532,2.468,36.43,224,0.900,bicubic,+5.002,+1.506,-12
 deit_base_patch16_224,86.827,13.173,97.056,2.944,86.57,224,0.900,bicubic,+4.843,+1.314,-18
 tresnet_m_448,86.814,13.186,97.210,2.791,31.39,448,0.875,bilinear,+5.100,+1.640,-12
-coat_mini,86.810,13.190,97.167,2.833,10.34,224,0.900,bicubic,+5.528,+1.773,+9
-swsl_resnet50,86.801,13.199,97.491,2.509,25.56,224,0.875,bilinear,+5.655,+1.513,+14
-tf_efficientnet_lite4,86.799,13.201,97.256,2.744,13.01,380,0.920,bilinear,+5.259,+1.596,-10
+coat_mini,86.810,13.190,97.167,2.833,10.34,224,0.900,bicubic,+5.528,+1.773,+11
+swsl_resnet50,86.801,13.199,97.491,2.509,25.56,224,0.875,bilinear,+5.655,+1.513,+17
+tf_efficientnet_lite4,86.799,13.201,97.256,2.744,13.01,380,0.920,bilinear,+5.259,+1.596,-9
 ssl_resnext101_32x8d,86.797,13.203,97.470,2.530,88.79,224,0.875,bilinear,+5.197,+1.424,-12
-tresnet_l,86.754,13.246,97.271,2.729,55.99,224,0.875,bilinear,+5.270,+1.651,-7
+tresnet_l,86.754,13.246,97.271,2.729,55.99,224,0.875,bilinear,+5.270,+1.651,-5
 twins_svt_small,86.754,13.246,97.175,2.825,24.06,224,0.900,bicubic,+5.072,+1.497,-17
 crossvit_base_240,86.735,13.265,97.122,2.878,105.03,240,0.875,bicubic,+4.529,+1.294,-34
-levit_256,86.733,13.267,97.261,2.739,18.89,224,0.900,bicubic,+5.231,+1.781,-11
-crossvit_small_240,86.705,13.295,97.284,2.716,26.86,240,0.875,bicubic,+5.675,+1.818,+13
-seresnext50_32x4d,86.705,13.295,97.207,2.793,27.56,224,0.875,bicubic,+5.437,+1.581,+1
-pit_b_224,86.690,13.310,96.894,3.107,73.76,224,0.900,bicubic,+4.246,+1.181,-53
-tf_efficientnet_b1_ns,86.681,13.319,97.380,2.620,7.79,240,0.882,bicubic,+5.297,+1.642,-8
-swin_tiny_patch4_window7_224,86.671,13.329,97.199,2.801,28.29,224,0.900,bicubic,+5.285,+1.663,-11
-gernet_l,86.652,13.348,97.195,2.805,31.08,256,0.875,bilinear,+5.306,+1.659,-7
-wide_resnet50_2,86.647,13.353,97.205,2.795,68.88,224,0.875,bicubic,+5.197,+1.687,-16
-efficientnet_el,86.622,13.378,97.182,2.818,10.59,300,0.904,bicubic,+5.316,+1.646,-7
-twins_pcpvt_small,86.609,13.391,97.342,2.658,24.11,224,0.900,bicubic,+5.505,+1.700,+1
-resmlp_24_distilled_224,86.607,13.393,97.137,2.863,30.02,224,0.875,bicubic,+5.847,+1.917,+18
-nf_resnet50,86.598,13.402,97.295,2.705,25.56,288,0.940,bicubic,+5.942,+1.959,+21
-efficientnet_b3_pruned,86.585,13.415,97.186,2.814,9.86,300,0.904,bicubic,+5.727,+1.946,+13
-sehalonet33ts,86.585,13.415,97.004,2.995,13.69,256,0.940,bicubic,+5.603,+1.732,+4
-resnest50d_4s2x40d,86.581,13.419,97.271,2.729,30.42,224,0.875,bicubic,+5.461,+1.711,-5
-repvgg_b3,86.570,13.430,97.143,2.857,123.09,224,0.875,bilinear,+6.054,+1.879,+23
-xcit_tiny_24_p16_224_dist,86.543,13.457,97.214,2.786,12.12,224,1.000,bicubic,+6.081,+2.006,+26
-ecaresnet50d,86.479,13.521,97.186,2.814,25.58,224,0.875,bicubic,+5.859,+1.878,+17
-ssl_resnext101_32x4d,86.474,13.526,97.468,2.532,44.18,224,0.875,bilinear,+5.552,+1.738,+4
-gcresnet50t,86.459,13.541,97.141,2.859,25.90,256,0.900,bicubic,+5.521,+1.701,+2
-gluon_resnet152_v1s,86.453,13.547,97.122,2.878,60.32,224,0.875,bicubic,+5.433,+1.700,-5
-haloregnetz_b,86.449,13.551,96.938,3.062,11.68,224,0.940,bicubic,+5.407,+1.738,-9
-resnest50d_1s4x24d,86.440,13.560,97.152,2.848,25.68,224,0.875,bicubic,+5.440,+1.826,-6
-resnetv2_50x1_bitm,86.440,13.560,97.605,2.396,25.55,448,1.000,bilinear,+6.096,+1.918,+27
+levit_256,86.733,13.267,97.261,2.739,18.89,224,0.900,bicubic,+5.231,+1.781,-9
+seresnext50_32x4d,86.705,13.295,97.207,2.793,27.56,224,0.875,bicubic,+5.437,+1.581,+3
+crossvit_small_240,86.705,13.295,97.284,2.716,26.86,240,0.875,bicubic,+5.675,+1.818,+16
+pit_b_224,86.690,13.310,96.894,3.107,73.76,224,0.900,bicubic,+4.246,+1.182,-53
+tf_efficientnet_b1_ns,86.681,13.319,97.380,2.620,7.79,240,0.882,bicubic,+5.297,+1.642,-5
+swin_tiny_patch4_window7_224,86.671,13.329,97.199,2.801,28.29,224,0.900,bicubic,+5.285,+1.663,-8
+gernet_l,86.652,13.348,97.195,2.805,31.08,256,0.875,bilinear,+5.306,+1.659,-5
+wide_resnet50_2,86.647,13.353,97.205,2.795,68.88,224,0.875,bicubic,+5.197,+1.687,-14
+efficientnet_el,86.622,13.378,97.182,2.818,10.59,300,0.904,bicubic,+5.316,+1.646,-5
+twins_pcpvt_small,86.609,13.391,97.342,2.658,24.11,224,0.900,bicubic,+5.505,+1.700,+4
+resmlp_24_distilled_224,86.607,13.393,97.137,2.863,30.02,224,0.875,bicubic,+5.847,+1.917,+21
+nf_resnet50,86.598,13.402,97.295,2.705,25.56,288,0.940,bicubic,+5.942,+1.959,+24
+efficientnet_b3_pruned,86.585,13.415,97.186,2.814,9.86,300,0.904,bicubic,+5.727,+1.946,+16
+sehalonet33ts,86.585,13.415,97.004,2.995,13.69,256,0.940,bicubic,+5.603,+1.732,+7
+resnest50d_4s2x40d,86.581,13.419,97.271,2.729,30.42,224,0.875,bicubic,+5.461,+1.711,-2
+repvgg_b3,86.570,13.430,97.143,2.857,123.09,224,0.875,bilinear,+6.054,+1.879,+26
+xcit_tiny_24_p16_224_dist,86.543,13.457,97.214,2.786,12.12,224,1.000,bicubic,+6.081,+2.006,+29
+ecaresnet50d,86.479,13.521,97.186,2.814,25.58,224,0.875,bicubic,+5.859,+1.878,+20
+ssl_resnext101_32x4d,86.474,13.526,97.468,2.532,44.18,224,0.875,bilinear,+5.552,+1.738,+7
+gcresnet50t,86.459,13.541,97.141,2.859,25.90,256,0.900,bicubic,+5.521,+1.701,+5
+gluon_resnet152_v1s,86.453,13.547,97.122,2.878,60.32,224,0.875,bicubic,+5.433,+1.700,-2
+haloregnetz_b,86.449,13.551,96.938,3.062,11.68,224,0.940,bicubic,+5.407,+1.738,-6
+resnest50d_1s4x24d,86.440,13.560,97.152,2.848,25.68,224,0.875,bicubic,+5.440,+1.826,-3
+resnetv2_50x1_bitm,86.440,13.560,97.605,2.396,25.55,448,1.000,bilinear,+6.096,+1.919,+30
+halonet50ts,86.391,13.609,96.799,3.200,22.73,256,0.940,bicubic,+4.843,+1.487,-39
+lamhalobotnet50ts_256,86.391,13.609,96.676,3.324,22.57,256,0.950,bicubic,+4.969,+1.620,-30
+halo2botnet50ts_256,86.372,13.628,96.761,3.239,22.64,256,0.950,bicubic,+4.852,+1.503,-38
 repvgg_b3g4,86.359,13.641,97.052,2.949,83.83,224,0.875,bilinear,+6.141,+1.948,+38
-legacy_senet154,86.334,13.666,96.925,3.075,115.09,224,0.875,bilinear,+5.007,+1.419,-25
+legacy_senet154,86.334,13.666,96.925,3.075,115.09,224,0.875,bilinear,+5.008,+1.419,-26
 gernet_m,86.325,13.675,97.092,2.908,21.14,224,0.875,bilinear,+5.599,+1.914,+4
 cait_xxs36_224,86.321,13.679,97.113,2.887,17.30,224,1.000,bicubic,+6.559,+2.245,+62
 pit_s_224,86.319,13.681,97.045,2.955,23.46,224,0.900,bicubic,+5.219,+1.711,-17
 efficientnet_b2,86.310,13.690,96.990,3.010,9.11,288,1.000,bicubic,+5.700,+1.674,+6
 vit_small_patch32_384,86.304,13.696,97.417,2.583,22.92,384,1.000,bicubic,+5.818,+1.819,+9
-gluon_senet154,86.274,13.726,96.936,3.064,115.09,224,0.875,bicubic,+5.050,+1.584,-27
+gluon_senet154,86.274,13.726,96.936,3.064,115.09,224,0.875,bicubic,+5.050,+1.584,-28
 resnest50d,86.231,13.769,97.064,2.936,27.48,224,0.875,bilinear,+5.269,+1.686,-14
 convmixer_768_32,86.220,13.780,97.030,2.970,21.11,224,0.960,bicubic,+6.060,+1.956,+32
 efficientnet_el_pruned,86.188,13.812,97.022,2.978,10.59,300,0.904,bicubic,+5.900,+1.800,+21
 ecaresnet101d_pruned,86.182,13.818,97.342,2.658,24.88,224,0.875,bicubic,+5.370,+1.702,-9
-halonet50ts,86.175,13.825,96.785,3.215,22.73,256,0.940,bicubic,+4.826,+1.501,-38
-rexnet_150,86.165,13.835,97.071,2.929,9.73,224,0.875,bicubic,+5.855,+1.911,+15
-cspdarknet53,86.152,13.848,97.013,2.987,27.64,256,0.887,bilinear,+6.102,+1.921,+34
-inception_v4,86.152,13.848,96.921,3.079,42.68,299,0.875,bicubic,+6.008,+1.949,+27
-inception_resnet_v2,86.120,13.880,97.041,2.959,55.84,299,0.897,bicubic,+5.672,+1.733,+4
-xcit_tiny_12_p8_224,86.118,13.882,97.084,2.917,6.71,224,1.000,bicubic,+6.408,+2.026,+50
-ssl_resnext50_32x4d,86.075,13.925,97.212,2.788,25.03,224,0.875,bilinear,+5.773,+1.794,+12
+rexnet_150,86.165,13.835,97.071,2.929,9.73,224,0.875,bicubic,+5.855,+1.911,+16
+cspdarknet53,86.152,13.848,97.013,2.987,27.64,256,0.887,bilinear,+6.102,+1.921,+35
+inception_v4,86.152,13.848,96.921,3.079,42.68,299,0.875,bicubic,+6.008,+1.949,+28
+inception_resnet_v2,86.120,13.880,97.041,2.959,55.84,299,0.897,bicubic,+5.672,+1.733,+5
+xcit_tiny_12_p8_224,86.118,13.882,97.084,2.917,6.71,224,1.000,bicubic,+6.408,+2.026,+51
+ssl_resnext50_32x4d,86.075,13.925,97.212,2.788,25.03,224,0.875,bilinear,+5.773,+1.794,+13
 tf_efficientnet_el,86.071,13.929,96.966,3.034,10.59,300,0.904,bicubic,+5.823,+1.842,+16
+lambda_resnet50ts,86.052,13.948,96.744,3.256,21.54,256,0.950,bicubic,+4.886,+1.648,-37
 ecaresnetlight,86.045,13.955,97.069,2.931,30.16,224,0.875,bicubic,+5.591,+1.817,-1
 gluon_resnet101_v1s,86.037,13.963,97.026,2.974,44.67,224,0.875,bicubic,+5.755,+1.864,+11
 resnetv2_50,86.020,13.980,96.911,3.089,25.55,224,0.950,bicubic,+5.614,+1.831,-1
@@ -245,39 +248,39 @@ gluon_seresnext101_32x4d,86.007,13.993,96.979,3.021,48.96,224,0.875,bicubic,+5.1
 seresnet33ts,86.005,13.995,97.009,2.991,19.78,256,0.900,bicubic,+5.633,+1.895,0
 resnet50d,85.994,14.006,96.985,3.015,25.58,224,0.875,bicubic,+5.456,+1.825,-13
 tf_efficientnet_b2_ap,85.977,14.023,96.808,3.192,9.11,260,0.890,bicubic,+5.671,+1.776,+2
-ecaresnet26t,85.964,14.036,97.032,2.968,16.01,320,0.950,bicubic,+6.130,+1.948,+32
+ecaresnet26t,85.964,14.036,97.032,2.968,16.01,320,0.950,bicubic,+6.130,+1.948,+31
 vit_base_patch32_224,85.960,14.040,97.128,2.872,88.22,224,0.900,bicubic,+5.228,+1.562,-24
 gluon_seresnext101_64x4d,85.951,14.049,96.987,3.013,88.23,224,0.875,bicubic,+5.081,+1.681,-30
 gluon_resnet152_v1d,85.906,14.094,96.808,3.192,60.21,224,0.875,bicubic,+5.430,+1.606,-15
-vit_large_patch32_384,85.902,14.098,97.370,2.630,306.63,384,1.000,bicubic,+4.396,+1.284,-68
+vit_large_patch32_384,85.902,14.098,97.370,2.630,306.63,384,1.000,bicubic,+4.396,+1.284,-69
 tf_efficientnetv2_b2,85.900,14.100,96.883,3.117,10.10,260,0.890,bicubic,+5.686,+1.839,+6
 tf_efficientnet_b2,85.881,14.119,96.855,3.145,9.11,260,0.890,bicubic,+5.813,+1.951,+12
 vit_base_patch16_sam_224,85.879,14.121,96.706,3.294,86.57,224,0.900,bicubic,+5.637,+1.944,+1
 repvgg_b2g4,85.857,14.143,96.821,3.179,61.76,224,0.875,bilinear,+6.477,+2.127,+48
-seresnet50,85.830,14.170,97.002,2.998,28.09,224,0.875,bicubic,+5.582,+1.932,-3
+seresnet50,85.830,14.170,97.002,2.998,28.09,224,0.875,bicubic,+5.582,+1.932,-2
 gluon_resnet101_v1d,85.827,14.173,96.661,3.339,44.57,224,0.875,bicubic,+5.423,+1.637,-16
 gcresnet33ts,85.804,14.196,96.896,3.104,19.88,256,0.900,bicubic,+5.718,+1.904,+6
-mixnet_xl,85.785,14.215,96.721,3.280,11.90,224,0.875,bicubic,+5.317,+1.788,-23
-ens_adv_inception_resnet_v2,85.781,14.220,96.757,3.243,55.84,299,0.897,bicubic,+5.802,+1.821,+9
+mixnet_xl,85.785,14.215,96.721,3.280,11.90,224,0.875,bicubic,+5.317,+1.789,-23
+ens_adv_inception_resnet_v2,85.781,14.220,96.757,3.243,55.84,299,0.897,bicubic,+5.803,+1.821,+9
 cspresnext50,85.763,14.237,96.838,3.162,20.57,224,0.875,bilinear,+5.711,+1.888,+5
 tf_efficientnet_lite3,85.759,14.241,96.894,3.107,8.20,300,0.904,bilinear,+5.939,+1.984,+19
 gluon_resnext101_32x4d,85.744,14.256,96.616,3.384,44.18,224,0.875,bicubic,+5.406,+1.708,-17
 ese_vovnet39b,85.742,14.258,96.902,3.098,24.57,224,0.875,bicubic,+6.438,+2.178,+44
 legacy_seresnext101_32x4d,85.738,14.262,96.763,3.237,48.96,224,0.875,bilinear,+5.516,+1.751,-9
-eca_resnet33ts,85.736,14.264,96.900,3.100,19.68,256,0.900,bicubic,+5.640,+1.926,-3
-xcit_tiny_24_p16_224,85.736,14.264,96.938,3.062,12.12,224,1.000,bicubic,+6.284,+2.050,+33
+xcit_tiny_24_p16_224,85.736,14.264,96.938,3.062,12.12,224,1.000,bicubic,+6.284,+2.050,+34
+eca_resnet33ts,85.736,14.264,96.900,3.100,19.68,256,0.900,bicubic,+5.640,+1.926,-4
 cspresnet50,85.725,14.275,96.802,3.198,21.62,256,0.887,bilinear,+6.149,+2.100,+26
 regnety_320,85.723,14.277,96.727,3.273,145.05,224,0.875,bicubic,+4.929,+1.481,-47
-gluon_resnext101_64x4d,85.704,14.296,96.646,3.354,83.46,224,0.875,bicubic,+5.078,+1.644,-42
-resnet50,85.704,14.296,96.490,3.510,25.56,224,0.950,bicubic,+5.322,+1.896,-28
+resnet50,85.704,14.296,96.490,3.510,25.56,224,0.950,bicubic,+5.322,+1.896,-27
+gluon_resnext101_64x4d,85.704,14.296,96.646,3.354,83.46,224,0.875,bicubic,+5.078,+1.644,-43
 resmlp_big_24_224,85.697,14.303,96.417,3.583,129.14,224,0.875,bicubic,+4.665,+1.395,-64
 xception71,85.693,14.307,96.772,3.228,42.34,299,0.903,bicubic,+5.809,+1.840,0
-efficientnet_em,85.691,14.309,96.941,3.059,6.90,240,0.882,bicubic,+6.431,+2.148,+40
+efficientnet_em,85.691,14.309,96.941,3.059,6.90,240,0.882,bicubic,+6.431,+2.149,+42
 deit_small_patch16_224,85.663,14.337,96.906,3.094,22.05,224,0.900,bicubic,+5.797,+1.850,+1
 dpn107,85.650,14.350,96.725,3.275,86.92,224,0.875,bicubic,+5.478,+1.821,-17
 pit_xs_distilled_224,85.644,14.356,96.665,3.335,11.00,224,0.900,bicubic,+6.350,+2.291,+35
 efficientnet_b2_pruned,85.637,14.363,96.746,3.254,8.31,260,0.890,bicubic,+5.731,+1.892,-6
-resmlp_36_224,85.623,14.377,96.795,3.205,44.69,224,0.875,bicubic,+5.846,+1.909,+4
+resmlp_36_224,85.623,14.377,96.795,3.205,44.69,224,0.875,bicubic,+5.847,+1.909,+4
 levit_192,85.586,14.414,96.744,3.256,10.95,224,0.900,bicubic,+5.726,+1.942,-3
 gluon_resnet152_v1c,85.576,14.425,96.652,3.348,60.21,224,0.875,bicubic,+5.664,+1.800,-10
 ecaresnet50d_pruned,85.573,14.427,96.934,3.066,19.94,224,0.875,bicubic,+5.867,+2.060,+5
@@ -287,46 +290,48 @@ regnety_120,85.541,14.459,96.774,3.226,51.82,224,0.875,bicubic,+5.155,+1.652,-43
 regnetx_320,85.516,14.484,96.667,3.333,107.81,224,0.875,bicubic,+5.268,+1.641,-34
 nf_regnet_b1,85.496,14.504,96.791,3.209,10.22,288,0.900,bicubic,+6.200,+2.049,+24
 dpn92,85.484,14.516,96.635,3.365,37.67,224,0.875,bicubic,+5.490,+1.799,-20
-rexnet_130,85.465,14.536,96.686,3.314,7.56,224,0.875,bicubic,+5.968,+2.012,+8
+rexnet_130,85.465,14.536,96.686,3.314,7.56,224,0.875,bicubic,+5.969,+2.012,+8
 gluon_resnet152_v1b,85.458,14.542,96.560,3.440,60.19,224,0.875,bicubic,+5.778,+1.824,-1
-resnetrs50,85.433,14.568,96.731,3.269,35.69,224,0.910,bicubic,+5.562,+1.761,-16
-dpn131,85.411,14.589,96.637,3.363,79.25,224,0.875,bicubic,+5.577,+1.925,-14
+resnetrs50,85.433,14.568,96.731,3.269,35.69,224,0.910,bicubic,+5.563,+1.761,-16
+dpn131,85.411,14.589,96.637,3.363,79.25,224,0.875,bicubic,+5.577,+1.925,-12
 dla102x2,85.383,14.617,96.635,3.365,41.28,224,0.875,bilinear,+5.943,+1.991,+8
-regnetx_160,85.364,14.636,96.633,3.367,54.28,224,0.875,bicubic,+5.530,+1.809,-14
+regnetx_160,85.364,14.636,96.633,3.367,54.28,224,0.875,bicubic,+5.530,+1.809,-15
 gmlp_s16_224,85.349,14.651,96.641,3.358,19.42,224,0.875,bicubic,+5.707,+2.019,-3
 gluon_seresnext50_32x4d,85.343,14.657,96.671,3.329,27.56,224,0.875,bicubic,+5.419,+1.843,-26
-skresnext50_32x4d,85.315,14.685,96.394,3.606,27.48,224,0.875,bicubic,+5.173,+1.750,-35
-gluon_resnet101_v1c,85.311,14.689,96.415,3.585,44.57,224,0.875,bicubic,+5.777,+1.827,-2
-dpn98,85.309,14.691,96.466,3.534,61.57,224,0.875,bicubic,+5.655,+1.862,-8
-xception65,85.304,14.696,96.633,3.367,39.92,299,0.903,bicubic,+5.758,+1.973,-5
-lambda_resnet26t,85.300,14.700,96.723,3.277,10.96,256,0.940,bicubic,+6.192,+2.135,+21
-regnety_064,85.287,14.713,96.633,3.367,30.58,224,0.875,bicubic,+5.557,+1.871,-17
-dpn68b,85.285,14.715,96.473,3.527,12.61,224,0.875,bicubic,+6.069,+2.051,+15
-resnetblur50,85.277,14.723,96.516,3.484,25.56,224,0.875,bicubic,+5.977,+1.986,+5
-resmlp_24_224,85.275,14.726,96.499,3.502,30.02,224,0.875,bicubic,+5.888,+1.953,-3
-coat_lite_mini,85.249,14.751,96.684,3.316,11.01,224,0.900,bicubic,+6.149,+2.082,+17
-resnet33ts,85.242,14.758,96.620,3.380,19.68,256,0.900,bicubic,+6.028,+2.048,+12
+botnet26t_256,85.334,14.666,96.635,3.365,12.49,256,0.950,bicubic,+6.074,+2.101,+18
+skresnext50_32x4d,85.315,14.685,96.394,3.606,27.48,224,0.875,bicubic,+5.173,+1.750,-36
+gluon_resnet101_v1c,85.311,14.689,96.415,3.585,44.57,224,0.875,bicubic,+5.777,+1.827,-3
+dpn98,85.309,14.691,96.466,3.534,61.57,224,0.875,bicubic,+5.655,+1.862,-9
+xception65,85.304,14.696,96.633,3.367,39.92,299,0.903,bicubic,+5.758,+1.973,-6
+lambda_resnet26t,85.300,14.700,96.723,3.277,10.96,256,0.940,bicubic,+6.192,+2.135,+22
+regnety_064,85.287,14.713,96.633,3.367,30.58,224,0.875,bicubic,+5.557,+1.871,-18
+dpn68b,85.285,14.715,96.473,3.527,12.61,224,0.875,bicubic,+6.069,+2.051,+16
+resnetblur50,85.277,14.723,96.516,3.484,25.56,224,0.875,bicubic,+5.977,+1.880,+5
+resmlp_24_224,85.275,14.726,96.499,3.502,30.02,224,0.875,bicubic,+5.889,+1.953,-4
+coat_lite_mini,85.249,14.751,96.684,3.316,11.01,224,0.900,bicubic,+6.149,+2.082,+18
+resnet33ts,85.242,14.758,96.620,3.380,19.68,256,0.900,bicubic,+6.028,+2.048,+13
 resnext50_32x4d,85.232,14.768,96.526,3.474,25.03,224,0.875,bicubic,+5.432,+1.912,-27
-regnety_080,85.232,14.768,96.635,3.365,39.18,224,0.875,bicubic,+5.360,+1.803,-34
-cait_xxs24_224,85.221,14.779,96.718,3.282,11.96,224,1.000,bicubic,+6.845,+2.402,+50
-halonet26t,85.213,14.787,96.466,3.534,12.48,256,0.950,bicubic,+6.079,+2.150,+10
-xcit_tiny_12_p16_224_dist,85.206,14.794,96.605,3.395,6.72,224,1.000,bicubic,+6.626,+2.401,+33
-resnext101_32x8d,85.187,14.813,96.449,3.551,88.79,224,0.875,bilinear,+5.875,+1.927,-6
-gluon_inception_v3,85.183,14.817,96.531,3.470,23.83,299,0.875,bicubic,+6.385,+2.151,+24
-resnet32ts,85.174,14.826,96.624,3.376,17.96,256,0.900,bicubic,+6.154,+2.262,+13
-hrnet_w48,85.155,14.845,96.490,3.510,77.47,224,0.875,bilinear,+5.833,+1.976,-10
-regnetx_120,85.138,14.862,96.473,3.527,46.11,224,0.875,bicubic,+5.532,+1.743,-24
-gluon_resnet101_v1b,85.129,14.871,96.370,3.630,44.55,224,0.875,bicubic,+5.829,+1.734,-8
+regnety_080,85.232,14.768,96.635,3.365,39.18,224,0.875,bicubic,+5.360,+1.803,-36
+cait_xxs24_224,85.221,14.779,96.718,3.282,11.96,224,1.000,bicubic,+6.845,+2.402,+51
+halonet26t,85.213,14.787,96.466,3.534,12.48,256,0.950,bicubic,+6.079,+2.150,+11
+xcit_tiny_12_p16_224_dist,85.206,14.794,96.605,3.395,6.72,224,1.000,bicubic,+6.626,+2.401,+34
+resnext101_32x8d,85.187,14.813,96.449,3.551,88.79,224,0.875,bilinear,+5.875,+1.927,-7
+gluon_inception_v3,85.183,14.817,96.531,3.470,23.83,299,0.875,bicubic,+6.385,+2.151,+25
+resnet32ts,85.174,14.826,96.624,3.376,17.96,256,0.900,bicubic,+6.154,+2.262,+14
+hrnet_w48,85.155,14.845,96.490,3.510,77.47,224,0.875,bilinear,+5.833,+1.976,-11
+regnetx_120,85.138,14.862,96.473,3.527,46.11,224,0.875,bicubic,+5.532,+1.743,-25
 tf_efficientnet_b1_ap,85.129,14.871,96.407,3.593,7.79,240,0.882,bicubic,+5.855,+2.105,-6
-xception,85.129,14.871,96.477,3.523,22.86,299,0.897,bicubic,+6.081,+2.081,+7
-gluon_xception65,85.123,14.877,96.599,3.401,39.92,299,0.903,bicubic,+5.421,+1.731,-33
-hrnet_w64,85.117,14.883,96.746,3.254,128.06,224,0.875,bilinear,+5.660,+2.092,-23
-ssl_resnet50,85.104,14.896,96.862,3.139,25.56,224,0.875,bilinear,+5.868,+2.029,-8
+xception,85.129,14.871,96.477,3.523,22.86,299,0.897,bicubic,+6.081,+2.081,+9
+gluon_resnet101_v1b,85.129,14.871,96.370,3.630,44.55,224,0.875,bicubic,+5.829,+1.840,-12
+eca_botnext26ts_256,85.127,14.873,96.511,3.489,10.59,256,0.950,bicubic,+5.853,+1.905,-8
+gluon_xception65,85.123,14.877,96.599,3.401,39.92,299,0.903,bicubic,+5.421,+1.731,-35
+hrnet_w64,85.117,14.883,96.746,3.254,128.06,224,0.875,bilinear,+5.661,+2.092,-25
+ssl_resnet50,85.104,14.896,96.862,3.139,25.56,224,0.875,bilinear,+5.868,+2.030,-8
 res2net101_26w_4s,85.089,14.911,96.385,3.615,45.21,224,0.875,bilinear,+5.897,+1.947,-4
 lambda_resnet26rpt_256,85.084,14.916,96.558,3.442,10.99,256,0.940,bicubic,+6.116,+2.130,+6
-tf_efficientnet_cc_b1_8e,85.072,14.928,96.424,3.576,39.72,240,0.882,bicubic,+5.746,+2.056,-21
+tf_efficientnet_cc_b1_8e,85.072,14.928,96.424,3.576,39.72,240,0.882,bicubic,+5.746,+2.056,-23
 xcit_nano_12_p8_384_dist,85.029,14.971,96.629,3.371,3.05,384,1.000,bicubic,+7.211,+2.595,+62
-gluon_resnext50_32x4d,85.010,14.990,96.426,3.574,25.03,224,0.875,bicubic,+5.646,+2.002,-24
+gluon_resnext50_32x4d,85.010,14.990,96.426,3.574,25.03,224,0.875,bicubic,+5.646,+2.002,-26
 tf_efficientnet_b0_ns,85.003,14.997,96.496,3.504,5.29,224,0.875,bicubic,+6.345,+2.126,+15
 resnest26d,84.997,15.003,96.629,3.371,17.07,224,0.875,bilinear,+6.519,+2.333,+20
 coat_tiny,84.969,15.031,96.409,3.591,5.50,224,0.900,bicubic,+6.535,+2.375,+25
@@ -338,9 +343,9 @@ tf_efficientnet_b1,84.907,15.093,96.362,3.638,7.79,240,0.882,bicubic,+6.071,+2.1
 hrnet_w44,84.886,15.114,96.432,3.568,67.06,224,0.875,bilinear,+5.996,+2.050,-4
 regnetx_080,84.875,15.125,96.428,3.572,39.57,224,0.875,bicubic,+5.655,+1.882,-21
 gluon_resnet50_v1s,84.852,15.148,96.447,3.553,25.68,224,0.875,bicubic,+6.156,+2.199,+3
-res2net50_26w_8s,84.843,15.157,96.338,3.662,48.40,224,0.875,bilinear,+5.863,+2.054,-10
-dla60_res2next,84.828,15.172,96.413,3.587,17.03,224,0.875,bilinear,+6.386,+2.255,+13
-mixnet_l,84.826,15.174,96.328,3.672,7.33,224,0.875,bicubic,+5.846,+2.148,-13
+res2net50_26w_8s,84.843,15.157,96.338,3.662,48.40,224,0.875,bilinear,+5.863,+2.054,-11
+dla60_res2next,84.828,15.172,96.413,3.587,17.03,224,0.875,bilinear,+6.386,+2.217,+14
+mixnet_l,84.826,15.174,96.328,3.672,7.33,224,0.875,bicubic,+5.846,+2.148,-12
 levit_128,84.822,15.178,96.351,3.649,9.21,224,0.900,bicubic,+6.356,+2.341,+8
 dla60_res2net,84.820,15.180,96.481,3.519,20.85,224,0.875,bilinear,+6.358,+2.273,+8
 vit_tiny_patch16_384,84.820,15.180,96.714,3.286,5.79,384,1.000,bicubic,+6.374,+2.170,+8
@@ -348,21 +353,21 @@ tv_resnet152,84.818,15.182,96.219,3.781,60.19,224,0.875,bilinear,+6.496,+2.175,+
 dla102x,84.813,15.187,96.548,3.452,26.31,224,0.875,bilinear,+6.301,+2.322,+1
 gluon_resnet50_v1d,84.811,15.189,96.394,3.606,25.58,224,0.875,bicubic,+5.747,+1.934,-23
 xception41,84.809,15.191,96.413,3.587,26.97,299,0.903,bicubic,+6.277,+2.129,-2
-pit_xs_224,84.783,15.217,96.505,3.495,10.62,224,0.900,bicubic,+6.599,+2.341,+18
-regnetx_064,84.783,15.217,96.492,3.508,26.21,224,0.875,bicubic,+5.723,+2.026,-25
+regnetx_064,84.783,15.217,96.492,3.508,26.21,224,0.875,bicubic,+5.723,+2.026,-24
+pit_xs_224,84.783,15.217,96.505,3.495,10.62,224,0.900,bicubic,+6.599,+2.341,+17
 hrnet_w40,84.745,15.255,96.556,3.444,57.56,224,0.875,bilinear,+5.819,+2.078,-20
 repvgg_b2,84.726,15.274,96.484,3.517,89.02,224,0.875,bilinear,+5.932,+2.058,-14
 res2net50_26w_6s,84.724,15.276,96.274,3.726,37.05,224,0.875,bilinear,+6.158,+2.156,-8
 resmlp_12_distilled_224,84.707,15.293,96.225,3.775,15.35,224,0.875,bicubic,+6.763,+2.663,+25
 legacy_seresnet152,84.696,15.304,96.417,3.583,66.82,224,0.875,bilinear,+6.034,+2.041,-13
 selecsls60b,84.655,15.345,96.298,3.702,32.77,224,0.875,bicubic,+6.247,+2.122,0
-hrnet_w32,84.653,15.347,96.413,3.587,41.23,224,0.875,bilinear,+6.211,+2.217,-3
+hrnet_w32,84.653,15.347,96.413,3.587,41.23,224,0.875,bilinear,+6.211,+2.255,-4
 bat_resnext26ts,84.640,15.360,96.285,3.715,10.73,256,0.900,bicubic,+6.378,+2.185,+4
 tf_efficientnetv2_b0,84.625,15.375,96.272,3.728,7.14,224,0.875,bicubic,+6.255,+2.246,+1
 efficientnet_b1,84.615,15.385,96.336,3.664,7.79,256,1.000,bicubic,+5.811,+1.990,-24
 regnetx_040,84.600,15.400,96.385,3.615,22.12,224,0.875,bicubic,+6.116,+2.131,-13
-efficientnet_es,84.591,15.409,96.315,3.685,5.44,224,0.875,bicubic,+6.509,+2.371,+10
-hrnet_w30,84.591,15.409,96.392,3.608,37.71,224,0.875,bilinear,+6.389,+2.164,+3
+hrnet_w30,84.591,15.409,96.392,3.608,37.71,224,0.875,bilinear,+6.389,+2.164,+4
+efficientnet_es,84.591,15.409,96.315,3.685,5.44,224,0.875,bicubic,+6.509,+2.371,+9
 tf_mixnet_l,84.559,15.441,96.247,3.753,7.33,224,0.875,bicubic,+5.781,+2.247,-25
 wide_resnet101_2,84.555,15.445,96.351,3.649,126.89,224,0.875,bilinear,+5.701,+2.067,-32
 dla60x,84.529,15.471,96.291,3.709,17.35,224,0.875,bilinear,+6.283,+2.267,-2
@@ -376,15 +381,15 @@ res2net50_26w_4s,84.371,15.629,96.080,3.920,25.70,224,0.875,bilinear,+6.385,+2.2
 hardcorenas_f,84.322,15.678,96.027,3.973,8.20,224,0.875,bilinear,+6.218,+2.233,-3
 res2net50_14w_8s,84.307,15.693,96.074,3.926,25.06,224,0.875,bilinear,+6.173,+2.218,-5
 selecsls60,84.282,15.718,96.091,3.909,30.67,224,0.875,bicubic,+6.298,+2.259,+1
-regnetx_032,84.230,15.770,96.255,3.745,15.30,224,0.875,bicubic,+6.080,+2.169,-9
-res2next50,84.230,15.770,96.003,3.997,24.67,224,0.875,bilinear,+5.988,+2.099,-13
+res2next50,84.230,15.770,96.003,3.997,24.67,224,0.875,bilinear,+5.988,+2.099,-12
+regnetx_032,84.230,15.770,96.255,3.745,15.30,224,0.875,bicubic,+6.080,+2.169,-10
 gluon_resnet50_v1c,84.209,15.791,96.165,3.835,25.58,224,0.875,bicubic,+6.203,+2.177,-4
 dla102,84.192,15.808,96.223,3.777,33.27,224,0.875,bilinear,+6.164,+2.265,-6
 gcresnext26ts,84.181,15.819,96.084,3.916,10.48,256,0.900,bicubic,+6.361,+2.258,+6
-rexnet_100,84.173,15.827,96.253,3.747,4.80,224,0.875,bicubic,+6.313,+2.377,+2
-tf_inception_v3,84.128,15.872,95.918,4.082,23.83,299,0.875,bicubic,+6.268,+2.272,+2
+rexnet_100,84.173,15.827,96.253,3.747,4.80,224,0.875,bicubic,+6.313,+2.377,+3
+tf_inception_v3,84.128,15.872,95.918,4.082,23.83,299,0.875,bicubic,+6.268,+2.272,+1
 seresnext26ts,84.124,15.876,96.069,3.931,10.39,256,0.900,bicubic,+6.276,+2.281,+2
-res2net50_48w_2s,84.121,15.879,95.965,4.035,25.29,224,0.875,bilinear,+6.588,+2.407,+12
+res2net50_48w_2s,84.121,15.879,95.965,4.035,25.29,224,0.875,bilinear,+6.587,+2.407,+12
 resnet34d,84.104,15.896,95.975,4.025,21.82,224,0.875,bicubic,+6.990,+2.593,+25
 tf_efficientnet_lite2,84.092,15.908,96.063,3.937,6.09,260,0.890,bicubic,+6.610,+2.315,+12
 xcit_tiny_12_p16_224,84.083,15.917,96.230,3.771,6.72,224,1.000,bicubic,+6.963,+2.512,+22
@@ -392,13 +397,13 @@ efficientnet_b0,84.034,15.966,95.956,4.044,5.29,224,0.875,bicubic,+6.330,+2.434,
 crossvit_9_dagger_240,84.030,15.970,96.080,3.920,8.78,240,0.875,bicubic,+7.040,+2.474,+26
 hardcorenas_e,83.972,16.028,95.901,4.099,8.07,224,0.875,bilinear,+6.172,+2.205,-2
 gmixer_24_224,83.970,16.030,95.852,4.148,24.72,224,0.875,bicubic,+5.918,+2.184,-19
-tf_efficientnet_cc_b0_8e,83.970,16.030,96.072,3.929,24.01,224,0.875,bicubic,+6.062,+2.415,-12
+tf_efficientnet_cc_b0_8e,83.970,16.030,96.072,3.929,24.01,224,0.875,bicubic,+6.062,+2.416,-12
 regnety_016,83.955,16.045,95.997,4.003,11.20,224,0.875,bicubic,+6.091,+2.273,-11
 tv_resnext50_32x4d,83.955,16.045,95.948,4.052,25.03,224,0.875,bilinear,+6.345,+2.264,-3
 gluon_resnet50_v1b,83.942,16.058,96.018,3.982,25.56,224,0.875,bicubic,+6.366,+2.296,0
-densenet161,83.900,16.101,96.014,3.986,28.68,224,0.875,bicubic,+6.547,+2.378,+7
-mobilenetv2_120d,83.887,16.113,95.905,4.095,5.83,224,0.875,bicubic,+6.601,+2.393,+9
-seresnext26t_32x4d,83.887,16.113,95.943,4.057,16.81,224,0.875,bicubic,+5.909,+2.201,-21
+densenet161,83.900,16.101,96.014,3.986,28.68,224,0.875,bicubic,+6.548,+2.378,+7
+seresnext26t_32x4d,83.887,16.113,95.943,4.057,16.81,224,0.875,bicubic,+5.909,+2.201,-20
+mobilenetv2_120d,83.887,16.113,95.905,4.095,5.83,224,0.875,bicubic,+6.601,+2.393,+8
 adv_inception_v3,83.876,16.124,95.939,4.061,23.83,299,0.875,bicubic,+6.298,+2.199,-5
 tv_resnet101,83.855,16.145,95.888,4.112,44.55,224,0.875,bilinear,+6.487,+2.328,+2
 inception_v3,83.771,16.229,95.898,4.101,23.83,299,0.875,bicubic,+6.307,+2.422,-2
@@ -418,12 +423,12 @@ mobilenetv3_large_100_miil,83.549,16.451,95.450,4.550,5.48,224,0.875,bilinear,+5
 densenet201,83.547,16.453,95.807,4.193,20.01,224,0.875,bicubic,+6.257,+2.327,-10
 gernet_s,83.522,16.478,95.792,4.208,8.17,224,0.875,bilinear,+6.616,+2.658,+4
 legacy_seresnext26_32x4d,83.515,16.485,95.719,4.281,16.79,224,0.875,bicubic,+6.421,+2.409,-5
-mixnet_m,83.513,16.487,95.691,4.309,5.01,224,0.875,bicubic,+6.239,+2.269,-11
-tf_efficientnet_b0,83.513,16.487,95.717,4.283,5.29,224,0.875,bicubic,+6.667,+2.487,+2
+mixnet_m,83.513,16.487,95.691,4.309,5.01,224,0.875,bicubic,+6.239,+2.269,-12
+tf_efficientnet_b0,83.513,16.487,95.717,4.283,5.29,224,0.875,bicubic,+6.667,+2.487,+3
 hrnet_w18,83.500,16.500,95.907,4.093,21.30,224,0.875,bilinear,+6.742,+2.469,+4
-densenetblur121d,83.475,16.525,95.817,4.183,8.00,224,0.875,bicubic,+6.885,+2.625,+8
+densenetblur121d,83.475,16.525,95.817,4.183,8.00,224,0.875,bicubic,+6.885,+2.625,+9
 selecsls42b,83.460,16.540,95.749,4.251,32.46,224,0.875,bicubic,+6.270,+2.359,-14
-resnext26ts,83.457,16.543,95.726,4.274,10.30,256,0.900,bicubic,+6.686,+2.596,0
+resnext26ts,83.457,16.543,95.726,4.274,10.30,256,0.900,bicubic,+6.685,+2.596,0
 tf_efficientnet_lite1,83.355,16.645,95.638,4.362,5.42,240,0.882,bicubic,+6.691,+2.404,+2
 hardcorenas_c,83.336,16.664,95.713,4.287,5.52,224,0.875,bilinear,+6.286,+2.541,-12
 regnetx_016,83.186,16.814,95.740,4.260,9.19,224,0.875,bicubic,+6.240,+2.314,-9
@@ -431,7 +436,7 @@ mobilenetv2_140,83.176,16.824,95.685,4.315,6.11,224,0.875,bicubic,+6.660,+2.685,
 tf_mixnet_m,83.174,16.826,95.469,4.531,5.01,224,0.875,bicubic,+6.216,+2.303,-12
 xcit_nano_12_p16_384_dist,83.174,16.826,95.743,4.257,3.05,384,1.000,bicubic,+7.706,+3.067,+22
 dpn68,83.171,16.829,95.589,4.411,12.61,224,0.875,bicubic,+6.877,+2.627,+7
-tf_efficientnet_es,83.167,16.833,95.591,4.409,5.44,224,0.875,bicubic,+6.577,+2.379,-1
+tf_efficientnet_es,83.167,16.833,95.591,4.409,5.44,224,0.875,bicubic,+6.577,+2.379,-2
 ese_vovnet19b_dw,83.114,16.886,95.790,4.210,6.54,224,0.875,bicubic,+6.290,+2.510,-10
 levit_128s,83.065,16.935,95.533,4.467,7.78,224,0.900,bicubic,+6.527,+2.669,-2
 resnet26d,83.043,16.957,95.602,4.398,16.01,224,0.875,bicubic,+6.353,+2.454,-9
@@ -441,8 +446,8 @@ hardcorenas_b,82.877,17.123,95.386,4.614,5.18,224,0.875,bilinear,+6.347,+2.634,-
 densenet121,82.815,17.185,95.585,4.415,7.98,224,0.875,bicubic,+7.247,+2.933,+9
 vit_tiny_r_s16_p8_384,82.693,17.307,95.862,4.138,6.36,384,1.000,bicubic,+6.721,+2.590,+2
 densenet169,82.661,17.339,95.593,4.407,14.15,224,0.875,bicubic,+6.763,+2.569,+3
-mixnet_s,82.525,17.476,95.352,4.648,4.13,224,0.875,bicubic,+6.531,+2.560,-2
-vit_small_patch32_224,82.510,17.490,95.674,4.326,22.88,224,0.900,bicubic,+6.516,+2.398,-2
+mixnet_s,82.525,17.476,95.352,4.648,4.13,224,0.875,bicubic,+6.531,+2.560,-1
+vit_small_patch32_224,82.510,17.490,95.674,4.326,22.88,224,0.900,bicubic,+6.516,+2.398,-3
 regnety_008,82.478,17.523,95.480,4.520,6.26,224,0.875,bicubic,+6.158,+2.412,-7
 efficientnet_lite0,82.388,17.612,95.286,4.714,4.65,224,0.875,bicubic,+6.884,+2.770,+6
 resnest14d,82.362,17.638,95.324,4.676,10.61,224,0.875,bilinear,+6.856,+2.804,+4
@@ -452,7 +457,7 @@ mobilenetv3_rw,82.268,17.732,95.241,4.759,5.48,224,0.875,bicubic,+6.650,+2.529,-
 semnasnet_100,82.253,17.747,95.239,4.761,3.89,224,0.875,bicubic,+6.801,+2.633,+4
 mobilenetv3_large_100,82.177,17.823,95.196,4.804,5.48,224,0.875,bicubic,+6.403,+2.656,-6
 resnet34,82.125,17.875,95.136,4.864,21.80,224,0.875,bilinear,+7.013,+2.860,+7
-mobilenetv2_110d,82.076,17.924,95.076,4.923,4.52,224,0.875,bicubic,+7.024,+2.889,+9
+mobilenetv2_110d,82.076,17.924,95.076,4.923,4.52,224,0.875,bicubic,+7.024,+2.888,+9
 vit_tiny_patch16_224,82.044,17.956,95.493,4.507,5.72,224,0.900,bicubic,+6.590,+2.641,-1
 tf_mixnet_s,82.040,17.960,95.130,4.870,4.13,224,0.875,bicubic,+6.356,+2.494,-9
 repvgg_b0,82.006,17.994,95.102,4.898,15.82,224,0.875,bilinear,+6.854,+2.688,+1
@@ -462,34 +467,33 @@ pit_ti_distilled_224,81.972,18.029,95.156,4.845,5.10,224,0.900,bicubic,+7.442,+3
 hrnet_w18_small_v2,81.959,18.041,95.166,4.834,15.60,224,0.875,bilinear,+6.853,+2.754,0
 tf_efficientnet_lite0,81.950,18.050,95.160,4.840,4.65,224,0.875,bicubic,+7.118,+2.984,+3
 resnet26,81.942,18.058,95.245,4.755,16.00,224,0.875,bicubic,+6.650,+2.671,-7
-tf_mobilenetv3_large_100,81.841,18.159,95.076,4.923,5.48,224,0.875,bilinear,+6.331,+2.469,-14
+tf_mobilenetv3_large_100,81.841,18.159,95.076,4.923,5.48,224,0.875,bilinear,+6.331,+2.468,-14
 tv_densenet121,81.728,18.272,95.036,4.964,7.98,224,0.875,bicubic,+6.982,+2.882,+2
-regnety_006,81.703,18.297,95.113,4.887,6.06,224,0.875,bicubic,+6.436,+2.579,-9
+regnety_006,81.703,18.297,95.113,4.887,6.06,224,0.875,bicubic,+6.437,+2.579,-9
 dla34,81.643,18.357,94.874,5.126,15.74,224,0.875,bilinear,+7.035,+2.816,+2
 xcit_nano_12_p8_224,81.641,18.359,95.264,4.736,3.05,224,1.000,bicubic,+7.729,+3.098,+10
 crossvit_9_240,81.630,18.370,94.983,5.017,8.55,240,0.875,bicubic,+7.648,+3.013,+8
 fbnetc_100,81.555,18.445,94.948,5.052,5.57,224,0.875,bilinear,+6.435,+2.574,-11
 legacy_seresnet34,81.532,18.468,94.899,5.101,21.96,224,0.875,bilinear,+6.740,+2.771,-5
 regnetx_008,81.508,18.492,95.062,4.938,7.26,224,0.875,bicubic,+6.452,+2.714,-10
-gluon_resnet34_v1b,81.489,18.511,94.808,5.192,21.80,224,0.875,bicubic,+6.897,+2.811,-3
+gluon_resnet34_v1b,81.489,18.511,94.808,5.192,21.80,224,0.875,bicubic,+6.897,+2.812,-3
 mnasnet_100,81.472,18.528,94.893,5.107,4.38,224,0.875,bicubic,+6.798,+2.795,-6
 vgg19_bn,81.451,18.549,94.778,5.222,143.68,224,0.875,bilinear,+7.217,+2.924,-2
-convit_tiny,81.115,18.885,95.044,4.955,5.71,224,0.875,bicubic,+8.003,+3.325,+11
-crossvit_tiny_240,81.100,18.900,94.991,5.009,7.01,240,0.875,bicubic,+7.756,+3.069,+7
+convit_tiny,81.115,18.885,95.044,4.955,5.71,224,0.875,bicubic,+8.003,+3.324,+10
+crossvit_tiny_240,81.100,18.900,94.991,5.009,7.01,240,0.875,bicubic,+7.756,+3.069,+6
 spnasnet_100,80.866,19.134,94.511,5.489,4.42,224,0.875,bilinear,+6.788,+2.691,-4
 ghostnet_100,80.699,19.301,94.291,5.709,5.18,224,0.875,bilinear,+6.715,+2.831,-3
 regnety_004,80.648,19.352,94.692,5.308,4.34,224,0.875,bicubic,+6.636,+2.926,-5
-skresnet18,80.624,19.376,94.383,5.617,11.96,224,0.875,bicubic,+7.602,+3.213,+7
-regnetx_006,80.616,19.384,94.526,5.474,6.20,224,0.875,bicubic,+6.770,+2.844,-2
-pit_ti_224,80.597,19.404,94.618,5.383,4.85,224,0.900,bicubic,+7.675,+3.208,+7
-swsl_resnet18,80.562,19.438,94.746,5.254,11.69,224,0.875,bilinear,+7.280,+2.988,+2
-vgg16_bn,80.535,19.465,94.583,5.417,138.37,224,0.875,bilinear,+7.175,+3.091,-2
-resnet18d,80.387,19.613,94.244,5.756,11.71,224,0.875,bicubic,+8.119,+3.560,+10
-tv_resnet34,80.377,19.623,94.430,5.570,21.80,224,0.875,bilinear,+7.073,+3.008,-2
-mobilenetv2_100,80.257,19.743,94.197,5.803,3.50,224,0.875,bicubic,+7.305,+3.195,+1
-xcit_nano_12_p16_224_dist,80.225,19.775,94.363,5.637,3.05,224,1.000,bicubic,+7.913,+3.511,+6
-vit_base_patch32_sam_224,80.212,19.788,93.821,6.179,88.22,224,0.900,bicubic,+6.512,+2.813,-9
-eca_botnext26ts_256,80.118,19.882,94.244,5.756,10.59,256,0.950,bicubic,+6.240,+2.456,-12
+skresnet18,80.624,19.376,94.383,5.617,11.96,224,0.875,bicubic,+7.602,+3.213,+6
+regnetx_006,80.616,19.384,94.526,5.474,6.20,224,0.875,bicubic,+6.770,+2.844,-3
+pit_ti_224,80.597,19.404,94.618,5.383,4.85,224,0.900,bicubic,+7.675,+3.208,+6
+swsl_resnet18,80.562,19.438,94.746,5.254,11.69,224,0.875,bilinear,+7.280,+2.988,+1
+vgg16_bn,80.535,19.465,94.583,5.417,138.37,224,0.875,bilinear,+7.175,+3.091,-3
+resnet18d,80.387,19.613,94.244,5.756,11.71,224,0.875,bicubic,+8.119,+3.560,+9
+tv_resnet34,80.377,19.623,94.430,5.570,21.80,224,0.875,bilinear,+7.073,+3.008,-3
+mobilenetv2_100,80.257,19.743,94.197,5.803,3.50,224,0.875,bicubic,+7.305,+3.195,0
+xcit_nano_12_p16_224_dist,80.225,19.775,94.363,5.637,3.05,224,1.000,bicubic,+7.913,+3.511,+5
+vit_base_patch32_sam_224,80.212,19.788,93.821,6.179,88.22,224,0.900,bicubic,+6.512,+2.813,-10
 ssl_resnet18,80.114,19.886,94.594,5.406,11.69,224,0.875,bilinear,+7.502,+3.174,-1
 tf_mobilenetv3_large_075,80.088,19.912,94.186,5.814,3.99,224,0.875,bilinear,+6.638,+2.846,-11
 deit_tiny_patch16_224,80.009,19.991,94.445,5.555,5.72,224,0.900,bicubic,+7.849,+3.333,+4
@@ -506,14 +510,13 @@ vgg11_bn,77.926,22.074,93.228,6.772,132.87,224,0.875,bilinear,+7.564,+3.422,+1
 xcit_nano_12_p16_224,77.909,22.091,93.437,6.563,3.05,224,1.000,bicubic,+7.937,+3.679,+2
 regnety_002,77.417,22.583,92.916,7.084,3.16,224,0.875,bicubic,+7.135,+3.372,0
 mixer_l16_224,77.294,22.706,90.557,9.443,208.20,224,0.875,bicubic,+5.228,+2.903,-8
-resnet18,77.276,22.724,92.760,7.240,11.69,224,0.875,bilinear,+7.537,+3.674,+1
+resnet18,77.276,22.724,92.760,7.240,11.69,224,0.875,bilinear,+7.536,+3.674,+1
 vgg13,77.234,22.766,92.702,7.298,133.05,224,0.875,bilinear,+7.296,+3.444,-1
 vgg11,76.397,23.603,92.171,7.829,132.86,224,0.875,bilinear,+7.349,+3.535,0
 regnetx_002,76.102,23.898,92.205,7.795,2.68,224,0.875,bicubic,+7.352,+3.645,0
-dla60x_c,75.656,24.344,92.164,7.836,1.32,224,0.875,bilinear,+7.744,+3.746,+2
-botnet26t_256,75.146,24.854,91.996,8.004,12.49,256,0.950,bicubic,+6.600,+3.300,-1
+dla60x_c,75.656,24.344,92.164,7.836,1.32,224,0.875,bilinear,+7.744,+3.746,+1
 tf_mobilenetv3_small_100,74.736,25.264,91.274,8.726,2.54,224,0.875,bilinear,+6.810,+3.598,-1
 dla46x_c,73.645,26.355,91.110,8.890,1.07,224,0.875,bilinear,+7.669,+4.122,0
 tf_mobilenetv3_small_075,72.816,27.184,90.031,9.969,2.04,224,0.875,bilinear,+7.096,+3.895,0
 dla46_c,72.607,27.393,90.495,9.505,1.30,224,0.875,bilinear,+7.737,+4.201,0
-tf_mobilenetv3_small_minimal_100,70.107,29.893,88.516,11.485,2.04,224,0.875,bilinear,+7.199,+4.269,0
+tf_mobilenetv3_small_minimal_100,70.107,29.893,88.516,11.485,2.04,224,0.875,bilinear,+7.199,+4.270,0

results/results-imagenet.csv

@@ -113,8 +113,8 @@ xcit_small_12_p16_224_dist,83.350,16.650,96.422,3.578,26.25,224,1.000,bicubic
 vit_base_patch32_384,83.346,16.654,96.844,3.156,88.30,384,1.000,bicubic
 xcit_small_12_p8_224,83.346,16.654,96.476,3.524,26.21,224,1.000,bicubic
 tf_efficientnet_b4_ap,83.258,16.742,96.396,3.604,19.34,380,0.922,bicubic
-swin_small_patch4_window7_224,83.226,16.774,96.330,3.670,49.61,224,0.900,bicubic
 swsl_resnext101_32x4d,83.226,16.774,96.768,3.232,44.18,224,0.875,bilinear
+swin_small_patch4_window7_224,83.226,16.774,96.330,3.670,49.61,224,0.900,bicubic
 twins_pcpvt_large,83.138,16.862,96.608,3.392,60.99,224,0.900,bicubic
 twins_svt_base,83.124,16.876,96.428,3.572,56.07,224,0.900,bicubic
 jx_nest_small,83.118,16.882,96.332,3.668,38.35,224,0.875,bicubic
@@ -178,20 +178,22 @@ twins_svt_small,81.682,18.318,95.678,4.322,24.06,224,0.900,bicubic
 tf_efficientnet_b3,81.646,18.354,95.720,4.280,12.23,300,0.904,bicubic
 rexnet_200,81.626,18.374,95.672,4.328,16.37,224,0.875,bicubic
 ssl_resnext101_32x8d,81.600,18.400,96.046,3.954,88.79,224,0.875,bilinear
+halonet50ts,81.548,18.452,95.312,4.688,22.73,256,0.940,bicubic
 tf_efficientnet_lite4,81.540,18.460,95.660,4.340,13.01,380,0.920,bilinear
 crossvit_15_240,81.526,18.474,95.694,4.306,27.53,240,0.875,bicubic
+halo2botnet50ts_256,81.520,18.480,95.258,4.742,22.64,256,0.950,bicubic
 tnt_s_patch16_224,81.514,18.486,95.744,4.256,23.76,224,0.900,bicubic
 vit_large_patch32_384,81.506,18.494,96.086,3.914,306.63,384,1.000,bicubic
 levit_256,81.502,18.498,95.480,4.520,18.89,224,0.900,bicubic
 tresnet_l,81.484,18.516,95.620,4.380,55.99,224,0.875,bilinear
 wide_resnet50_2,81.450,18.550,95.518,4.482,68.88,224,0.875,bicubic
 jx_nest_tiny,81.434,18.566,95.620,4.380,17.06,224,0.875,bicubic
+lamhalobotnet50ts_256,81.422,18.578,95.056,4.944,22.57,256,0.950,bicubic
 convit_small,81.412,18.588,95.746,4.254,27.78,224,0.875,bicubic
 swin_tiny_patch4_window7_224,81.386,18.614,95.536,4.464,28.29,224,0.900,bicubic
 vit_small_patch16_224,81.386,18.614,96.130,3.870,22.05,224,0.900,bicubic
 tf_efficientnet_b1_ns,81.384,18.616,95.738,4.262,7.79,240,0.882,bicubic
 convmixer_1536_20,81.376,18.624,95.610,4.390,51.63,224,0.960,bicubic
-halonet50ts,81.350,18.650,95.284,4.716,22.73,256,0.940,bicubic
 gernet_l,81.346,18.654,95.536,4.464,31.08,256,0.875,bilinear
 legacy_senet154,81.326,18.674,95.506,4.494,115.09,224,0.875,bilinear
 efficientnet_el,81.306,18.694,95.536,4.464,10.59,300,0.904,bicubic
@@ -200,6 +202,7 @@ seresnext50_32x4d,81.268,18.732,95.626,4.374,27.56,224,0.875,bicubic
 gluon_senet154,81.224,18.776,95.352,4.648,115.09,224,0.875,bicubic
 xcit_tiny_12_p8_224_dist,81.214,18.786,95.606,4.394,6.71,224,1.000,bicubic
 deit_small_distilled_patch16_224,81.202,18.798,95.378,4.622,22.44,224,0.900,bicubic
+lambda_resnet50ts,81.166,18.834,95.096,4.904,21.54,256,0.950,bicubic
 resmlp_36_distilled_224,81.154,18.846,95.496,4.504,44.69,224,0.875,bicubic
 swsl_resnet50,81.146,18.854,95.978,4.022,25.56,224,0.875,bilinear
 resnest50d_4s2x40d,81.120,18.880,95.560,4.440,30.42,224,0.875,bicubic
@@ -251,8 +254,8 @@ ssl_resnext50_32x4d,80.302,19.698,95.418,4.582,25.03,224,0.875,bilinear
 efficientnet_el_pruned,80.288,19.712,95.222,4.778,10.59,300,0.904,bicubic
 gluon_resnet101_v1s,80.282,19.718,95.162,4.838,44.67,224,0.875,bicubic
 regnetx_320,80.248,19.752,95.026,4.974,107.81,224,0.875,bicubic
-seresnet50,80.248,19.752,95.070,4.930,28.09,224,0.875,bicubic
 tf_efficientnet_el,80.248,19.752,95.124,4.876,10.59,300,0.904,bicubic
+seresnet50,80.248,19.752,95.070,4.930,28.09,224,0.875,bicubic
 vit_base_patch16_sam_224,80.242,19.758,94.762,5.238,86.57,224,0.900,bicubic
 legacy_seresnext101_32x4d,80.222,19.778,95.012,4.988,48.96,224,0.875,bilinear
 repvgg_b3g4,80.218,19.782,95.104,4.896,83.83,224,0.875,bilinear
@@ -276,9 +279,9 @@ regnety_080,79.872,20.128,94.832,5.168,39.18,224,0.875,bicubic
 resnetrs50,79.870,20.130,94.970,5.030,35.69,224,0.910,bicubic
 deit_small_patch16_224,79.866,20.134,95.056,4.944,22.05,224,0.900,bicubic
 levit_192,79.860,20.140,94.802,5.198,10.95,224,0.900,bicubic
-dpn131,79.834,20.166,94.712,5.288,79.25,224,0.875,bicubic
 ecaresnet26t,79.834,20.166,95.084,4.916,16.01,320,0.950,bicubic
 regnetx_160,79.834,20.166,94.824,5.176,54.28,224,0.875,bicubic
+dpn131,79.834,20.166,94.712,5.288,79.25,224,0.875,bicubic
 tf_efficientnet_lite3,79.820,20.180,94.910,5.090,8.20,300,0.904,bilinear
 resnext50_32x4d,79.800,20.200,94.614,5.386,25.03,224,0.875,bicubic
 resmlp_36_224,79.776,20.224,94.886,5.114,44.69,224,0.875,bicubic
@@ -307,11 +310,13 @@ tf_efficientnet_cc_b1_8e,79.326,20.674,94.368,5.632,39.72,240,0.882,bicubic
 hrnet_w48,79.322,20.678,94.514,5.486,77.47,224,0.875,bilinear
 resnext101_32x8d,79.312,20.688,94.522,5.478,88.79,224,0.875,bilinear
 ese_vovnet39b,79.304,20.696,94.724,5.276,24.57,224,0.875,bicubic
-resnetblur50,79.300,20.700,94.636,5.364,25.56,224,0.875,bicubic
 gluon_resnet101_v1b,79.300,20.700,94.530,5.470,44.55,224,0.875,bicubic
+resnetblur50,79.300,20.700,94.636,5.364,25.56,224,0.875,bicubic
 nf_regnet_b1,79.296,20.704,94.742,5.258,10.22,288,0.900,bicubic
 pit_xs_distilled_224,79.294,20.706,94.374,5.626,11.00,224,0.900,bicubic
 tf_efficientnet_b1_ap,79.274,20.726,94.302,5.698,7.79,240,0.882,bicubic
+eca_botnext26ts_256,79.274,20.726,94.606,5.394,10.59,256,0.950,bicubic
+botnet26t_256,79.260,20.740,94.534,5.466,12.49,256,0.950,bicubic
 efficientnet_em,79.260,20.740,94.792,5.208,6.90,240,0.882,bicubic
 ssl_resnet50,79.236,20.764,94.832,5.168,25.56,224,0.875,bilinear
 regnety_040,79.228,20.772,94.646,5.354,20.65,224,0.875,bicubic
@@ -327,8 +332,8 @@ gluon_resnet50_v1d,79.064,20.936,94.460,5.540,25.58,224,0.875,bicubic
 regnetx_064,79.060,20.940,94.466,5.534,26.21,224,0.875,bicubic
 xception,79.048,20.952,94.396,5.604,22.86,299,0.897,bicubic
 resnet32ts,79.020,20.980,94.362,5.638,17.96,256,0.900,bicubic
-mixnet_l,78.980,21.020,94.180,5.820,7.33,224,0.875,bicubic
 res2net50_26w_8s,78.980,21.020,94.284,5.716,48.40,224,0.875,bilinear
+mixnet_l,78.980,21.020,94.180,5.820,7.33,224,0.875,bicubic
 lambda_resnet26rpt_256,78.968,21.032,94.428,5.572,10.99,256,0.940,bicubic
 hrnet_w40,78.926,21.074,94.478,5.522,57.56,224,0.875,bilinear
 hrnet_w44,78.890,21.110,94.382,5.618,67.06,224,0.875,bilinear
@@ -352,8 +357,8 @@ resnest26d,78.478,21.522,94.296,5.704,17.07,224,0.875,bilinear
 levit_128,78.466,21.534,94.010,5.990,9.21,224,0.900,bicubic
 dla60_res2net,78.462,21.538,94.208,5.792,20.85,224,0.875,bilinear
 vit_tiny_patch16_384,78.446,21.554,94.544,5.456,5.79,384,1.000,bicubic
-dla60_res2next,78.442,21.558,94.158,5.842,17.03,224,0.875,bilinear
 hrnet_w32,78.442,21.558,94.196,5.804,41.23,224,0.875,bilinear
+dla60_res2next,78.442,21.558,94.158,5.842,17.03,224,0.875,bilinear
 coat_tiny,78.434,21.566,94.034,5.966,5.50,224,0.900,bicubic
 selecsls60b,78.408,21.592,94.176,5.824,32.77,224,0.875,bicubic
 legacy_seresnet101,78.384,21.616,94.264,5.736,49.33,224,0.875,bilinear
@@ -383,8 +388,8 @@ mobilenetv3_large_100_miil,77.912,22.088,92.904,7.096,5.48,224,0.875,bilinear
 tf_efficientnet_cc_b0_8e,77.908,22.092,93.656,6.344,24.01,224,0.875,bicubic
 resnet26t,77.872,22.128,93.834,6.166,16.01,256,0.940,bicubic
 regnety_016,77.864,22.136,93.724,6.276,11.20,224,0.875,bicubic
-rexnet_100,77.860,22.140,93.876,6.124,4.80,224,0.875,bicubic
 tf_inception_v3,77.860,22.140,93.646,6.354,23.83,299,0.875,bicubic
+rexnet_100,77.860,22.140,93.876,6.124,4.80,224,0.875,bicubic
 seresnext26ts,77.848,22.152,93.788,6.212,10.39,256,0.900,bicubic
 gcresnext26ts,77.820,22.180,93.826,6.174,10.48,256,0.900,bicubic
 xcit_nano_12_p8_384_dist,77.818,22.182,94.034,5.966,3.05,384,1.000,bicubic
@@ -429,8 +434,8 @@ resnet26d,76.690,23.310,93.148,6.852,16.01,224,0.875,bicubic
 tf_efficientnet_lite1,76.664,23.336,93.234,6.766,5.42,240,0.882,bicubic
 resmlp_12_224,76.654,23.346,93.172,6.828,15.35,224,0.875,bicubic
 mixer_b16_224,76.622,23.378,92.228,7.772,59.88,224,0.875,bicubic
-densenetblur121d,76.590,23.410,93.192,6.808,8.00,224,0.875,bicubic
 tf_efficientnet_es,76.590,23.410,93.212,6.788,5.44,224,0.875,bicubic
+densenetblur121d,76.590,23.410,93.192,6.808,8.00,224,0.875,bicubic
 levit_128s,76.538,23.462,92.864,7.136,7.78,224,0.900,bicubic
 hardcorenas_b,76.530,23.470,92.752,7.248,5.18,224,0.875,bilinear
 mobilenetv2_140,76.516,23.484,93.000,7.000,6.11,224,0.875,bicubic
@@ -439,8 +444,8 @@ xcit_nano_12_p8_224_dist,76.330,23.670,93.086,6.914,3.05,224,1.000,bicubic
 regnety_008,76.320,23.680,93.068,6.932,6.26,224,0.875,bicubic
 dpn68,76.294,23.706,92.962,7.038,12.61,224,0.875,bicubic
 tv_resnet50,76.152,23.848,92.878,7.122,25.56,224,0.875,bilinear
-mixnet_s,75.994,24.006,92.792,7.208,4.13,224,0.875,bicubic
 vit_small_patch32_224,75.994,24.006,93.276,6.724,22.88,224,0.900,bicubic
+mixnet_s,75.994,24.006,92.792,7.208,4.13,224,0.875,bicubic
 vit_tiny_r_s16_p8_384,75.972,24.028,93.272,6.728,6.36,384,1.000,bicubic
 hardcorenas_a,75.912,24.088,92.514,7.486,5.26,224,0.875,bilinear
 densenet169,75.898,24.102,93.024,6.976,14.15,224,0.875,bicubic
@@ -477,7 +482,6 @@ regnety_004,74.012,25.988,91.766,8.234,4.34,224,0.875,bicubic
 ghostnet_100,73.984,26.016,91.460,8.540,5.18,224,0.875,bilinear
 crossvit_9_240,73.982,26.018,91.970,8.030,8.55,240,0.875,bicubic
 xcit_nano_12_p8_224,73.912,26.088,92.166,7.834,3.05,224,1.000,bicubic
-eca_botnext26ts_256,73.878,26.122,91.788,8.212,10.59,256,0.950,bicubic
 regnetx_006,73.846,26.154,91.682,8.318,6.20,224,0.875,bicubic
 vit_base_patch32_sam_224,73.700,26.300,91.008,8.992,88.22,224,0.900,bicubic
 tf_mobilenetv3_large_075,73.450,26.550,91.340,8.660,3.99,224,0.875,bilinear
@@ -510,7 +514,6 @@ vgg13,69.938,30.062,89.258,10.742,133.05,224,0.875,bilinear
 resnet18,69.740,30.260,89.086,10.914,11.69,224,0.875,bilinear
 vgg11,69.048,30.952,88.636,11.364,132.86,224,0.875,bilinear
 regnetx_002,68.750,31.250,88.560,11.440,2.68,224,0.875,bicubic
-botnet26t_256,68.546,31.454,88.696,11.304,12.49,256,0.950,bicubic
 tf_mobilenetv3_small_100,67.926,32.074,87.676,12.324,2.54,224,0.875,bilinear
 dla60x_c,67.912,32.088,88.418,11.582,1.32,224,0.875,bilinear
 dla46x_c,65.976,34.024,86.988,13.012,1.07,224,0.875,bilinear

results/results-imagenetv2-matched-frequency.csv

@@ -71,7 +71,7 @@ pit_b_distilled_224,74.080,25.920,91.590,8.410,74.79,224,0.900,bicubic,-10.078,-
 vit_base_patch16_224,74.070,25.930,92.400,7.600,86.57,224,0.900,bicubic,-10.470,-4.906,-8
 efficientnetv2_rw_s,74.020,25.980,91.750,8.250,23.94,384,1.000,bicubic,-9.810,-4.972,+23
 crossvit_18_dagger_408,74.010,25.990,91.300,8.700,44.61,408,1.000,bicubic,-10.174,-5.522,+5
-swsl_resnext101_32x4d,74.000,26.000,91.970,8.030,44.18,224,0.875,bilinear,-9.226,-4.798,+43
+swsl_resnext101_32x4d,74.000,26.000,91.970,8.030,44.18,224,0.875,bilinear,-9.226,-4.360,+42
 vit_base_patch16_224_miil,74.000,26.000,91.600,8.400,86.54,224,0.875,bilinear,-10.276,-5.198,-1
 tf_efficientnetv2_s,73.980,26.020,91.430,8.570,21.46,384,1.000,bicubic,-9.918,-5.268,+14
 resnest269e,73.920,26.080,91.990,8.010,110.93,416,0.928,bicubic,-10.604,-4.996,-13
@@ -82,8 +82,8 @@ xcit_small_12_p8_224_dist,73.880,26.120,91.700,8.300,26.21,224,1.000,bicubic,-10
 resnetrs420,73.870,26.130,91.700,8.300,191.89,416,1.000,bicubic,-11.138,-5.426,-32
 tf_efficientnet_b3_ns,73.770,26.230,91.850,8.150,12.23,300,0.904,bicubic,-10.272,-5.058,+2
 regnetz_d,73.760,26.240,91.850,8.150,27.58,320,0.950,bicubic,-10.274,-5.020,+2
-swsl_resnext101_32x16d,73.670,26.330,92.120,7.880,194.03,224,0.875,bilinear,-9.684,-4.716,+25
-ig_resnext101_32x8d,73.670,26.330,92.190,7.810,88.79,224,0.875,bilinear,-9.040,-4.450,+49
+ig_resnext101_32x8d,73.670,26.330,92.190,7.810,88.79,224,0.875,bilinear,-9.040,-4.450,+48
+swsl_resnext101_32x16d,73.670,26.330,92.120,7.880,194.03,224,0.875,bilinear,-9.684,-4.716,+26
 xcit_medium_24_p16_224_dist,73.610,26.390,91.450,8.550,84.40,224,1.000,bicubic,-10.668,-5.492,-14
 xcit_tiny_24_p8_384_dist,73.460,26.540,91.640,8.360,12.11,384,1.000,bicubic,-10.304,-5.064,+11
 resnetrs270,73.450,26.550,91.460,8.540,129.86,352,1.000,bicubic,-10.990,-5.694,-22
@@ -97,9 +97,9 @@ resnet152d,73.250,26.750,91.210,8.790,60.21,320,1.000,bicubic,-10.414,-5.524,+8
 vit_small_patch16_384,73.180,26.820,91.900,8.100,22.20,384,1.000,bicubic,-10.614,-5.208,+1
 resnetrs200,73.170,26.830,91.110,8.890,93.21,320,1.000,bicubic,-10.888,-5.764,-16
 jx_nest_base,73.160,26.840,91.000,9.000,67.72,224,0.875,bicubic,-10.394,-5.364,+7
-xcit_small_24_p16_224_dist,73.150,26.850,91.430,8.570,47.67,224,1.000,bicubic,-10.724,-5.298,-11
-resnetv2_152x4_bitm,73.150,26.850,91.780,8.220,936.53,480,1.000,bilinear,-11.788,-5.678,-47
-xcit_small_24_p8_224,73.150,26.850,91.210,8.790,47.63,224,1.000,bicubic,-10.696,-5.422,-8
+xcit_small_24_p8_224,73.150,26.850,91.210,8.790,47.63,224,1.000,bicubic,-10.696,-5.422,-9
+xcit_small_24_p16_224_dist,73.150,26.850,91.430,8.570,47.67,224,1.000,bicubic,-10.724,-5.298,-9
+resnetv2_152x4_bitm,73.150,26.850,91.780,8.220,936.53,480,1.000,bilinear,-11.788,-5.678,-48
 resnetrs350,73.130,26.870,91.180,8.820,163.96,384,1.000,bicubic,-11.582,-5.810,-42
 xcit_medium_24_p8_224,73.090,26.910,90.440,9.560,84.32,224,1.000,bicubic,-10.646,-5.946,-4
 resnetv2_152x2_bitm,73.000,27.000,91.990,8.010,236.34,448,1.000,bilinear,-11.452,-5.446,-40
@@ -141,10 +141,10 @@ xcit_tiny_24_p16_384_dist,72.070,27.930,90.510,9.490,12.12,384,1.000,bicubic,-10
 crossvit_18_dagger_240,72.020,27.980,90.100,9.900,44.27,240,0.875,bicubic,-10.486,-5.972,+3
 xcit_tiny_12_p8_384_dist,71.820,28.180,90.700,9.300,6.71,384,1.000,bicubic,-10.572,-5.518,+6
 resnetv2_50x3_bitm,71.770,28.230,91.280,8.720,217.32,448,1.000,bilinear,-12.214,-5.850,-55
-swin_small_patch4_window7_224,71.750,28.250,90.280,9.720,49.61,224,0.900,bicubic,-11.476,-6.050,-28
+swin_small_patch4_window7_224,71.750,28.250,90.280,9.720,49.61,224,0.900,bicubic,-11.476,-6.488,-27
 crossvit_15_dagger_240,71.650,28.350,89.800,10.200,28.21,240,0.875,bicubic,-10.660,-6.162,+9
 pit_b_224,71.650,28.350,89.280,10.720,73.76,224,0.900,bicubic,-10.794,-6.432,0
-swsl_resnet50,71.640,28.360,90.500,9.500,25.56,224,0.875,bilinear,-9.506,-5.478,+57
+swsl_resnet50,71.640,28.360,90.500,9.500,25.56,224,0.875,bilinear,-9.506,-5.478,+60
 eca_nfnet_l0,71.580,28.420,91.010,8.990,24.14,288,1.000,bicubic,-11.012,-5.476,-11
 resnet61q,71.550,28.450,90.010,9.990,36.85,288,1.000,bicubic,-10.972,-6.124,-7
 xcit_large_24_p16_224,71.540,28.460,89.200,10.800,189.10,224,1.000,bicubic,-11.358,-6.682,-23
@@ -163,63 +163,66 @@ ssl_resnext101_32x16d,71.170,28.830,90.460,9.540,194.03,224,0.875,bilinear,-10.6
 ecaresnet50t,71.110,28.890,90.410,9.590,25.57,320,0.950,bicubic,-11.254,-5.732,-12
 xcit_small_24_p16_224,71.090,28.910,89.530,10.470,47.67,224,1.000,bicubic,-11.488,-6.470,-25
 xcit_small_12_p16_224,71.070,28.930,89.730,10.270,26.25,224,1.000,bicubic,-10.906,-6.088,+3
-crossvit_base_240,71.070,28.930,89.780,10.220,105.03,240,0.875,bicubic,-11.136,-6.048,-4
 resnet51q,71.070,28.930,90.070,9.930,35.70,288,1.000,bilinear,-11.298,-6.106,-16
-convmixer_1536_20,71.050,28.950,89.470,10.530,51.63,224,0.960,bicubic,-10.326,-6.140,+25
+crossvit_base_240,71.070,28.930,89.780,10.220,105.03,240,0.875,bicubic,-11.136,-6.048,-4
+convmixer_1536_20,71.050,28.950,89.470,10.530,51.63,224,0.960,bicubic,-10.326,-6.140,+28
 coat_lite_small,71.010,28.990,89.460,10.540,19.84,224,0.900,bicubic,-11.292,-6.400,-14
 tf_efficientnet_b3_ap,71.010,28.990,89.220,10.780,12.23,300,0.904,bicubic,-10.812,-6.400,+5
 deit_base_patch16_224,70.970,29.030,89.170,10.830,86.57,224,0.900,bicubic,-11.014,-6.572,-2
 xcit_medium_24_p16_224,70.960,29.040,89.460,10.540,84.40,224,1.000,bicubic,-11.666,-6.516,-36
-tnt_s_patch16_224,70.920,29.080,89.510,10.490,23.76,224,0.900,bicubic,-10.594,-6.234,+10
-xcit_tiny_12_p8_224_dist,70.910,29.090,89.720,10.280,6.71,224,1.000,bicubic,-10.304,-5.886,+27
-vit_large_patch32_384,70.890,29.110,90.460,9.540,306.63,384,1.000,bicubic,-10.616,-5.626,+9
-resnest50d_4s2x40d,70.850,29.150,89.520,10.480,30.42,224,0.875,bicubic,-10.270,-6.040,+29
+tnt_s_patch16_224,70.920,29.080,89.510,10.490,23.76,224,0.900,bicubic,-10.594,-6.234,+12
+xcit_tiny_12_p8_224_dist,70.910,29.090,89.720,10.280,6.71,224,1.000,bicubic,-10.304,-5.886,+29
+vit_large_patch32_384,70.890,29.110,90.460,9.540,306.63,384,1.000,bicubic,-10.616,-5.626,+11
+resnest50d_4s2x40d,70.850,29.150,89.520,10.480,30.42,224,0.875,bicubic,-10.270,-6.040,+32
 visformer_small,70.850,29.150,89.310,10.690,40.22,224,0.900,bicubic,-11.246,-6.568,-12
 rexnet_200,70.840,29.160,89.800,10.200,16.37,224,0.875,bicubic,-10.786,-5.872,+1
 tresnet_m_448,70.770,29.230,88.690,11.310,31.39,448,0.875,bilinear,-10.944,-6.880,-3
-jx_nest_tiny,70.720,29.280,89.840,10.160,17.06,224,0.875,bicubic,-10.714,-5.780,+8
+jx_nest_tiny,70.720,29.280,89.840,10.160,17.06,224,0.875,bicubic,-10.714,-5.780,+10
 resnetrs101,70.700,29.300,89.620,10.380,63.62,288,0.940,bicubic,-11.594,-6.382,-24
-wide_resnet50_2,70.690,29.310,89.120,10.880,68.88,224,0.875,bicubic,-10.760,-6.398,+5
-tresnet_l,70.680,29.320,89.640,10.360,55.99,224,0.875,bilinear,-10.804,-5.980,+3
-vit_small_patch16_224,70.670,29.330,90.090,9.910,22.05,224,0.900,bicubic,-10.716,-6.040,+7
-convit_small,70.660,29.340,89.570,10.430,27.78,224,0.875,bicubic,-10.752,-6.176,+4
+wide_resnet50_2,70.690,29.310,89.120,10.880,68.88,224,0.875,bicubic,-10.760,-6.398,+7
+tresnet_l,70.680,29.320,89.640,10.360,55.99,224,0.875,bilinear,-10.804,-5.980,+5
+vit_small_patch16_224,70.670,29.330,90.090,9.910,22.05,224,0.900,bicubic,-10.716,-6.040,+10
+convit_small,70.660,29.340,89.570,10.430,27.78,224,0.875,bicubic,-10.752,-6.176,+7
 resnetv2_101x1_bitm,70.630,29.370,90.950,9.050,44.54,448,1.000,bilinear,-11.700,-5.578,-33
-tf_efficientnet_b1_ns,70.630,29.370,89.930,10.070,7.79,240,0.882,bicubic,-10.754,-5.808,+5
+tf_efficientnet_b1_ns,70.630,29.370,89.930,10.070,7.79,240,0.882,bicubic,-10.754,-5.808,+8
 tf_efficientnetv2_b3,70.630,29.370,89.370,10.630,14.36,300,0.904,bicubic,-11.324,-6.414,-17
-levit_384,70.610,29.390,89.240,10.760,39.13,224,0.900,bicubic,-11.982,-6.774,-51
-crossvit_small_240,70.580,29.420,89.410,10.590,26.86,240,0.875,bicubic,-10.450,-6.056,+20
-vit_small_r26_s32_224,70.560,29.440,90.020,9.980,36.43,224,0.900,bicubic,-11.278,-6.006,-17
-cait_xxs24_384,70.550,29.450,89.780,10.220,12.03,384,1.000,bicubic,-10.404,-5.858,+23
-twins_pcpvt_small,70.490,29.510,89.060,10.940,24.11,224,0.900,bicubic,-10.614,-6.582,+13
+halo2botnet50ts_256,70.610,29.390,89.020,10.980,22.64,256,0.950,bicubic,-10.910,-6.238,-5
+levit_384,70.610,29.390,89.240,10.760,39.13,224,0.900,bicubic,-11.982,-6.774,-52
+crossvit_small_240,70.580,29.420,89.410,10.590,26.86,240,0.875,bicubic,-10.450,-6.056,+22
+vit_small_r26_s32_224,70.560,29.440,90.020,9.980,36.43,224,0.900,bicubic,-11.278,-6.006,-18
+cait_xxs24_384,70.550,29.450,89.780,10.220,12.03,384,1.000,bicubic,-10.404,-5.858,+25
+lamhalobotnet50ts_256,70.530,29.470,88.910,11.090,22.57,256,0.950,bicubic,-10.892,-6.146,-3
+twins_pcpvt_small,70.490,29.510,89.060,10.940,24.11,224,0.900,bicubic,-10.614,-6.582,+14
 legacy_senet154,70.480,29.520,88.960,11.040,115.09,224,0.875,bilinear,-10.846,-6.546,+2
+gluon_seresnext101_64x4d,70.470,29.530,89.180,10.820,88.23,224,0.875,bicubic,-10.400,-6.126,+25
 coat_mini,70.470,29.530,89.580,10.420,10.34,224,0.900,bicubic,-10.812,-5.814,+3
-gluon_seresnext101_64x4d,70.470,29.530,89.180,10.820,88.23,224,0.875,bicubic,-10.400,-6.126,+24
 deit_small_distilled_patch16_224,70.460,29.540,89.400,10.600,22.44,224,0.900,bicubic,-10.742,-5.978,+5
 seresnext50_32x4d,70.450,29.550,89.130,10.870,27.56,224,0.875,bicubic,-10.818,-6.496,+1
-tf_efficientnet_b3,70.400,29.600,89.270,10.730,12.23,300,0.904,bicubic,-11.246,-6.450,-22
+tf_efficientnet_b3,70.400,29.600,89.270,10.730,12.23,300,0.904,bicubic,-11.246,-6.450,-23
 regnetz_b,70.400,29.600,89.440,10.560,9.72,288,0.940,bicubic,-10.318,-6.034,+28
 gernet_l,70.380,29.620,88.940,11.060,31.08,256,0.875,bilinear,-10.966,-6.596,-6
-resnest50d_1s4x24d,70.360,29.640,89.140,10.860,25.68,224,0.875,bicubic,-10.640,-6.186,+10
-ssl_resnext101_32x4d,70.360,29.640,89.810,10.190,44.18,224,0.875,bilinear,-10.562,-5.920,+15
-crossvit_15_240,70.350,29.650,89.520,10.480,27.53,240,0.875,bicubic,-11.176,-6.174,-22
-gluon_senet154,70.340,29.660,88.960,11.040,115.09,224,0.875,bicubic,-10.884,-6.392,-5
-twins_svt_small,70.330,29.670,89.300,10.700,24.06,224,0.900,bicubic,-11.352,-6.378,-29
-halonet50ts,70.250,29.750,88.710,11.290,22.73,256,0.940,bicubic,-11.100,-6.574,-13
-resnest50d,70.250,29.750,88.630,11.370,27.48,224,0.875,bilinear,-10.712,-6.748,+6
-tf_efficientnet_lite4,70.190,29.810,89.040,10.960,13.01,380,0.920,bilinear,-11.350,-6.620,-28
-gluon_resnet152_v1s,70.120,29.880,88.890,11.110,60.32,224,0.875,bicubic,-10.900,-6.532,+1
-resmlp_36_distilled_224,70.120,29.880,89.060,10.940,44.69,224,0.875,bicubic,-11.034,-6.436,-8
+halonet50ts,70.370,29.630,88.760,11.240,22.73,256,0.940,bicubic,-11.178,-6.552,-23
+ssl_resnext101_32x4d,70.360,29.640,89.810,10.190,44.18,224,0.875,bilinear,-10.562,-5.920,+16
+resnest50d_1s4x24d,70.360,29.640,89.140,10.860,25.68,224,0.875,bicubic,-10.640,-6.186,+9
+crossvit_15_240,70.350,29.650,89.520,10.480,27.53,240,0.875,bicubic,-11.176,-6.174,-24
+gluon_senet154,70.340,29.660,88.960,11.040,115.09,224,0.875,bicubic,-10.884,-6.392,-6
+twins_svt_small,70.330,29.670,89.300,10.700,24.06,224,0.900,bicubic,-11.352,-6.378,-32
+resnest50d,70.250,29.750,88.630,11.370,27.48,224,0.875,bilinear,-10.712,-6.748,+7
+tf_efficientnet_lite4,70.190,29.810,89.040,10.960,13.01,380,0.920,bilinear,-11.350,-6.620,-29
+gluon_resnet152_v1s,70.120,29.880,88.890,11.110,60.32,224,0.875,bicubic,-10.900,-6.532,+2
+resmlp_36_distilled_224,70.120,29.880,89.060,10.940,44.69,224,0.875,bicubic,-11.034,-6.436,-7
 efficientnet_el,70.060,29.940,89.150,10.850,10.59,300,0.904,bicubic,-11.246,-6.386,-15
-inception_resnet_v2,70.030,29.970,88.620,11.380,55.84,299,0.897,bicubic,-10.418,-6.688,+27
-haloregnetz_b,69.980,30.020,88.850,11.150,11.68,224,0.940,bicubic,-11.062,-6.350,-6
+inception_resnet_v2,70.030,29.970,88.620,11.380,55.84,299,0.897,bicubic,-10.418,-6.688,+28
+haloregnetz_b,69.980,30.020,88.850,11.150,11.68,224,0.940,bicubic,-11.062,-6.350,-5
+repvgg_b3,69.940,30.060,88.660,11.340,123.09,224,0.875,bilinear,-10.576,-6.604,+20
 gluon_seresnext101_32x4d,69.940,30.060,88.870,11.130,48.96,224,0.875,bicubic,-10.936,-6.422,+4
-repvgg_b3,69.940,30.060,88.660,11.340,123.09,224,0.875,bilinear,-10.576,-6.604,+18
 levit_256,69.930,30.070,89.240,10.760,18.89,224,0.900,bicubic,-11.572,-6.240,-32
-regnety_320,69.870,30.130,88.760,11.240,145.05,224,0.875,bicubic,-10.924,-6.486,+5
-gluon_resnet152_v1d,69.810,30.190,88.490,11.510,60.21,224,0.875,bicubic,-10.666,-6.712,+17
-pit_s_224,69.800,30.200,88.830,11.170,23.46,224,0.900,bicubic,-11.300,-6.504,-13
-sehalonet33ts,69.770,30.230,88.580,11.420,13.69,256,0.940,bicubic,-11.212,-6.692,-8
-ecaresnet101d_pruned,69.710,30.290,89.330,10.670,24.88,224,0.875,bicubic,-11.102,-6.310,0
+regnety_320,69.870,30.130,88.760,11.240,145.05,224,0.875,bicubic,-10.924,-6.486,+6
+gluon_resnet152_v1d,69.810,30.190,88.490,11.510,60.21,224,0.875,bicubic,-10.666,-6.712,+18
+pit_s_224,69.800,30.200,88.830,11.170,23.46,224,0.900,bicubic,-11.300,-6.504,-12
+sehalonet33ts,69.770,30.230,88.580,11.420,13.69,256,0.940,bicubic,-11.212,-6.692,-7
+ecaresnet101d_pruned,69.710,30.290,89.330,10.670,24.88,224,0.875,bicubic,-11.102,-6.310,+1
+lambda_resnet50ts,69.710,30.290,88.830,11.170,21.54,256,0.950,bicubic,-11.456,-6.266,-20
 xcit_tiny_24_p16_224_dist,69.610,30.390,88.730,11.270,12.12,224,1.000,bicubic,-10.852,-6.478,+15
 ens_adv_inception_resnet_v2,69.590,30.410,88.350,11.650,55.84,299,0.897,bicubic,-10.388,-6.586,+46
 ssl_resnext50_32x4d,69.590,30.410,89.310,10.690,25.03,224,0.875,bilinear,-10.712,-6.108,+25
@@ -227,13 +230,13 @@ ecaresnet50d,69.580,30.420,89.290,10.710,25.58,224,0.875,bicubic,-11.040,-6.018,
 gcresnet50t,69.570,30.430,88.920,11.080,25.90,256,0.900,bicubic,-11.368,-6.520,-10
 efficientnet_b3_pruned,69.550,30.450,88.770,11.230,9.86,300,0.904,bicubic,-11.308,-6.470,-7
 repvgg_b3g4,69.520,30.480,88.500,11.500,83.83,224,0.875,bilinear,-10.698,-6.604,+29
-resmlp_24_distilled_224,69.510,30.490,89.010,10.990,30.02,224,0.875,bicubic,-11.250,-6.210,-7
-gernet_m,69.510,30.490,88.590,11.410,21.14,224,0.875,bilinear,-11.216,-6.588,-4
+resmlp_24_distilled_224,69.510,30.490,89.010,10.990,30.02,224,0.875,bicubic,-11.250,-6.210,-6
+gernet_m,69.510,30.490,88.590,11.410,21.14,224,0.875,bilinear,-11.216,-6.588,-5
 convmixer_768_32,69.500,30.500,88.950,11.050,21.11,224,0.960,bicubic,-10.660,-6.124,+29
 gluon_resnext101_64x4d,69.490,30.510,88.250,11.750,83.46,224,0.875,bicubic,-11.136,-6.752,-4
 xcit_tiny_12_p16_384_dist,69.470,30.530,88.970,11.030,6.72,384,1.000,bicubic,-11.474,-6.444,-18
-efficientnet_el_pruned,69.460,30.540,88.890,11.110,10.59,300,0.904,bicubic,-10.828,-6.332,+16
-swin_tiny_patch4_window7_224,69.460,30.540,89.020,10.980,28.29,224,0.900,bicubic,-11.926,-6.516,-46
+swin_tiny_patch4_window7_224,69.460,30.540,89.020,10.980,28.29,224,0.900,bicubic,-11.926,-6.516,-45
+efficientnet_el_pruned,69.460,30.540,88.890,11.110,10.59,300,0.904,bicubic,-10.828,-6.332,+15
 regnetx_320,69.440,30.560,88.140,11.860,107.81,224,0.875,bicubic,-10.808,-6.886,+16
 gcresnext50ts,69.430,30.570,88.770,11.230,15.67,256,0.900,bicubic,-11.164,-6.410,-6
 rexnet_150,69.410,30.590,88.970,11.030,9.73,224,0.875,bicubic,-10.900,-6.190,+9
@@ -248,8 +251,8 @@ tf_efficientnetv2_b2,69.090,30.910,88.150,11.850,10.10,260,0.890,bicubic,-11.124
 legacy_seresnext101_32x4d,69.060,30.940,88.080,11.920,48.96,224,0.875,bilinear,-11.162,-6.932,+9
 mixnet_xl,69.040,30.960,88.340,11.660,11.90,224,0.875,bicubic,-11.428,-6.592,-12
 regnety_120,68.980,31.020,88.190,11.810,51.82,224,0.875,bicubic,-11.406,-6.932,-7
-gluon_resnet152_v1c,68.960,31.040,87.670,12.330,60.21,224,0.875,bicubic,-10.952,-7.182,+21
-seresnet33ts,68.960,31.040,88.340,11.660,19.78,256,0.900,bicubic,-11.412,-6.774,-7
+seresnet33ts,68.960,31.040,88.340,11.660,19.78,256,0.900,bicubic,-11.412,-6.774,-6
+gluon_resnet152_v1c,68.960,31.040,87.670,12.330,60.21,224,0.875,bicubic,-10.952,-7.182,+20
 vit_small_patch32_384,68.950,31.050,89.660,10.340,22.92,384,1.000,bicubic,-11.536,-5.938,-18
 resnetv2_50,68.900,31.100,88.400,11.600,25.55,224,0.950,bicubic,-11.506,-6.680,-13
 gluon_resnext101_32x4d,68.880,31.120,88.280,11.720,44.18,224,0.875,bicubic,-11.458,-6.628,-8
@@ -257,88 +260,90 @@ hrnet_w64,68.830,31.170,88.140,11.860,128.06,224,0.875,bilinear,-10.626,-6.514,+
 gluon_resnet152_v1b,68.800,31.200,87.570,12.430,60.19,224,0.875,bicubic,-10.880,-7.166,+33
 tf_efficientnet_b2_ap,68.790,31.210,88.330,11.670,9.11,260,0.890,bicubic,-11.516,-6.702,-9
 gluon_resnet101_v1d,68.780,31.220,88.080,11.920,44.57,224,0.875,bicubic,-11.624,-6.944,-17
-xception65,68.760,31.240,88.250,11.750,39.92,299,0.903,bicubic,-10.786,-6.410,+32
-seresnet50,68.760,31.240,88.520,11.480,28.09,224,0.875,bicubic,-11.488,-6.550,-9
-gluon_xception65,68.760,31.240,87.950,12.050,39.92,299,0.903,bicubic,-10.942,-6.918,+28
-repvgg_b2g4,68.760,31.240,88.260,11.740,61.76,224,0.875,bilinear,-10.620,-6.434,+42
-eca_resnet33ts,68.760,31.240,88.520,11.480,19.68,256,0.900,bicubic,-11.336,-6.454,+4
+seresnet50,68.760,31.240,88.520,11.480,28.09,224,0.875,bicubic,-11.488,-6.550,-5
+repvgg_b2g4,68.760,31.240,88.260,11.740,61.76,224,0.875,bilinear,-10.620,-6.434,+41
+gluon_xception65,68.760,31.240,87.950,12.050,39.92,299,0.903,bicubic,-10.942,-6.918,+25
+xception65,68.760,31.240,88.250,11.750,39.92,299,0.903,bicubic,-10.786,-6.410,+35
+eca_resnet33ts,68.760,31.240,88.520,11.480,19.68,256,0.900,bicubic,-11.336,-6.454,+2
 cspdarknet53,68.730,31.270,88.540,11.460,27.64,256,0.887,bilinear,-11.320,-6.552,+3
 cspresnext50,68.720,31.280,88.020,11.980,20.57,224,0.875,bilinear,-11.332,-6.930,+1
 gcresnet33ts,68.700,31.300,88.480,11.520,19.88,256,0.900,bicubic,-11.386,-6.512,-2
 resnext50d_32x4d,68.670,31.330,88.230,11.770,25.05,224,0.875,bicubic,-10.994,-6.636,+23
-dpn131,68.660,31.340,87.220,12.780,79.25,224,0.875,bicubic,-11.174,-7.492,+10
+dpn131,68.660,31.340,87.220,12.780,79.25,224,0.875,bicubic,-11.174,-7.492,+12
 gluon_resnet101_v1s,68.650,31.350,87.720,12.280,44.67,224,0.875,bicubic,-11.632,-7.442,-18
 gmlp_s16_224,68.620,31.380,87.950,12.050,19.42,224,0.875,bicubic,-11.022,-6.672,+22
 xcit_tiny_12_p8_224,68.610,31.390,88.690,11.310,6.71,224,1.000,bicubic,-11.100,-6.368,+15
 gluon_seresnext50_32x4d,68.580,31.420,88.150,11.850,27.56,224,0.875,bicubic,-11.344,-6.678,-2
-regnetx_160,68.520,31.480,88.280,11.720,54.28,224,0.875,bicubic,-11.314,-6.544,+7
+regnetx_160,68.520,31.480,88.280,11.720,54.28,224,0.875,bicubic,-11.314,-6.544,+6
 regnety_080,68.510,31.490,88.000,12.000,39.18,224,0.875,bicubic,-11.362,-6.832,0
 deit_small_patch16_224,68.490,31.510,88.260,11.740,22.05,224,0.900,bicubic,-11.376,-6.796,+1
 tf_efficientnet_b2,68.460,31.540,88.010,11.990,9.11,260,0.890,bicubic,-11.608,-6.894,-11
-skresnext50_32x4d,68.440,31.560,87.610,12.390,27.48,224,0.875,bicubic,-11.702,-7.034,-16
-resnet50,68.440,31.560,87.600,12.400,25.56,224,0.950,bicubic,-11.942,-6.994,-34
+resnet50,68.440,31.560,87.600,12.400,25.56,224,0.950,bicubic,-11.942,-6.994,-35
+skresnext50_32x4d,68.440,31.560,87.610,12.390,27.48,224,0.875,bicubic,-11.702,-7.034,-15
 dpn107,68.430,31.570,88.080,11.920,86.92,224,0.875,bicubic,-11.742,-6.824,-20
 cspresnet50,68.380,31.620,87.950,12.050,21.62,256,0.887,bilinear,-11.196,-6.752,+14
 dla102x2,68.380,31.620,87.810,12.190,41.28,224,0.875,bilinear,-11.060,-6.834,+20
 resnext50_32x4d,68.380,31.620,87.590,12.410,25.03,224,0.875,bicubic,-11.420,-7.024,0
-cait_xxs36_224,68.350,31.650,88.610,11.390,17.30,224,1.000,bicubic,-11.412,-6.258,+1
-ssl_resnet50,68.350,31.650,88.580,11.420,25.56,224,0.875,bilinear,-10.886,-6.252,+31
+ssl_resnet50,68.350,31.650,88.580,11.420,25.56,224,0.875,bilinear,-10.886,-6.252,+34
+cait_xxs36_224,68.350,31.650,88.610,11.390,17.30,224,1.000,bicubic,-11.412,-6.258,0
 xcit_tiny_24_p16_224,68.340,31.660,88.120,11.880,12.12,224,1.000,bicubic,-11.112,-6.768,+15
 regnety_064,68.330,31.670,88.030,11.970,30.58,224,0.875,bicubic,-11.400,-6.732,-1
 vit_base_patch16_sam_224,68.310,31.690,87.680,12.320,86.57,224,0.900,bicubic,-11.932,-7.082,-32
 dpn98,68.300,31.700,87.570,12.430,61.57,224,0.875,bicubic,-11.354,-7.034,+3
 resmlp_big_24_224,68.280,31.720,87.700,12.300,129.14,224,0.875,bicubic,-12.752,-7.322,-81
-ecaresnet26t,68.240,31.760,88.660,11.340,16.01,320,0.950,bicubic,-11.594,-6.424,-11
-ese_vovnet39b,68.230,31.770,88.290,11.710,24.57,224,0.875,bicubic,-11.074,-6.434,+17
-regnetx_120,68.230,31.770,87.580,12.420,46.11,224,0.875,bicubic,-11.376,-7.150,+1
-rexnet_130,68.220,31.780,88.000,12.000,7.56,224,0.875,bicubic,-11.276,-6.674,+3
+ecaresnet26t,68.240,31.760,88.660,11.340,16.01,320,0.950,bicubic,-11.594,-6.424,-12
+ese_vovnet39b,68.230,31.770,88.290,11.710,24.57,224,0.875,bicubic,-11.074,-6.434,+16
+regnetx_120,68.230,31.770,87.580,12.420,46.11,224,0.875,bicubic,-11.376,-7.150,+2
 efficientnet_b2_pruned,68.220,31.780,88.080,11.920,8.31,260,0.890,bicubic,-11.686,-6.774,-21
+rexnet_130,68.220,31.780,88.000,12.000,7.56,224,0.875,bicubic,-11.276,-6.674,+3
 gluon_resnext50_32x4d,68.160,31.840,87.360,12.640,25.03,224,0.875,bicubic,-11.204,-7.064,+9
 ecaresnet50d_pruned,68.140,31.860,88.340,11.660,19.94,224,0.875,bicubic,-11.566,-6.534,-9
-tf_efficientnet_el,68.100,31.900,88.020,11.980,10.59,300,0.904,bicubic,-12.148,-7.104,-43
+tf_efficientnet_el,68.100,31.900,88.020,11.980,10.59,300,0.904,bicubic,-12.148,-7.104,-44
 resnetv2_50x1_bitm,67.930,32.070,89.090,10.910,25.55,448,1.000,bilinear,-12.414,-6.596,-53
-regnetx_080,67.920,32.080,87.070,12.930,39.57,224,0.875,bicubic,-11.300,-7.476,+18
+regnetx_080,67.920,32.080,87.070,12.930,39.57,224,0.875,bicubic,-11.300,-7.476,+20
 resmlp_36_224,67.920,32.080,88.220,11.780,44.69,224,0.875,bicubic,-11.856,-6.666,-17
 tf_efficientnet_lite3,67.920,32.080,87.710,12.290,8.20,300,0.904,bilinear,-11.900,-7.200,-20
 pit_xs_distilled_224,67.900,32.100,87.710,12.290,11.00,224,0.900,bicubic,-11.394,-6.664,+10
 resnetrs50,67.890,32.110,87.660,12.340,35.69,224,0.910,bicubic,-11.980,-7.310,-28
-legacy_seresnext50_32x4d,67.880,32.120,87.590,12.410,27.56,224,0.875,bilinear,-11.198,-6.842,+20
-gluon_resnet50_v1d,67.870,32.130,86.940,13.060,25.58,224,0.875,bicubic,-11.194,-7.520,+20
+legacy_seresnext50_32x4d,67.880,32.120,87.590,12.410,27.56,224,0.875,bilinear,-11.198,-6.842,+22
+gluon_resnet50_v1d,67.870,32.130,86.940,13.060,25.58,224,0.875,bicubic,-11.194,-7.520,+22
+tf_efficientnetv2_b1,67.840,32.160,87.620,12.380,8.14,240,0.882,bicubic,-11.634,-7.100,-9
+nf_regnet_b1,67.840,32.160,88.080,11.920,10.22,288,0.900,bicubic,-11.456,-6.662,+3
 levit_192,67.840,32.160,87.820,12.180,10.95,224,0.900,bicubic,-12.020,-6.982,-29
-nf_regnet_b1,67.840,32.160,88.080,11.920,10.22,288,0.900,bicubic,-11.456,-6.662,+4
-tf_efficientnetv2_b1,67.840,32.160,87.620,12.380,8.14,240,0.882,bicubic,-11.634,-7.100,-10
 hrnet_w48,67.800,32.200,87.370,12.630,77.47,224,0.875,bilinear,-11.522,-7.144,-3
 resnext101_32x8d,67.760,32.240,87.360,12.640,88.79,224,0.875,bilinear,-11.552,-7.162,-3
-tf_efficientnet_b0_ns,67.720,32.280,87.940,12.060,5.29,224,0.875,bicubic,-10.938,-6.430,+33
+tf_efficientnet_b0_ns,67.720,32.280,87.940,12.060,5.29,224,0.875,bicubic,-10.938,-6.430,+35
 resmlp_24_224,67.700,32.300,87.570,12.430,30.02,224,0.875,bicubic,-11.686,-6.976,-10
-halonet26t,67.690,32.310,87.310,12.690,12.48,256,0.950,bicubic,-11.444,-7.006,+8
-hrnet_w44,67.690,32.310,87.490,12.510,67.06,224,0.875,bilinear,-11.200,-6.892,+19
-regnetx_064,67.670,32.330,87.470,12.530,26.21,224,0.875,bicubic,-11.390,-6.996,+11
-coat_lite_mini,67.660,32.340,87.720,12.280,11.01,224,0.900,bicubic,-11.440,-6.882,+7
-dla169,67.650,32.350,87.460,12.540,53.39,224,0.875,bilinear,-11.048,-6.872,+24
-regnety_040,67.620,32.380,87.390,12.610,20.65,224,0.875,bicubic,-11.608,-7.256,-2
-efficientnet_em,67.570,32.430,88.110,11.890,6.90,240,0.882,bicubic,-11.690,-6.682,-5
-dpn92,67.550,32.450,87.290,12.710,37.67,224,0.875,bicubic,-12.444,-7.546,-52
-xception,67.550,32.450,87.520,12.480,22.86,299,0.897,bicubic,-11.498,-6.876,+6
-gluon_inception_v3,67.540,32.460,87.250,12.750,23.83,299,0.875,bicubic,-11.258,-7.130,+16
-dpn68b,67.520,32.480,87.490,12.510,12.61,224,0.875,bicubic,-11.696,-6.932,-5
-legacy_seresnet152,67.510,32.490,87.500,12.500,66.82,224,0.875,bilinear,-11.152,-6.876,+19
-lambda_resnet26t,67.490,32.510,87.650,12.350,10.96,256,0.940,bicubic,-11.618,-6.938,-4
+hrnet_w44,67.690,32.310,87.490,12.510,67.06,224,0.875,bilinear,-11.200,-6.892,+22
+halonet26t,67.690,32.310,87.310,12.690,12.48,256,0.950,bicubic,-11.444,-7.006,+9
+eca_botnext26ts_256,67.680,32.320,87.090,12.910,10.59,256,0.950,bicubic,-11.594,-7.516,-1
+regnetx_064,67.670,32.330,87.470,12.530,26.21,224,0.875,bicubic,-11.390,-6.996,+12
+coat_lite_mini,67.660,32.340,87.720,12.280,11.01,224,0.900,bicubic,-11.440,-6.882,+8
+dla169,67.650,32.350,87.460,12.540,53.39,224,0.875,bilinear,-11.048,-6.872,+25
+regnety_040,67.620,32.380,87.390,12.610,20.65,224,0.875,bicubic,-11.608,-7.256,-1
+efficientnet_em,67.570,32.430,88.110,11.890,6.90,240,0.882,bicubic,-11.690,-6.682,-4
+dpn92,67.550,32.450,87.290,12.710,37.67,224,0.875,bicubic,-12.444,-7.546,-53
+xception,67.550,32.450,87.520,12.480,22.86,299,0.897,bicubic,-11.498,-6.876,+7
+gluon_inception_v3,67.540,32.460,87.250,12.750,23.83,299,0.875,bicubic,-11.258,-7.130,+17
+dpn68b,67.520,32.480,87.490,12.510,12.61,224,0.875,bicubic,-11.696,-6.932,-4
+legacy_seresnet152,67.510,32.490,87.500,12.500,66.82,224,0.875,bilinear,-11.152,-6.876,+20
 efficientnet_b1,67.490,32.510,87.430,12.570,7.79,256,1.000,bicubic,-11.314,-6.916,+12
-hrnet_w40,67.470,32.530,87.140,12.860,57.56,224,0.875,bilinear,-11.456,-7.338,+5
-resnetblur50,67.440,32.560,87.580,12.420,25.56,224,0.875,bicubic,-11.860,-6.950,-19
-tf_efficientnet_b1_ap,67.430,32.570,87.540,12.460,7.79,240,0.882,bicubic,-11.844,-6.762,-16
-tf_efficientnet_cc_b1_8e,67.380,32.620,87.280,12.720,39.72,240,0.882,bicubic,-11.946,-7.088,-25
+lambda_resnet26t,67.490,32.510,87.650,12.350,10.96,256,0.940,bicubic,-11.618,-6.938,-2
+hrnet_w40,67.470,32.530,87.140,12.860,57.56,224,0.875,bilinear,-11.456,-7.338,+6
+resnetblur50,67.440,32.560,87.580,12.420,25.56,224,0.875,bicubic,-11.860,-7.056,-19
+tf_efficientnet_b1_ap,67.430,32.570,87.540,12.460,7.79,240,0.882,bicubic,-11.844,-6.762,-17
+tf_efficientnet_cc_b1_8e,67.380,32.620,87.280,12.720,39.72,240,0.882,bicubic,-11.946,-7.088,-26
 res2net50_26w_8s,67.360,32.640,87.130,12.870,48.40,224,0.875,bilinear,-11.620,-7.154,-1
-res2net101_26w_4s,67.360,32.640,87.170,12.830,45.21,224,0.875,bilinear,-11.832,-7.268,-12
-gluon_resnet101_v1b,67.350,32.650,87.050,12.950,44.55,224,0.875,bicubic,-11.950,-7.586,-23
-cait_xxs24_224,67.310,32.690,87.490,12.510,11.96,224,1.000,bicubic,-11.066,-6.826,+26
-xception41,67.310,32.690,87.150,12.850,26.97,299,0.903,bicubic,-11.222,-7.134,+12
-gluon_resnet101_v1c,67.290,32.710,87.060,12.940,44.57,224,0.875,bicubic,-12.244,-7.528,-40
-resnet33ts,67.170,32.830,87.410,12.590,19.68,256,0.900,bicubic,-12.044,-7.162,-18
-regnetx_032,67.150,32.850,86.980,13.020,15.30,224,0.875,bicubic,-11.000,-7.106,+31
-coat_tiny,67.120,32.880,87.380,12.620,5.50,224,0.900,bicubic,-11.314,-6.654,+17
+res2net101_26w_4s,67.360,32.640,87.170,12.830,45.21,224,0.875,bilinear,-11.832,-7.268,-11
+gluon_resnet101_v1b,67.350,32.650,87.050,12.950,44.55,224,0.875,bicubic,-11.950,-7.480,-25
+cait_xxs24_224,67.310,32.690,87.490,12.510,11.96,224,1.000,bicubic,-11.066,-6.826,+27
+xception41,67.310,32.690,87.150,12.850,26.97,299,0.903,bicubic,-11.222,-7.134,+13
+gluon_resnet101_v1c,67.290,32.710,87.060,12.940,44.57,224,0.875,bicubic,-12.244,-7.528,-41
+resnet33ts,67.170,32.830,87.410,12.590,19.68,256,0.900,bicubic,-12.044,-7.162,-17
+regnetx_032,67.150,32.850,86.980,13.020,15.30,224,0.875,bicubic,-11.000,-7.106,+32
+botnet26t_256,67.130,32.870,87.500,12.500,12.49,256,0.950,bicubic,-12.130,-7.034,-25
 resnest26d,67.120,32.880,87.130,12.870,17.07,224,0.875,bilinear,-11.358,-7.166,+10
+coat_tiny,67.120,32.880,87.380,12.620,5.50,224,0.900,bicubic,-11.314,-6.654,+17
 dla60_res2net,67.110,32.890,87.080,12.920,20.85,224,0.875,bilinear,-11.352,-7.128,+11
 legacy_seresnet101,67.100,32.900,87.020,12.980,49.33,224,0.875,bilinear,-11.284,-7.244,+16
 dla60x,67.080,32.920,87.200,12.800,17.35,224,0.875,bilinear,-11.166,-6.824,+22
@@ -346,23 +351,23 @@ dla102x,67.000,33.000,86.730,13.270,26.31,224,0.875,bilinear,-11.512,-7.496,+4
 res2net50_26w_6s,66.980,33.020,86.830,13.170,37.05,224,0.875,bilinear,-11.586,-7.288,+1
 xcit_tiny_12_p16_224_dist,66.970,33.030,87.340,12.660,6.72,224,1.000,bicubic,-11.610,-6.864,-1
 repvgg_b2,66.950,33.050,87.260,12.740,89.02,224,0.875,bilinear,-11.844,-7.166,-8
-gluon_resnet50_v1s,66.940,33.060,86.800,13.200,25.68,224,0.875,bicubic,-11.756,-7.448,-6
-mixnet_l,66.940,33.060,86.790,13.210,7.33,224,0.875,bicubic,-12.040,-7.390,-20
-pit_xs_224,66.940,33.060,87.190,12.810,10.62,224,0.900,bicubic,-11.244,-6.974,+18
+pit_xs_224,66.940,33.060,87.190,12.810,10.62,224,0.900,bicubic,-11.244,-6.974,+20
+mixnet_l,66.940,33.060,86.790,13.210,7.33,224,0.875,bicubic,-12.040,-7.390,-19
+gluon_resnet50_v1s,66.940,33.060,86.800,13.200,25.68,224,0.875,bicubic,-11.756,-7.448,-8
 tv_resnet152,66.930,33.070,87.440,12.560,60.19,224,0.875,bilinear,-11.392,-6.604,+11
-eca_halonext26ts,66.820,33.180,87.070,12.930,10.76,256,0.940,bicubic,-12.020,-7.186,-17
-repvgg_b1,66.820,33.180,86.690,13.310,57.42,224,0.875,bilinear,-11.558,-7.414,+6
+repvgg_b1,66.820,33.180,86.690,13.310,57.42,224,0.875,bilinear,-11.558,-7.414,+7
+eca_halonext26ts,66.820,33.180,87.070,12.930,10.76,256,0.940,bicubic,-12.020,-7.186,-18
 tf_efficientnet_b1,66.810,33.190,86.920,13.080,7.79,240,0.882,bicubic,-12.026,-7.274,-18
 lambda_resnet26rpt_256,66.800,33.200,87.060,12.940,10.99,256,0.940,bicubic,-12.168,-7.368,-24
 efficientnet_es,66.720,33.280,86.670,13.330,5.44,224,0.875,bicubic,-11.362,-7.274,+17
 xcit_nano_12_p8_384_dist,66.720,33.280,87.050,12.950,3.05,384,1.000,bicubic,-11.098,-6.984,+32
-gluon_resnet50_v1c,66.710,33.290,86.110,13.890,25.58,224,0.875,bicubic,-11.296,-7.878,+17
-dla60_res2next,66.710,33.290,86.940,13.060,17.03,224,0.875,bilinear,-11.732,-7.218,-4
+gluon_resnet50_v1c,66.710,33.290,86.110,13.890,25.58,224,0.875,bicubic,-11.296,-7.878,+18
+dla60_res2next,66.710,33.290,86.940,13.060,17.03,224,0.875,bilinear,-11.732,-7.256,-4
 hrnet_w30,66.690,33.310,86.740,13.260,37.71,224,0.875,bilinear,-11.512,-7.488,+7
 resnet32ts,66.690,33.310,87.130,12.870,17.96,256,0.900,bicubic,-12.330,-7.232,-33
-hrnet_w32,66.650,33.350,87.190,12.810,41.23,224,0.875,bilinear,-11.792,-7.006,-7
+selecsls60b,66.650,33.350,86.590,13.410,32.77,224,0.875,bicubic,-11.758,-7.586,-5
 regnetx_040,66.650,33.350,86.530,13.470,22.12,224,0.875,bicubic,-11.834,-7.724,-14
-selecsls60b,66.650,33.350,86.590,13.410,32.77,224,0.875,bicubic,-11.758,-7.586,-7
+hrnet_w32,66.650,33.350,87.190,12.810,41.23,224,0.875,bilinear,-11.792,-6.968,-10
 tf_mixnet_l,66.630,33.370,86.380,13.620,7.33,224,0.875,bicubic,-12.148,-7.620,-25
 dla102,66.590,33.410,86.930,13.070,33.27,224,0.875,bilinear,-11.438,-7.028,+9
 wide_resnet101_2,66.570,33.430,87.010,12.990,126.89,224,0.875,bilinear,-12.284,-7.274,-33
@@ -370,18 +375,18 @@ tf_efficientnetv2_b0,66.520,33.480,86.620,13.380,7.14,224,0.875,bicubic,-11.850,
 levit_128,66.500,33.500,86.710,13.290,9.21,224,0.900,bicubic,-11.966,-7.300,-18
 adv_inception_v3,66.370,33.630,86.380,13.620,23.83,299,0.875,bicubic,-11.208,-7.360,+26
 vit_tiny_patch16_384,66.330,33.670,87.160,12.840,5.79,384,1.000,bicubic,-12.116,-7.384,-18
-tf_inception_v3,66.320,33.680,86.570,13.430,23.83,299,0.875,bicubic,-11.540,-7.076,+14
+tf_inception_v3,66.320,33.680,86.570,13.430,23.83,299,0.875,bicubic,-11.540,-7.076,+13
 selecsls60,66.310,33.690,86.290,13.710,30.67,224,0.875,bicubic,-11.674,-7.542,+5
 resmlp_12_distilled_224,66.280,33.720,86.470,13.530,15.35,224,0.875,bicubic,-11.664,-7.092,+6
 hardcorenas_f,66.240,33.760,86.250,13.750,8.20,224,0.875,bilinear,-11.864,-7.544,-3
 coat_lite_tiny,66.230,33.770,86.950,13.050,5.72,224,0.900,bicubic,-11.284,-6.966,+23
 bat_resnext26ts,66.210,33.790,86.650,13.350,10.73,256,0.900,bicubic,-12.052,-7.450,-14
-efficientnet_b0,66.120,33.880,86.100,13.900,5.29,224,0.875,bicubic,-11.584,-7.422,+13
-tf_efficientnet_cc_b0_8e,66.120,33.880,86.100,13.900,24.01,224,0.875,bicubic,-11.788,-7.556,+3
+tf_efficientnet_cc_b0_8e,66.120,33.880,86.100,13.900,24.01,224,0.875,bicubic,-11.788,-7.556,+4
+efficientnet_b0,66.120,33.880,86.100,13.900,5.29,224,0.875,bicubic,-11.584,-7.422,+12
 legacy_seresnet50,66.090,33.910,86.290,13.710,28.09,224,0.875,bilinear,-11.548,-7.456,+12
 gmixer_24_224,66.080,33.920,85.980,14.020,24.72,224,0.875,bicubic,-11.972,-7.688,-7
-res2net50_14w_8s,66.030,33.970,86.200,13.800,25.06,224,0.875,bilinear,-12.104,-7.656,-11
-tf_efficientnet_em,66.030,33.970,86.210,13.790,6.90,240,0.882,bicubic,-12.112,-7.848,-13
+tf_efficientnet_em,66.030,33.970,86.210,13.790,6.90,240,0.882,bicubic,-12.112,-7.848,-12
+res2net50_14w_8s,66.030,33.970,86.200,13.800,25.06,224,0.875,bilinear,-12.104,-7.656,-12
 res2net50_26w_4s,66.010,33.990,86.590,13.410,25.70,224,0.875,bilinear,-11.976,-7.258,-7
 inception_v3,66.000,34.000,86.120,13.880,23.83,299,0.875,bicubic,-11.464,-7.356,+16
 hardcorenas_e,65.990,34.010,85.980,14.020,8.07,224,0.875,bilinear,-11.810,-7.716,+4
@@ -390,8 +395,8 @@ efficientnet_b1_pruned,65.950,34.050,86.510,13.490,6.33,240,0.882,bicubic,-12.30
 tv_resnext50_32x4d,65.940,34.060,86.030,13.970,25.03,224,0.875,bilinear,-11.670,-7.654,+4
 gluon_resnet50_v1b,65.910,34.090,86.230,13.770,25.56,224,0.875,bicubic,-11.666,-7.492,+7
 tv_resnet101,65.820,34.180,85.980,14.020,44.55,224,0.875,bilinear,-11.548,-7.580,+13
-gcresnext26ts,65.810,34.190,85.850,14.150,10.48,256,0.900,bicubic,-12.010,-7.976,-4
-rexnet_100,65.810,34.190,86.510,13.490,4.80,224,0.875,bicubic,-12.050,-7.366,-8
+rexnet_100,65.810,34.190,86.510,13.490,4.80,224,0.875,bicubic,-12.050,-7.366,-6
+gcresnext26ts,65.810,34.190,85.850,14.150,10.48,256,0.900,bicubic,-12.010,-7.976,-5
 seresnext26t_32x4d,65.780,34.220,85.610,14.390,16.81,224,0.875,bicubic,-12.198,-8.132,-15
 resnet34d,65.770,34.230,86.620,13.380,21.82,224,0.875,bicubic,-11.344,-6.762,+17
 repvgg_b1g4,65.760,34.240,85.970,14.030,39.97,224,0.875,bilinear,-11.834,-7.872,-2
@@ -409,7 +414,7 @@ convmixer_1024_20_ks9_p14,65.430,34.570,85.520,14.480,24.38,224,0.960,bicubic,-1
 tf_efficientnet_lite2,65.300,34.700,86.010,13.990,6.09,260,0.890,bicubic,-12.182,-7.738,-8
 densenet201,65.290,34.710,85.660,14.340,20.01,224,0.875,bicubic,-12.000,-7.820,-2
 seresnext26d_32x4d,65.260,34.740,85.810,14.190,16.81,224,0.875,bicubic,-12.326,-7.794,-15
-densenetblur121d,65.250,34.750,85.780,14.220,8.00,224,0.875,bicubic,-11.340,-7.412,+20
+densenetblur121d,65.250,34.750,85.780,14.220,8.00,224,0.875,bicubic,-11.340,-7.412,+21
 crossvit_9_dagger_240,65.230,34.770,86.470,13.530,8.78,240,0.875,bicubic,-11.760,-7.136,+5
 res2net50_48w_2s,65.220,34.780,85.920,14.080,25.29,224,0.875,bilinear,-12.314,-7.638,-15
 tf_efficientnet_b0_ap,65.200,34.800,85.490,14.510,5.29,224,0.875,bicubic,-11.904,-7.774,-1
@@ -431,19 +436,19 @@ densenet169,64.420,35.580,85.250,14.750,14.15,224,0.875,bicubic,-11.478,-7.774,+
 resnext26ts,64.380,35.620,85.000,15.000,10.30,256,0.900,bicubic,-12.392,-8.130,-5
 resmlp_12_224,64.340,35.660,85.600,14.400,15.35,224,0.875,bicubic,-12.314,-7.572,-2
 repvgg_a2,64.270,35.730,84.980,15.020,28.21,224,0.875,bilinear,-12.210,-8.040,+4
-regnetx_016,64.230,35.770,85.440,14.560,9.19,224,0.875,bicubic,-12.716,-7.986,-14
-xcit_nano_12_p16_384_dist,64.230,35.770,85.280,14.720,3.05,384,1.000,bicubic,-11.238,-7.396,+19
+xcit_nano_12_p16_384_dist,64.230,35.770,85.280,14.720,3.05,384,1.000,bicubic,-11.238,-7.396,+20
+regnetx_016,64.230,35.770,85.440,14.560,9.19,224,0.875,bicubic,-12.716,-7.986,-15
 hardcorenas_b,64.210,35.790,84.860,15.140,5.18,224,0.875,bilinear,-12.320,-7.892,-1
 tf_efficientnet_b0,64.160,35.840,85.170,14.830,5.29,224,0.875,bicubic,-12.686,-8.060,-13
 dpn68,64.030,35.970,84.990,15.010,12.61,224,0.875,bicubic,-12.264,-7.972,+2
-tf_efficientnet_es,63.900,36.100,84.580,15.420,5.44,224,0.875,bicubic,-12.690,-8.632,-6
-vit_small_patch32_224,63.880,36.120,85.590,14.410,22.88,224,0.900,bicubic,-12.114,-7.686,+3
+tf_efficientnet_es,63.900,36.100,84.580,15.420,5.44,224,0.875,bicubic,-12.690,-8.632,-7
+vit_small_patch32_224,63.880,36.120,85.590,14.410,22.88,224,0.900,bicubic,-12.114,-7.686,+2
 mobilenetv2_140,63.870,36.130,84.950,15.050,6.11,224,0.875,bicubic,-12.646,-8.050,-5
 densenet121,63.730,36.270,84.600,15.400,7.98,224,0.875,bicubic,-11.838,-8.052,+8
 regnety_008,63.730,36.270,85.240,14.760,6.26,224,0.875,bicubic,-12.590,-7.828,-4
 hardcorenas_a,63.680,36.320,84.470,15.530,5.26,224,0.875,bilinear,-12.232,-8.044,+1
 resnest14d,63.550,36.450,84.010,15.990,10.61,224,0.875,bilinear,-11.956,-8.510,+7
-mixnet_s,63.540,36.460,84.710,15.290,4.13,224,0.875,bicubic,-12.454,-8.082,-4
+mixnet_s,63.540,36.460,84.710,15.290,4.13,224,0.875,bicubic,-12.454,-8.082,-3
 tf_mixnet_s,63.430,36.570,84.090,15.910,4.13,224,0.875,bicubic,-12.254,-8.546,+1
 resnet26,63.420,36.580,84.210,15.790,16.00,224,0.875,bicubic,-11.872,-8.364,+9
 mobilenetv3_large_100,63.310,36.690,84.050,15.950,5.48,224,0.875,bicubic,-12.464,-8.490,-2
@@ -462,9 +467,9 @@ legacy_seresnet34,62.770,37.230,84.200,15.800,21.96,224,0.875,bilinear,-12.022,-
 regnety_006,62.740,37.260,84.100,15.900,6.06,224,0.875,bicubic,-12.526,-8.434,-4
 deit_tiny_distilled_patch16_224,62.720,37.280,83.800,16.200,5.91,224,0.900,bicubic,-11.804,-8.096,+10
 hrnet_w18_small_v2,62.660,37.340,83.850,16.150,15.60,224,0.875,bilinear,-12.446,-8.562,-2
-swsl_resnet18,62.650,37.350,84.290,15.710,11.69,224,0.875,bilinear,-10.632,-7.468,+22
-mobilenetv2_110d,62.620,37.380,84.450,15.550,4.52,224,0.875,bicubic,-12.432,-7.738,-2
-repvgg_b0,62.620,37.380,83.660,16.340,15.82,224,0.875,bilinear,-12.532,-8.754,-8
+swsl_resnet18,62.650,37.350,84.290,15.710,11.69,224,0.875,bilinear,-10.632,-7.468,+21
+repvgg_b0,62.620,37.380,83.660,16.340,15.82,224,0.875,bilinear,-12.532,-8.754,-7
+mobilenetv2_110d,62.620,37.380,84.450,15.550,4.52,224,0.875,bicubic,-12.432,-7.738,-3
 tf_efficientnet_lite0,62.560,37.440,84.140,15.860,4.65,224,0.875,bicubic,-12.272,-8.036,-2
 regnetx_008,62.510,37.490,83.980,16.020,7.26,224,0.875,bicubic,-12.546,-8.368,-6
 dla34,62.500,37.500,83.860,16.140,15.74,224,0.875,bilinear,-12.108,-8.198,0
@@ -473,24 +478,23 @@ xcit_nano_12_p8_224,62.450,37.550,84.190,15.810,3.05,224,1.000,bicubic,-11.462,-
 fbnetc_100,62.380,37.620,83.370,16.630,5.57,224,0.875,bilinear,-12.740,-9.004,-13
 tf_mobilenetv3_large_100,62.230,37.770,83.850,16.150,5.48,224,0.875,bilinear,-13.280,-8.758,-23
 crossvit_9_240,62.110,37.890,84.300,15.700,8.55,240,0.875,bicubic,-11.872,-7.670,+3
-crossvit_tiny_240,62.060,37.940,83.780,16.220,7.01,240,0.875,bicubic,-11.284,-8.142,+9
+crossvit_tiny_240,62.060,37.940,83.780,16.220,7.01,240,0.875,bicubic,-11.284,-8.142,+8
 regnety_004,61.990,38.010,83.440,16.560,4.34,224,0.875,bicubic,-12.022,-8.326,-1
 vgg19_bn,61.910,38.090,83.380,16.620,143.68,224,0.875,bilinear,-12.324,-8.474,-4
 mnasnet_100,61.900,38.100,83.730,16.270,4.38,224,0.875,bicubic,-12.774,-8.368,-10
-ssl_resnet18,61.530,38.470,83.300,16.700,11.69,224,0.875,bilinear,-11.082,-8.120,+12
-eca_botnext26ts_256,61.520,38.480,82.760,17.240,10.59,256,0.950,bicubic,-12.358,-9.028,-1
+ssl_resnet18,61.530,38.470,83.300,16.700,11.69,224,0.875,bilinear,-11.082,-8.120,+11
 convit_tiny,61.470,38.530,83.990,16.010,5.71,224,0.875,bicubic,-11.642,-7.730,+6
 tv_resnet34,61.150,38.850,82.640,17.360,21.80,224,0.875,bilinear,-12.154,-8.782,+3
 regnetx_006,61.120,38.880,83.250,16.750,6.20,224,0.875,bicubic,-12.726,-8.432,-3
-spnasnet_100,61.070,38.930,82.750,17.250,4.42,224,0.875,bilinear,-13.008,-9.070,-10
+spnasnet_100,61.070,38.930,82.750,17.250,4.42,224,0.875,bilinear,-13.008,-9.070,-9
 pit_ti_224,60.940,39.060,83.820,16.180,4.85,224,0.900,bicubic,-11.982,-7.590,+5
 vgg16_bn,60.820,39.180,83.010,16.990,138.37,224,0.875,bilinear,-12.540,-8.482,-4
 skresnet18,60.820,39.180,82.870,17.130,11.96,224,0.875,bicubic,-12.202,-8.300,+2
-ghostnet_100,60.610,39.390,82.270,17.730,5.18,224,0.875,bilinear,-13.374,-9.190,-12
+ghostnet_100,60.610,39.390,82.270,17.730,5.18,224,0.875,bilinear,-13.374,-9.190,-11
 tf_mobilenetv3_large_075,60.360,39.640,81.800,18.200,3.99,224,0.875,bilinear,-13.090,-9.540,-7
 xcit_nano_12_p16_224_dist,60.330,39.670,82.490,17.510,3.05,224,1.000,bicubic,-11.982,-8.362,+5
 mobilenetv2_100,60.210,39.790,82.040,17.960,3.50,224,0.875,bicubic,-12.742,-8.962,-2
-vit_base_patch32_sam_224,59.970,40.030,81.300,18.700,88.22,224,0.900,bicubic,-13.730,-9.708,-37
+vit_base_patch32_sam_224,59.970,40.030,81.300,18.700,88.22,224,0.900,bicubic,-13.730,-9.708,-36
 deit_tiny_patch16_224,59.920,40.080,82.730,17.270,5.72,224,0.900,bicubic,-12.240,-8.382,+6
 resnet18d,59.860,40.140,82.310,17.690,11.71,224,0.875,bicubic,-12.408,-8.374,+3
 legacy_seresnet18,59.730,40.270,81.600,18.400,11.78,224,0.875,bicubic,-12.004,-8.738,+7
@@ -508,11 +512,10 @@ vgg13,57.100,42.900,79.610,20.390,133.05,224,0.875,bilinear,-12.838,-9.648,+3
 vgg11_bn,57.040,42.960,79.760,20.240,132.87,224,0.875,bilinear,-13.322,-10.046,-1
 regnety_002,56.980,43.020,79.830,20.170,3.16,224,0.875,bicubic,-13.302,-9.714,-1
 mixer_l16_224,56.200,43.800,75.690,24.310,208.20,224,0.875,bicubic,-15.866,-11.964,-9
-dla60x_c,56.090,43.910,78.950,21.050,1.32,224,0.875,bilinear,-11.822,-9.468,+5
+dla60x_c,56.090,43.910,78.950,21.050,1.32,224,0.875,bilinear,-11.822,-9.468,+4
 vgg11,55.900,44.100,78.760,21.240,132.86,224,0.875,bilinear,-13.148,-9.876,0
 regnetx_002,55.790,44.210,79.240,20.760,2.68,224,0.875,bicubic,-12.960,-9.320,0
-tf_mobilenetv3_small_100,54.530,45.470,77.010,22.990,2.54,224,0.875,bilinear,-13.396,-10.666,+1
-botnet26t_256,53.690,46.310,77.400,22.600,12.49,256,0.950,bicubic,-14.856,-11.296,-1
+tf_mobilenetv3_small_100,54.530,45.470,77.010,22.990,2.54,224,0.875,bilinear,-13.396,-10.666,0
 dla46x_c,53.120,46.880,76.810,23.190,1.07,224,0.875,bilinear,-12.856,-10.178,+1
 tf_mobilenetv3_small_075,52.360,47.640,75.470,24.530,2.04,224,0.875,bilinear,-13.360,-10.666,+1
 dla46_c,52.020,47.980,75.730,24.270,1.30,224,0.875,bilinear,-12.850,-10.564,+1

results/results-sketch.csv

@@ -8,14 +8,14 @@ beit_large_patch16_512,56.757,43.243,78.874,21.126,305.67,512,1.000,bicubic,-31.
 swsl_resnext101_32x8d,56.421,43.579,78.948,21.052,88.79,224,0.875,bilinear,-27.853,-18.226,+67
 beit_large_patch16_224,54.969,45.031,77.600,22.400,304.43,224,0.900,bicubic,-32.507,-20.718,-3
 ig_resnext101_32x8d,54.937,45.063,77.539,22.461,88.79,224,0.875,bilinear,-27.773,-19.101,+124
-swsl_resnext101_32x4d,53.585,46.415,76.374,23.626,44.18,224,0.875,bilinear,-29.641,-20.394,+106
+swsl_resnext101_32x4d,53.585,46.415,76.374,23.626,44.18,224,0.875,bilinear,-29.641,-19.956,+105
 vit_large_patch16_384,52.762,47.238,74.725,25.275,304.72,384,1.000,bicubic,-34.330,-23.581,-4
-vit_large_r50_s32_384,52.049,47.951,73.540,26.459,329.09,384,1.000,bicubic,-34.131,-24.383,+4
+vit_large_r50_s32_384,52.049,47.951,73.540,26.459,329.09,384,1.000,bicubic,-34.131,-24.384,+4
 vit_large_patch16_224,51.842,48.158,73.721,26.279,304.33,224,0.900,bicubic,-33.996,-24.105,+9
 tf_efficientnet_l2_ns_475,51.435,48.565,73.845,26.155,480.31,475,0.936,bicubic,-36.803,-24.705,-10
 swsl_resnext50_32x4d,50.408,49.592,73.348,26.652,25.03,224,0.875,bilinear,-31.758,-22.886,+148
 swin_large_patch4_window12_384,50.357,49.643,72.546,27.454,196.74,384,1.000,bicubic,-36.793,-25.692,-10
-swsl_resnet50,49.506,50.494,72.356,27.645,25.56,224,0.875,bilinear,-31.640,-23.622,+186
+swsl_resnet50,49.506,50.494,72.356,27.645,25.56,224,0.875,bilinear,-31.640,-23.622,+189
 swin_large_patch4_window7_224,48.989,51.011,71.377,28.623,196.53,224,0.900,bicubic,-37.327,-26.513,-4
 beit_base_patch16_384,48.682,51.318,72.073,27.927,86.74,384,1.000,bicubic,-38.126,-26.067,-10
 swin_base_patch4_window12_384,48.529,51.471,71.809,28.191,87.90,384,1.000,bicubic,-37.907,-26.257,-8
@@ -64,7 +64,7 @@ dm_nfnet_f5,39.498,60.502,60.194,39.806,377.21,544,0.954,bicubic,-46.308,-37.288
 xcit_small_24_p8_224_dist,39.309,60.691,59.404,40.596,47.63,224,1.000,bicubic,-45.567,-37.794,-8
 xcit_medium_24_p16_224_dist,39.272,60.728,59.473,40.527,84.40,224,1.000,bicubic,-45.006,-37.469,+8
 efficientnet_b4,39.136,60.864,59.628,40.372,19.34,384,1.000,bicubic,-44.294,-36.966,+42
-xcit_small_24_p8_384_dist,39.001,60.999,59.196,40.804,47.63,384,1.000,bicubic,-46.565,-38.381,-38
+xcit_small_24_p8_384_dist,39.001,60.999,59.196,40.804,47.63,384,1.000,bicubic,-46.565,-38.380,-38
 resnetv2_152x2_bit_teacher_384,38.987,61.013,62.495,37.505,236.34,384,1.000,bicubic,-44.857,-34.623,+26
 vit_base_patch32_384,38.810,61.190,60.351,39.649,88.30,384,1.000,bicubic,-44.536,-36.493,+44
 eca_nfnet_l2,38.661,61.339,59.451,40.549,56.72,384,1.000,bicubic,-46.059,-37.807,-11
@@ -73,7 +73,7 @@ xcit_small_24_p16_384_dist,38.499,61.501,58.400,41.600,47.67,384,1.000,bicubic,-
 xcit_small_12_p8_224_dist,38.382,61.618,58.844,41.156,26.21,224,1.000,bicubic,-45.858,-38.028,+4
 tf_efficientnet_b5,38.364,61.636,59.923,40.077,30.39,456,0.934,bicubic,-45.446,-36.825,+23
 deit_base_distilled_patch16_384,38.240,61.760,57.798,42.202,87.63,384,1.000,bicubic,-47.182,-39.534,-40
-dm_nfnet_f4,38.215,61.785,58.596,41.404,316.07,512,0.951,bicubic,-47.486,-38.918,-49
+dm_nfnet_f4,38.215,61.785,58.596,41.404,316.07,512,0.951,bicubic,-47.485,-38.918,-49
 xcit_large_24_p8_224,38.124,61.876,57.875,42.125,188.93,224,1.000,bicubic,-46.258,-38.781,-7
 resnetv2_152x2_bitm,38.008,61.992,61.180,38.820,236.34,448,1.000,bilinear,-46.444,-36.256,-13
 cait_s24_384,37.884,62.116,58.087,41.913,47.06,384,1.000,bicubic,-47.160,-39.263,-30
@@ -85,12 +85,12 @@ resnetrs350,37.702,62.298,58.099,41.901,163.96,384,1.000,bicubic,-47.010,-38.891
 pit_b_distilled_224,37.588,62.412,57.230,42.770,74.79,224,0.900,bicubic,-46.570,-39.628,-5
 xcit_small_12_p16_384_dist,37.582,62.418,57.777,42.223,26.25,384,1.000,bicubic,-47.132,-39.339,-26
 resnet200d,37.507,62.493,58.303,41.697,64.69,320,1.000,bicubic,-46.463,-38.515,+2
-resnetv2_152x2_bit_teacher,37.348,62.652,59.474,40.526,236.34,224,0.875,bicubic,-45.554,-37.093,+38
+resnetv2_152x2_bit_teacher,37.348,62.652,59.474,40.526,236.34,224,0.875,bicubic,-45.554,-37.094,+38
 resnest269e,37.299,62.701,57.466,42.534,110.93,416,0.928,bicubic,-47.225,-39.520,-25
 resmlp_big_24_224_in22ft1k,37.244,62.756,58.203,41.797,129.14,224,0.875,bicubic,-47.180,-38.913,-21
 vit_small_r26_s32_224,37.244,62.756,59.052,40.948,36.43,224,0.900,bicubic,-44.594,-36.974,+83
 cait_s24_224,37.150,62.850,56.725,43.275,46.92,224,1.000,bicubic,-46.312,-39.841,+15
-vit_base_patch32_224,37.100,62.900,59.284,40.716,88.22,224,0.900,bicubic,-43.632,-36.282,+132
+vit_base_patch32_224,37.100,62.900,59.284,40.716,88.22,224,0.900,bicubic,-43.632,-36.282,+135
 tf_efficientnet_b3_ap,37.061,62.939,57.242,42.758,12.23,300,0.904,bicubic,-44.761,-38.378,+81
 efficientnetv2_rw_s,37.057,62.943,56.831,43.169,23.94,384,1.000,bicubic,-46.773,-39.891,0
 xcit_small_12_p16_224_dist,36.973,63.027,56.745,43.255,26.25,224,1.000,bicubic,-46.377,-39.677,+16
@@ -108,7 +108,7 @@ tf_efficientnet_b2_ns,36.139,63.861,57.515,42.485,9.11,260,0.890,bicubic,-46.251
 ecaresnet101d,36.014,63.986,56.199,43.801,44.57,224,0.875,bicubic,-46.158,-39.855,+55
 dm_nfnet_f2,35.990,64.010,55.495,44.505,193.78,352,0.920,bicubic,-49.056,-41.743,-62
 resnest200e,35.939,64.061,55.873,44.127,70.20,320,0.909,bicubic,-47.909,-41.017,-18
-swsl_resnet18,35.852,64.147,58.462,41.538,11.69,224,0.875,bilinear,-37.429,-33.295,+376
+swsl_resnet18,35.852,64.147,58.462,41.538,11.69,224,0.875,bilinear,-37.430,-33.296,+380
 eca_nfnet_l1,35.835,64.165,55.965,44.035,41.41,320,1.000,bicubic,-48.197,-41.067,-25
 xcit_small_24_p8_224,35.542,64.458,54.774,45.226,47.63,224,1.000,bicubic,-48.304,-41.858,-20
 vit_small_patch16_384,35.515,64.485,57.549,42.451,22.20,384,1.000,bicubic,-48.279,-39.559,-16
@@ -119,28 +119,28 @@ resnest101e,35.397,64.603,55.802,44.198,48.28,256,0.875,bilinear,-47.479,-40.510
 convit_base,35.318,64.682,54.943,45.057,86.54,224,0.875,bicubic,-46.974,-40.991,+39
 xcit_tiny_24_p8_224_dist,35.253,64.747,55.287,44.713,12.11,224,1.000,bicubic,-47.323,-40.893,+20
 twins_svt_large,35.108,64.892,54.729,45.271,99.27,224,0.900,bicubic,-48.576,-41.881,-18
-repvgg_b3g4,35.069,64.931,54.772,45.228,83.83,224,0.875,bilinear,-45.150,-40.332,+136
-repvgg_b3,35.041,64.959,54.562,45.438,123.09,224,0.875,bilinear,-45.475,-40.702,+111
+repvgg_b3g4,35.069,64.931,54.772,45.228,83.83,224,0.875,bilinear,-45.149,-40.332,+139
+repvgg_b3,35.041,64.959,54.562,45.438,123.09,224,0.875,bilinear,-45.475,-40.702,+114
 dm_nfnet_f1,34.990,65.010,54.108,45.892,132.63,320,0.910,bicubic,-49.634,-42.988,-62
 xcit_tiny_24_p8_384_dist,34.925,65.075,55.153,44.847,12.11,384,1.000,bicubic,-48.839,-41.551,-26
 resnet101d,34.870,65.130,54.216,45.784,44.57,320,1.000,bicubic,-48.154,-42.240,-1
-resmlp_big_24_distilled_224,34.780,65.220,54.641,45.359,129.14,224,0.875,bicubic,-48.816,-42.016,-22
-vit_large_patch32_384,34.693,65.307,55.723,44.277,306.63,384,1.000,bicubic,-46.813,-40.363,+56
+resmlp_big_24_distilled_224,34.780,65.220,54.641,45.359,129.14,224,0.875,bicubic,-48.816,-42.015,-22
+vit_large_patch32_384,34.693,65.307,55.723,44.277,306.63,384,1.000,bicubic,-46.813,-40.363,+58
 dm_nfnet_f0,34.630,65.370,54.676,45.324,71.49,256,0.900,bicubic,-48.754,-41.904,-19
 ssl_resnext101_32x16d,34.593,65.407,55.949,44.051,194.03,224,0.875,bilinear,-47.251,-40.141,+43
 resnetv2_101,34.587,65.413,53.155,46.845,44.54,224,0.950,bicubic,-47.445,-42.709,+36
-repvgg_b2g4,34.581,65.419,54.809,45.191,61.76,224,0.875,bilinear,-44.799,-39.885,+172
+repvgg_b2g4,34.581,65.419,54.809,45.191,61.76,224,0.875,bilinear,-44.799,-39.885,+175
 resnetrs152,34.377,65.623,53.568,46.432,86.62,320,1.000,bicubic,-49.333,-43.042,-32
-resnest50d_4s2x40d,34.367,65.633,54.731,45.269,30.42,224,0.875,bicubic,-46.753,-40.829,+71
+resnest50d_4s2x40d,34.367,65.633,54.731,45.269,30.42,224,0.875,bicubic,-46.753,-40.829,+74
 crossvit_18_dagger_408,34.245,65.755,53.086,46.914,44.61,408,1.000,bicubic,-49.939,-43.736,-57
 xcit_medium_24_p16_224,34.218,65.782,53.184,46.816,84.40,224,1.000,bicubic,-48.408,-42.792,0
 efficientnetv2_rw_t,34.153,65.847,53.151,46.849,13.65,288,1.000,bicubic,-48.185,-43.043,+15
-tf_efficientnet_b1_ns,34.114,65.886,55.460,44.540,7.79,240,0.882,bicubic,-47.270,-40.278,+54
+tf_efficientnet_b1_ns,34.114,65.886,55.460,44.540,7.79,240,0.882,bicubic,-47.270,-40.278,+57
 twins_pcpvt_large,34.090,65.910,54.128,45.872,60.99,224,0.900,bicubic,-49.048,-42.480,-21
 tf_efficientnet_b4,34.064,65.936,54.202,45.798,19.34,380,0.922,bicubic,-48.966,-42.096,-16
 ssl_resnext101_32x8d,34.060,65.940,55.603,44.397,88.79,224,0.875,bilinear,-47.540,-40.443,+39
 tf_efficientnet_b6,34.043,65.957,54.562,45.438,43.04,528,0.942,bicubic,-50.069,-42.326,-61
-efficientnet_b3_pruned,34.017,65.983,54.124,45.876,9.86,300,0.904,bicubic,-46.841,-41.116,+78
+efficientnet_b3_pruned,34.017,65.983,54.124,45.876,9.86,300,0.904,bicubic,-46.841,-41.116,+81
 nfnet_l0,34.011,65.989,54.383,45.617,35.07,288,1.000,bicubic,-48.741,-42.133,-13
 xcit_small_24_p16_224,34.009,65.991,53.294,46.706,47.67,224,1.000,bicubic,-48.569,-42.706,-6
 regnety_160,33.978,66.022,53.558,46.442,83.59,288,1.000,bicubic,-49.724,-43.224,-44
@@ -150,286 +150,291 @@ xcit_small_12_p16_224,33.776,66.225,53.230,46.770,26.25,224,1.000,bicubic,-48.20
 resnetv2_50x3_bitm,33.695,66.305,55.922,44.078,217.32,448,1.000,bilinear,-50.289,-41.208,-62
 resnet51q,33.585,66.415,53.029,46.971,35.70,288,1.000,bilinear,-48.783,-43.147,-1
 xcit_tiny_24_p16_384_dist,33.530,66.470,52.776,47.224,12.12,384,1.000,bicubic,-49.038,-43.518,-11
-convmixer_1536_20,33.447,66.553,53.041,46.959,51.63,224,0.960,bicubic,-47.929,-42.569,+40
+convmixer_1536_20,33.447,66.553,53.041,46.959,51.63,224,0.960,bicubic,-47.929,-42.569,+43
 regnety_032,33.406,66.594,52.803,47.197,19.44,288,1.000,bicubic,-49.316,-43.629,-22
 crossvit_18_240,33.398,66.602,52.257,47.743,43.27,240,0.875,bicubic,-48.996,-43.805,-8
-gernet_l,33.380,66.620,51.919,48.081,31.08,256,0.875,bilinear,-47.966,-43.617,+39
+gernet_l,33.380,66.620,51.919,48.081,31.08,256,0.875,bilinear,-47.966,-43.617,+41
 crossvit_15_dagger_408,33.331,66.669,52.224,47.776,28.50,408,1.000,bicubic,-50.495,-44.562,-61
 crossvit_18_dagger_240,33.282,66.718,52.210,47.790,44.27,240,0.875,bicubic,-49.224,-43.862,-14
 tresnet_xl,33.274,66.726,52.308,47.692,78.44,224,0.875,bilinear,-48.784,-43.624,+7
 jx_nest_base,33.219,66.781,51.823,48.177,67.72,224,0.875,bicubic,-50.335,-44.541,-54
-resnest50d_1s4x24d,33.157,66.844,52.852,47.148,25.68,224,0.875,bicubic,-47.843,-42.474,+51
+resnest50d_1s4x24d,33.157,66.844,52.852,47.148,25.68,224,0.875,bicubic,-47.843,-42.474,+54
 resnet61q,33.123,66.877,51.756,48.244,36.85,288,1.000,bicubic,-49.399,-44.378,-20
 jx_nest_small,33.046,66.954,51.062,48.938,38.35,224,0.875,bicubic,-50.072,-45.270,-43
-crossvit_base_240,33.041,66.960,51.384,48.616,105.03,240,0.875,bicubic,-49.166,-44.444,-3
+crossvit_base_240,33.041,66.960,51.384,48.616,105.03,240,0.875,bicubic,-49.165,-44.444,-3
 twins_pcpvt_base,33.031,66.969,52.491,47.509,43.83,224,0.900,bicubic,-49.681,-43.857,-32
-xcit_tiny_24_p16_224_dist,33.013,66.987,52.068,47.932,12.12,224,1.000,bicubic,-47.449,-43.140,+72
+xcit_tiny_24_p16_224_dist,33.013,66.987,52.068,47.932,12.12,224,1.000,bicubic,-47.449,-43.140,+75
 rexnet_200,32.984,67.016,52.945,47.055,16.37,224,0.875,bicubic,-48.642,-42.727,+12
-resnest50d,32.974,67.026,52.715,47.285,27.48,224,0.875,bilinear,-47.988,-42.663,+46
-convit_small,32.928,67.072,52.098,47.902,27.78,224,0.875,bicubic,-48.483,-43.648,+20
+resnest50d,32.974,67.026,52.715,47.285,27.48,224,0.875,bilinear,-47.988,-42.663,+49
+convit_small,32.928,67.072,52.098,47.902,27.78,224,0.875,bicubic,-48.484,-43.648,+23
 tf_efficientnetv2_s,32.909,67.091,51.760,48.240,21.46,384,1.000,bicubic,-50.989,-44.938,-80
 crossvit_15_dagger_240,32.895,67.105,51.768,48.232,28.21,240,0.875,bicubic,-49.415,-44.194,-17
-vit_small_patch16_224,32.877,67.123,53.949,46.051,22.05,224,0.900,bicubic,-48.509,-42.181,+19
+vit_small_patch16_224,32.877,67.123,53.949,46.051,22.05,224,0.900,bicubic,-48.509,-42.181,+22
 pnasnet5large,32.848,67.152,50.518,49.482,86.06,331,0.911,bicubic,-49.950,-45.516,-43
 twins_svt_base,32.838,67.162,51.559,48.441,56.07,224,0.900,bicubic,-50.286,-44.869,-55
 tf_efficientnet_b3,32.834,67.166,52.955,47.045,12.23,300,0.904,bicubic,-48.812,-42.765,+3
 regnetz_c,32.809,67.191,53.756,46.244,13.46,320,0.940,bicubic,-49.707,-42.604,-33
 nasnetalarge,32.773,67.227,50.150,49.850,88.75,331,0.911,bicubic,-49.863,-45.900,-42
-gernet_m,32.754,67.246,51.917,48.083,21.14,224,0.875,bilinear,-47.972,-43.261,+48
-gluon_resnet152_v1d,32.754,67.246,51.080,48.920,60.21,224,0.875,bicubic,-47.722,-44.122,+57
-inception_resnet_v2,32.746,67.254,50.642,49.358,55.84,299,0.897,bicubic,-47.702,-44.666,+60
+gernet_m,32.754,67.246,51.917,48.083,21.14,224,0.875,bilinear,-47.972,-43.261,+51
+gluon_resnet152_v1d,32.754,67.246,51.080,48.920,60.21,224,0.875,bicubic,-47.722,-44.122,+60
+inception_resnet_v2,32.746,67.254,50.642,49.358,55.84,299,0.897,bicubic,-47.702,-44.666,+63
 pit_b_224,32.710,67.290,49.832,50.168,73.76,224,0.900,bicubic,-49.734,-45.880,-35
-tf_efficientnet_b2_ap,32.669,67.331,52.249,47.751,9.11,260,0.890,bicubic,-47.637,-42.783,+67
+tf_efficientnet_b2_ap,32.669,67.331,52.249,47.751,9.11,260,0.890,bicubic,-47.637,-42.783,+70
 cait_xxs36_384,32.569,67.431,52.218,47.782,17.37,384,1.000,bicubic,-49.621,-43.942,-21
-tresnet_l,32.561,67.439,51.147,48.853,55.99,224,0.875,bilinear,-48.923,-44.473,+2
-wide_resnet50_2,32.480,67.519,51.467,48.533,68.88,224,0.875,bicubic,-48.970,-44.051,+2
-gmlp_s16_224,32.404,67.596,51.832,48.168,19.42,224,0.875,bicubic,-47.238,-42.790,+107
+tresnet_l,32.561,67.439,51.147,48.853,55.99,224,0.875,bilinear,-48.923,-44.473,+4
+wide_resnet50_2,32.480,67.519,51.467,48.533,68.88,224,0.875,bicubic,-48.970,-44.051,+4
+gmlp_s16_224,32.404,67.596,51.832,48.168,19.42,224,0.875,bicubic,-47.238,-42.790,+110
 deit_base_patch16_224,32.367,67.633,51.031,48.969,86.57,224,0.900,bicubic,-49.617,-44.711,-18
-ens_adv_inception_resnet_v2,32.367,67.633,50.431,49.569,55.84,299,0.897,bicubic,-47.612,-44.505,+82
-swin_small_patch4_window7_224,32.355,67.645,50.931,49.069,49.61,224,0.900,bicubic,-50.871,-45.399,-73
-gluon_resnet152_v1s,32.335,67.665,50.528,49.472,60.32,224,0.875,bicubic,-48.685,-44.894,+21
-deit_small_distilled_patch16_224,32.290,67.710,52.109,47.891,22.44,224,0.900,bicubic,-48.912,-43.268,+11
+ens_adv_inception_resnet_v2,32.367,67.633,50.431,49.569,55.84,299,0.897,bicubic,-47.611,-44.505,+85
+swin_small_patch4_window7_224,32.355,67.645,50.931,49.069,49.61,224,0.900,bicubic,-50.871,-45.837,-72
+gluon_resnet152_v1s,32.335,67.665,50.528,49.472,60.32,224,0.875,bicubic,-48.685,-44.894,+24
+deit_small_distilled_patch16_224,32.290,67.710,52.109,47.891,22.44,224,0.900,bicubic,-48.912,-43.269,+13
 xcit_tiny_24_p8_224,32.270,67.730,51.913,48.087,12.11,224,1.000,bicubic,-49.624,-44.071,-20
-gluon_seresnext101_64x4d,32.207,67.793,50.331,49.669,88.23,224,0.875,bicubic,-48.663,-44.975,+27
+gluon_seresnext101_64x4d,32.207,67.793,50.331,49.669,88.23,224,0.875,bicubic,-48.663,-44.975,+30
 coat_lite_small,32.135,67.865,49.946,50.054,19.84,224,0.900,bicubic,-50.167,-45.914,-39
-gluon_seresnext101_32x4d,32.115,67.885,51.227,48.773,48.96,224,0.875,bicubic,-48.761,-44.065,+24
-seresnext50_32x4d,32.001,67.999,51.245,48.755,27.56,224,0.875,bicubic,-49.267,-44.381,+3
+gluon_seresnext101_32x4d,32.115,67.885,51.227,48.773,48.96,224,0.875,bicubic,-48.761,-44.065,+27
+seresnext50_32x4d,32.001,67.999,51.245,48.755,27.56,224,0.875,bicubic,-49.267,-44.381,+5
 deit_base_patch16_384,31.987,68.013,50.557,49.443,86.86,384,1.000,bicubic,-51.119,-45.819,-76
-xcit_tiny_12_p8_224_dist,31.952,68.048,51.434,48.566,6.71,224,1.000,bicubic,-49.262,-44.173,+3
+xcit_tiny_12_p8_224_dist,31.952,68.048,51.434,48.566,6.71,224,1.000,bicubic,-49.262,-44.172,+5
 levit_384,31.879,68.121,50.610,49.390,39.13,224,0.900,bicubic,-50.713,-45.404,-61
 resnetrs101,31.856,68.144,51.019,48.981,63.62,288,0.940,bicubic,-50.438,-44.983,-43
-cspresnext50,31.820,68.180,51.616,48.384,20.57,224,0.875,bilinear,-48.232,-43.334,+66
-tnt_s_patch16_224,31.632,68.368,51.156,48.844,23.76,224,0.900,bicubic,-49.882,-44.588,-19
+cspresnext50,31.820,68.180,51.616,48.384,20.57,224,0.875,bilinear,-48.232,-43.334,+69
+tnt_s_patch16_224,31.632,68.368,51.156,48.844,23.76,224,0.900,bicubic,-49.882,-44.588,-17
 eca_nfnet_l0,31.614,68.386,51.606,48.394,24.14,288,1.000,bicubic,-50.978,-44.880,-66
 resnetv2_50x1_bit_distilled,31.610,68.390,51.304,48.696,25.55,224,0.875,bicubic,-51.212,-45.220,-75
-ssl_resnext101_32x4d,31.461,68.539,52.137,47.863,44.18,224,0.875,bilinear,-49.461,-43.593,+13
-inception_v4,31.378,68.622,49.240,50.760,42.68,299,0.875,bicubic,-48.766,-45.732,+56
-rexnet_150,31.374,68.626,51.294,48.706,9.73,224,0.875,bicubic,-48.936,-43.866,+41
-pit_s_224,31.331,68.669,49.693,50.307,23.46,224,0.900,bicubic,-49.769,-45.642,-1
-crossvit_15_240,31.313,68.687,50.192,49.808,27.53,240,0.875,bicubic,-50.213,-45.502,-27
-cait_xxs36_224,31.276,68.724,50.616,49.384,17.30,224,1.000,bicubic,-48.486,-44.252,+75
-crossvit_small_240,31.274,68.726,50.201,49.799,26.86,240,0.875,bicubic,-49.756,-45.265,-1
-cspresnet50,31.254,68.746,51.235,48.765,21.62,256,0.887,bilinear,-48.322,-43.467,+82
-convmixer_768_32,31.254,68.746,50.958,49.042,21.11,224,0.960,bicubic,-48.906,-44.116,+49
-coat_mini,31.213,68.787,49.793,50.207,10.34,224,0.900,bicubic,-50.069,-45.601,-16
+ssl_resnext101_32x4d,31.461,68.539,52.137,47.863,44.18,224,0.875,bilinear,-49.461,-43.593,+16
+inception_v4,31.378,68.622,49.240,50.760,42.68,299,0.875,bicubic,-48.766,-45.732,+59
+rexnet_150,31.374,68.626,51.294,48.706,9.73,224,0.875,bicubic,-48.936,-43.866,+44
+pit_s_224,31.331,68.669,49.693,50.307,23.46,224,0.900,bicubic,-49.769,-45.641,+2
+crossvit_15_240,31.313,68.687,50.192,49.808,27.53,240,0.875,bicubic,-50.213,-45.502,-26
+cait_xxs36_224,31.276,68.724,50.616,49.384,17.30,224,1.000,bicubic,-48.486,-44.252,+78
+crossvit_small_240,31.274,68.726,50.201,49.799,26.86,240,0.875,bicubic,-49.756,-45.265,+2
+convmixer_768_32,31.254,68.746,50.958,49.042,21.11,224,0.960,bicubic,-48.906,-44.116,+52
+cspresnet50,31.254,68.746,51.235,48.765,21.62,256,0.887,bilinear,-48.322,-43.467,+85
+coat_mini,31.213,68.787,49.793,50.207,10.34,224,0.900,bicubic,-50.069,-45.601,-14
 xcit_tiny_12_p8_384_dist,31.166,68.834,50.524,49.476,6.71,384,1.000,bicubic,-51.226,-45.694,-67
-gluon_resnet101_v1s,31.152,68.848,49.828,50.172,44.67,224,0.875,bicubic,-49.130,-45.334,+36
-ecaresnetlight,31.138,68.862,50.262,49.738,30.16,224,0.875,bicubic,-49.316,-44.990,+22
-resmlp_36_distilled_224,31.091,68.909,49.694,50.306,44.69,224,0.875,bicubic,-50.063,-45.802,-15
-ecaresnet50d,31.083,68.917,50.858,49.142,25.58,224,0.875,bicubic,-49.537,-44.450,+11
-tf_efficientnet_cc_b0_8e,31.083,68.917,50.771,49.229,24.01,224,0.875,bicubic,-46.825,-42.885,+163
+gluon_resnet101_v1s,31.152,68.848,49.828,50.172,44.67,224,0.875,bicubic,-49.130,-45.334,+39
+ecaresnetlight,31.138,68.862,50.262,49.738,30.16,224,0.875,bicubic,-49.316,-44.990,+25
+resmlp_36_distilled_224,31.091,68.909,49.694,50.306,44.69,224,0.875,bicubic,-50.063,-45.802,-12
+ecaresnet50d,31.083,68.917,50.858,49.142,25.58,224,0.875,bicubic,-49.537,-44.450,+14
+tf_efficientnet_cc_b0_8e,31.083,68.917,50.771,49.229,24.01,224,0.875,bicubic,-46.825,-42.885,+168
 ecaresnet50t,31.066,68.934,50.596,49.404,25.57,320,0.950,bicubic,-51.298,-45.546,-70
-resnet50d,31.038,68.962,49.844,50.156,25.58,224,0.875,bicubic,-49.500,-45.316,+11
-gluon_resnet152_v1c,31.017,68.984,48.940,51.060,60.21,224,0.875,bicubic,-48.895,-45.912,+49
-cspdarknet53,31.015,68.985,50.414,49.586,27.64,256,0.887,bilinear,-49.035,-44.678,+44
-gcresnet50t,31.015,68.985,50.131,49.869,25.90,256,0.900,bicubic,-49.923,-45.309,-8
-gluon_resnext101_64x4d,31.003,68.997,48.559,51.441,83.46,224,0.875,bicubic,-49.623,-46.443,+3
+resnet50d,31.038,68.962,49.844,50.156,25.58,224,0.875,bicubic,-49.500,-45.316,+14
+gluon_resnet152_v1c,31.017,68.984,48.940,51.060,60.21,224,0.875,bicubic,-48.895,-45.912,+52
+cspdarknet53,31.015,68.985,50.414,49.586,27.64,256,0.887,bilinear,-49.035,-44.678,+47
+gcresnet50t,31.015,68.985,50.131,49.869,25.90,256,0.900,bicubic,-49.923,-45.309,-5
+gluon_resnext101_64x4d,31.003,68.997,48.559,51.441,83.46,224,0.875,bicubic,-49.623,-46.443,+6
 twins_svt_small,31.001,68.999,49.237,50.763,24.06,224,0.900,bicubic,-50.681,-46.441,-50
-ecaresnet101d_pruned,30.908,69.092,50.017,49.983,24.88,224,0.875,bicubic,-49.904,-45.623,-6
-resmlp_24_distilled_224,30.889,69.111,50.184,49.816,30.02,224,0.875,bicubic,-49.871,-45.036,-5
-tf_efficientnet_cc_b1_8e,30.887,69.113,50.076,49.924,39.72,240,0.882,bicubic,-48.439,-44.292,+76
-gluon_resnext101_32x4d,30.885,69.115,48.563,51.437,44.18,224,0.875,bicubic,-49.453,-46.345,+16
+ecaresnet101d_pruned,30.908,69.092,50.017,49.983,24.88,224,0.875,bicubic,-49.904,-45.623,-3
+resmlp_24_distilled_224,30.889,69.111,50.184,49.816,30.02,224,0.875,bicubic,-49.871,-45.036,-2
+tf_efficientnet_cc_b1_8e,30.887,69.113,50.076,49.924,39.72,240,0.882,bicubic,-48.439,-44.292,+79
+gluon_resnext101_32x4d,30.885,69.115,48.563,51.437,44.18,224,0.875,bicubic,-49.453,-46.345,+19
 tf_efficientnetv2_b3,30.873,69.127,49.808,50.192,14.36,300,0.904,bicubic,-51.081,-45.976,-61
-tf_efficientnet_lite4,30.840,69.160,50.400,49.600,13.01,380,0.920,bilinear,-50.700,-45.260,-52
-nf_resnet50,30.730,69.270,49.968,50.032,25.56,288,0.940,bicubic,-49.926,-45.368,-6
-ese_vovnet39b,30.696,69.304,49.879,50.121,24.57,224,0.875,bicubic,-48.608,-44.845,+74
-dpn107,30.671,69.329,48.828,51.172,86.92,224,0.875,bicubic,-49.501,-46.076,+24
-xcit_tiny_24_p16_224,30.671,69.329,50.386,49.614,12.12,224,1.000,bicubic,-48.781,-44.502,+64
-tresnet_xl_448,30.625,69.374,49.075,50.925,78.44,448,0.875,bilinear,-52.430,-47.109,-115
-gluon_resnet152_v1b,30.622,69.379,48.523,51.477,60.19,224,0.875,bicubic,-49.059,-46.213,+51
-haloregnetz_b,30.614,69.386,48.999,51.001,11.68,224,0.940,bicubic,-50.428,-46.201,-32
-ssl_resnext50_32x4d,30.596,69.404,50.687,49.313,25.03,224,0.875,bilinear,-49.706,-44.731,+9
-gluon_resnet101_v1d,30.531,69.469,47.977,52.023,44.57,224,0.875,bicubic,-49.873,-47.047,0
-dpn68b,30.521,69.479,49.136,50.864,12.61,224,0.875,bicubic,-48.695,-45.286,+76
-resnest26d,30.496,69.504,50.665,49.335,17.07,224,0.875,bilinear,-47.982,-43.631,+107
-efficientnet_b2,30.445,69.555,49.698,50.302,9.11,288,1.000,bicubic,-50.165,-45.618,-14
-tf_efficientnet_b1_ap,30.419,69.581,49.555,50.445,7.79,240,0.882,bicubic,-48.855,-44.747,+68
-resnetv2_50,30.409,69.591,48.844,51.156,25.55,224,0.950,bicubic,-49.997,-46.236,-6
-xcit_tiny_12_p16_384_dist,30.392,69.608,50.127,49.873,6.72,384,1.000,bicubic,-50.552,-45.287,-32
-twins_pcpvt_small,30.378,69.622,49.394,50.606,24.11,224,0.900,bicubic,-50.726,-46.248,-43
+tf_efficientnet_lite4,30.840,69.160,50.400,49.600,13.01,380,0.920,bilinear,-50.700,-45.260,-51
+nf_resnet50,30.730,69.270,49.968,50.032,25.56,288,0.940,bicubic,-49.926,-45.368,-3
+ese_vovnet39b,30.696,69.304,49.879,50.121,24.57,224,0.875,bicubic,-48.608,-44.845,+77
+dpn107,30.671,69.329,48.828,51.172,86.92,224,0.875,bicubic,-49.501,-46.076,+27
+xcit_tiny_24_p16_224,30.671,69.329,50.386,49.614,12.12,224,1.000,bicubic,-48.781,-44.502,+67
+tresnet_xl_448,30.625,69.374,49.075,50.925,78.44,448,0.875,bilinear,-52.431,-47.109,-115
+gluon_resnet152_v1b,30.622,69.379,48.523,51.477,60.19,224,0.875,bicubic,-49.058,-46.213,+54
+haloregnetz_b,30.614,69.386,48.999,51.001,11.68,224,0.940,bicubic,-50.428,-46.201,-29
+ssl_resnext50_32x4d,30.596,69.404,50.687,49.313,25.03,224,0.875,bilinear,-49.706,-44.731,+12
+gluon_resnet101_v1d,30.531,69.469,47.977,52.023,44.57,224,0.875,bicubic,-49.873,-47.047,+3
+dpn68b,30.521,69.479,49.136,50.864,12.61,224,0.875,bicubic,-48.695,-45.286,+81
+resnest26d,30.496,69.504,50.665,49.335,17.07,224,0.875,bilinear,-47.982,-43.631,+112
+efficientnet_b2,30.445,69.555,49.698,50.302,9.11,288,1.000,bicubic,-50.165,-45.618,-11
+tf_efficientnet_b1_ap,30.419,69.581,49.555,50.445,7.79,240,0.882,bicubic,-48.855,-44.747,+71
+resnetv2_50,30.409,69.591,48.844,51.156,25.55,224,0.950,bicubic,-49.997,-46.236,-3
+xcit_tiny_12_p16_384_dist,30.392,69.608,50.127,49.873,6.72,384,1.000,bicubic,-50.552,-45.287,-29
+twins_pcpvt_small,30.378,69.622,49.394,50.606,24.11,224,0.900,bicubic,-50.726,-46.248,-40
 visformer_small,30.337,69.663,48.303,51.697,40.22,224,0.900,bicubic,-51.759,-47.575,-85
-pit_xs_distilled_224,30.280,69.720,49.830,50.170,11.00,224,0.900,bicubic,-49.014,-44.544,+62
-convmixer_1024_20_ks9_p14,30.081,69.919,49.928,50.072,24.38,224,0.960,bicubic,-46.863,-43.430,+169
-dpn98,30.065,69.935,48.252,51.748,61.57,224,0.875,bicubic,-49.589,-46.352,+39
-seresnet50,30.061,69.939,49.327,50.673,28.09,224,0.875,bicubic,-50.187,-45.743,0
-dpn131,30.036,69.964,48.144,51.856,79.25,224,0.875,bicubic,-49.798,-46.568,+24
-efficientnet_el,30.028,69.972,48.840,51.160,10.59,300,0.904,bicubic,-51.278,-46.696,-59
-tf_efficientnet_b2,30.020,69.980,49.592,50.408,9.11,260,0.890,bicubic,-50.048,-45.312,+9
-xcit_tiny_12_p16_224_dist,29.999,70.001,49.681,50.319,6.72,224,1.000,bicubic,-48.581,-44.523,+88
-legacy_senet154,29.989,70.011,48.056,51.944,115.09,224,0.875,bilinear,-51.337,-47.450,-63
-dpn92,29.977,70.023,49.201,50.799,37.67,224,0.875,bicubic,-50.017,-45.635,+9
+pit_xs_distilled_224,30.280,69.720,49.830,50.170,11.00,224,0.900,bicubic,-49.014,-44.544,+65
+convmixer_1024_20_ks9_p14,30.081,69.919,49.928,50.072,24.38,224,0.960,bicubic,-46.863,-43.430,+174
+dpn98,30.065,69.935,48.252,51.748,61.57,224,0.875,bicubic,-49.589,-46.352,+42
+seresnet50,30.061,69.939,49.327,50.673,28.09,224,0.875,bicubic,-50.187,-45.743,+4
+dpn131,30.036,69.964,48.144,51.856,79.25,224,0.875,bicubic,-49.798,-46.568,+29
+efficientnet_el,30.028,69.972,48.840,51.160,10.59,300,0.904,bicubic,-51.278,-46.696,-57
+tf_efficientnet_b2,30.020,69.980,49.592,50.408,9.11,260,0.890,bicubic,-50.048,-45.312,+12
+xcit_tiny_12_p16_224_dist,29.999,70.001,49.681,50.319,6.72,224,1.000,bicubic,-48.581,-44.523,+93
+legacy_senet154,29.989,70.011,48.056,51.944,115.09,224,0.875,bilinear,-51.337,-47.450,-61
+dpn92,29.977,70.023,49.201,50.799,37.67,224,0.875,bicubic,-50.017,-45.635,+12
 resnetv2_101x1_bitm,29.922,70.078,51.129,48.871,44.54,448,1.000,bilinear,-52.408,-45.399,-108
-xception,29.887,70.113,48.716,51.284,22.86,299,0.897,bicubic,-49.161,-45.680,+66
-gluon_senet154,29.881,70.119,47.885,52.115,115.09,224,0.875,bicubic,-51.343,-47.467,-63
-adv_inception_v3,29.820,70.180,47.867,52.133,23.83,299,0.875,bicubic,-47.758,-45.873,+133
-gluon_xception65,29.804,70.196,47.776,52.224,39.92,299,0.903,bicubic,-49.898,-47.091,+24
-resmlp_36_224,29.710,70.290,48.981,51.019,44.69,224,0.875,bicubic,-50.066,-45.905,+18
-resnet50,29.649,70.351,46.753,53.247,25.56,224,0.950,bicubic,-50.733,-47.841,-23
-resnetblur50,29.613,70.386,48.260,51.740,25.56,224,0.875,bicubic,-49.686,-46.270,+42
-jx_nest_tiny,29.555,70.445,46.992,53.008,17.06,224,0.875,bicubic,-51.879,-48.628,-81
-efficientnet_em,29.482,70.518,48.944,51.056,6.90,240,0.882,bicubic,-49.778,-45.848,+45
-gcresnext50ts,29.446,70.554,47.898,52.102,15.67,256,0.900,bicubic,-51.148,-47.282,-39
-resnext101_32x8d,29.437,70.563,48.510,51.490,88.79,224,0.875,bilinear,-49.875,-46.013,+36
-coat_lite_mini,29.427,70.573,47.727,52.273,11.01,224,0.900,bicubic,-49.673,-46.875,+51
-ssl_resnet50,29.425,70.575,49.785,50.215,25.56,224,0.875,bilinear,-49.811,-45.047,+42
-deit_small_patch16_224,29.413,70.587,48.260,51.740,22.05,224,0.900,bicubic,-50.453,-46.796,+2
-cait_xxs24_384,29.405,70.595,48.751,51.249,12.03,384,1.000,bicubic,-51.549,-46.887,-61
-nf_regnet_b1,29.391,70.609,49.447,50.553,10.22,288,0.900,bicubic,-49.905,-45.295,+35
-resnext50_32x4d,29.358,70.642,47.409,52.591,25.03,224,0.875,bicubic,-50.442,-47.205,+5
-swin_tiny_patch4_window7_224,29.342,70.658,47.621,52.379,28.29,224,0.900,bicubic,-52.044,-47.915,-89
-resnet34d,29.325,70.675,48.427,51.573,21.82,224,0.875,bicubic,-47.789,-44.955,+133
-cait_xxs24_224,29.305,70.695,48.535,51.465,11.96,224,1.000,bicubic,-49.071,-45.781,+80
-ecaresnet50d_pruned,29.215,70.785,48.455,51.545,19.94,224,0.875,bicubic,-50.491,-46.419,+6
+xception,29.887,70.113,48.716,51.284,22.86,299,0.897,bicubic,-49.161,-45.680,+71
+gluon_senet154,29.881,70.119,47.885,52.115,115.09,224,0.875,bicubic,-51.343,-47.467,-61
+adv_inception_v3,29.820,70.180,47.867,52.133,23.83,299,0.875,bicubic,-47.758,-45.873,+138
+gluon_xception65,29.804,70.196,47.776,52.224,39.92,299,0.903,bicubic,-49.898,-47.092,+27
+resmlp_36_224,29.710,70.290,48.981,51.019,44.69,224,0.875,bicubic,-50.066,-45.905,+21
+resnet50,29.649,70.351,46.753,53.247,25.56,224,0.950,bicubic,-50.733,-47.841,-20
+resnetblur50,29.613,70.386,48.260,51.740,25.56,224,0.875,bicubic,-49.687,-46.376,+46
+jx_nest_tiny,29.555,70.445,46.992,53.008,17.06,224,0.875,bicubic,-51.879,-48.628,-79
+efficientnet_em,29.482,70.518,48.944,51.056,6.90,240,0.882,bicubic,-49.778,-45.848,+50
+gcresnext50ts,29.446,70.554,47.898,52.102,15.67,256,0.900,bicubic,-51.148,-47.282,-36
+resnext101_32x8d,29.437,70.563,48.510,51.490,88.79,224,0.875,bilinear,-49.875,-46.012,+39
+coat_lite_mini,29.427,70.573,47.727,52.273,11.01,224,0.900,bicubic,-49.673,-46.875,+56
+ssl_resnet50,29.425,70.575,49.785,50.215,25.56,224,0.875,bilinear,-49.811,-45.047,+47
+deit_small_patch16_224,29.413,70.587,48.260,51.740,22.05,224,0.900,bicubic,-50.453,-46.796,+5
+cait_xxs24_384,29.405,70.595,48.751,51.249,12.03,384,1.000,bicubic,-51.549,-46.887,-58
+nf_regnet_b1,29.391,70.609,49.447,50.553,10.22,288,0.900,bicubic,-49.905,-45.295,+38
+resnext50_32x4d,29.358,70.642,47.409,52.591,25.03,224,0.875,bicubic,-50.442,-47.205,+8
+swin_tiny_patch4_window7_224,29.342,70.658,47.621,52.379,28.29,224,0.900,bicubic,-52.044,-47.915,-86
+resnet34d,29.325,70.675,48.427,51.573,21.82,224,0.875,bicubic,-47.789,-44.955,+138
+cait_xxs24_224,29.305,70.695,48.535,51.465,11.96,224,1.000,bicubic,-49.071,-45.781,+85
+ecaresnet50d_pruned,29.215,70.785,48.455,51.545,19.94,224,0.875,bicubic,-50.491,-46.419,+9
 tresnet_l_448,29.179,70.821,47.244,52.756,55.99,448,0.875,bilinear,-53.083,-48.736,-124
-gluon_inception_v3,29.134,70.866,46.963,53.037,23.83,299,0.875,bicubic,-49.664,-47.417,+55
-eca_resnet33ts,29.097,70.903,48.814,51.186,19.68,256,0.900,bicubic,-50.999,-46.160,-21
-xception71,29.053,70.947,47.443,52.557,42.34,299,0.903,bicubic,-50.831,-47.489,-12
-hrnet_w64,28.992,71.007,47.140,52.860,128.06,224,0.875,bilinear,-50.464,-47.514,+13
-regnetz_b,28.934,71.066,47.244,52.756,9.72,288,0.940,bicubic,-51.784,-48.230,-61
-xcit_tiny_12_p8_224,28.934,71.066,47.543,52.457,6.71,224,1.000,bicubic,-50.776,-47.515,-2
-tf_efficientnet_b0_ns,28.908,71.092,48.983,51.017,5.29,224,0.875,bicubic,-49.750,-45.387,+55
-xception65,28.904,71.096,47.161,52.839,39.92,299,0.903,bicubic,-50.642,-47.498,+5
-gluon_resnet101_v1b,28.894,71.106,46.395,53.605,44.55,224,0.875,bicubic,-50.406,-48.241,+19
-vit_small_patch32_384,28.871,71.129,48.912,51.088,22.92,384,1.000,bicubic,-51.615,-46.686,-59
-tf_efficientnet_b1,28.871,71.129,47.513,52.487,7.79,240,0.882,bicubic,-49.965,-46.681,+44
-skresnext50_32x4d,28.855,71.145,46.503,53.497,27.48,224,0.875,bicubic,-51.287,-48.141,-32
-sehalonet33ts,28.768,71.231,46.576,53.424,13.69,256,0.940,bicubic,-52.213,-48.696,-83
-levit_256,28.767,71.234,46.702,53.298,18.89,224,0.900,bicubic,-52.735,-48.778,-112
-tf_efficientnet_lite3,28.668,71.332,47.368,52.632,8.20,300,0.904,bilinear,-51.152,-47.542,-16
-skresnet34,28.654,71.346,47.969,52.031,22.28,224,0.875,bicubic,-48.266,-45.351,+123
-gluon_seresnext50_32x4d,28.649,71.351,46.460,53.540,27.56,224,0.875,bicubic,-51.275,-48.368,-29
-hrnet_w40,28.631,71.369,47.460,52.540,57.56,224,0.875,bilinear,-50.295,-47.018,+32
-tf_efficientnetv2_b0,28.574,71.426,47.097,52.903,7.14,224,0.875,bicubic,-49.796,-46.929,+60
-tv_resnet152,28.539,71.461,47.134,52.866,60.19,224,0.875,bilinear,-49.783,-46.910,+60
-xcit_tiny_12_p16_224,28.529,71.471,47.419,52.581,6.72,224,1.000,bicubic,-48.591,-46.299,+108
-repvgg_b2,28.444,71.556,47.040,52.960,89.02,224,0.875,bilinear,-50.350,-47.386,+35
-hrnet_w48,28.427,71.573,47.588,52.412,77.47,224,0.875,bilinear,-50.895,-46.926,+1
-halonet50ts,28.397,71.603,45.827,54.173,22.73,256,0.940,bicubic,-52.953,-49.457,-113
-gluon_resnext50_32x4d,28.383,71.617,45.356,54.644,25.03,224,0.875,bicubic,-50.981,-49.068,-3
-efficientnet_b2_pruned,28.362,71.638,47.055,52.945,8.31,260,0.890,bicubic,-51.544,-47.799,-36
-tf_efficientnet_b0_ap,28.354,71.646,47.535,52.465,5.29,224,0.875,bicubic,-48.750,-45.729,+104
-seresnet33ts,28.352,71.648,47.761,52.239,19.78,256,0.900,bicubic,-52.020,-47.353,-66
-dla169,28.344,71.656,47.393,52.607,53.39,224,0.875,bilinear,-50.354,-46.939,+30
-tf_efficientnet_cc_b0_4e,28.344,71.656,47.370,52.630,13.31,224,0.875,bicubic,-48.976,-45.952,+94
-dla102x2,28.330,71.670,46.786,53.214,41.28,224,0.875,bilinear,-51.110,-47.858,-12
-mixnet_xl,28.289,71.711,46.700,53.300,11.90,224,0.875,bicubic,-52.179,-48.232,-78
-gluon_resnet50_v1d,28.238,71.762,45.922,54.078,25.58,224,0.875,bicubic,-50.826,-48.538,+10
-gluon_resnet101_v1c,28.120,71.880,45.994,54.006,44.57,224,0.875,bicubic,-51.414,-48.594,-20
-wide_resnet101_2,28.116,71.884,46.425,53.575,126.89,224,0.875,bilinear,-50.738,-47.859,+17
-densenet161,28.098,71.902,46.647,53.353,28.68,224,0.875,bicubic,-49.254,-46.989,+87
-regnetx_320,28.095,71.906,45.128,54.872,107.81,224,0.875,bicubic,-52.154,-49.898,-67
-regnety_320,28.073,71.927,45.458,54.542,145.05,224,0.875,bicubic,-52.721,-49.788,-98
-gernet_s,28.040,71.960,46.745,53.255,8.17,224,0.875,bilinear,-48.867,-46.389,+101
-levit_192,28.038,71.963,45.872,54.128,10.95,224,0.900,bicubic,-51.822,-48.930,-45
-efficientnet_el_pruned,28.006,71.994,46.798,53.202,10.59,300,0.904,bicubic,-52.282,-48.424,-73
-xception41,27.892,72.108,45.894,54.106,26.97,299,0.903,bicubic,-50.640,-48.390,+23
+gluon_inception_v3,29.134,70.866,46.963,53.037,23.83,299,0.875,bicubic,-49.664,-47.417,+60
+eca_resnet33ts,29.097,70.903,48.814,51.186,19.68,256,0.900,bicubic,-50.999,-46.160,-18
+lambda_resnet50ts,29.097,70.903,46.967,53.033,21.54,256,0.950,bicubic,-52.069,-48.129,-81
+xception71,29.053,70.947,47.443,52.557,42.34,299,0.903,bicubic,-50.831,-47.489,-10
+hrnet_w64,28.992,71.007,47.140,52.860,128.06,224,0.875,bilinear,-50.464,-47.514,+15
+regnetz_b,28.934,71.066,47.244,52.756,9.72,288,0.940,bicubic,-51.784,-48.230,-59
+xcit_tiny_12_p8_224,28.934,71.066,47.543,52.457,6.71,224,1.000,bicubic,-50.776,-47.515,0
+tf_efficientnet_b0_ns,28.908,71.092,48.983,51.017,5.29,224,0.875,bicubic,-49.750,-45.387,+59
+xception65,28.904,71.096,47.161,52.839,39.92,299,0.903,bicubic,-50.642,-47.499,+7
+gluon_resnet101_v1b,28.894,71.106,46.395,53.605,44.55,224,0.875,bicubic,-50.406,-48.135,+20
+tf_efficientnet_b1,28.871,71.129,47.513,52.487,7.79,240,0.882,bicubic,-49.965,-46.681,+47
+vit_small_patch32_384,28.871,71.129,48.912,51.088,22.92,384,1.000,bicubic,-51.615,-46.686,-56
+skresnext50_32x4d,28.855,71.145,46.503,53.497,27.48,224,0.875,bicubic,-51.287,-48.141,-30
+sehalonet33ts,28.768,71.231,46.576,53.424,13.69,256,0.940,bicubic,-52.214,-48.696,-81
+levit_256,28.767,71.234,46.702,53.298,18.89,224,0.900,bicubic,-52.735,-48.778,-111
+tf_efficientnet_lite3,28.668,71.332,47.368,52.632,8.20,300,0.904,bilinear,-51.152,-47.542,-14
+skresnet34,28.654,71.346,47.969,52.031,22.28,224,0.875,bicubic,-48.266,-45.351,+127
+gluon_seresnext50_32x4d,28.649,71.351,46.460,53.540,27.56,224,0.875,bicubic,-51.275,-48.368,-27
+hrnet_w40,28.631,71.369,47.460,52.540,57.56,224,0.875,bilinear,-50.295,-47.018,+36
+tf_efficientnetv2_b0,28.574,71.426,47.097,52.903,7.14,224,0.875,bicubic,-49.796,-46.929,+64
+tv_resnet152,28.539,71.461,47.134,52.866,60.19,224,0.875,bilinear,-49.783,-46.910,+64
+xcit_tiny_12_p16_224,28.529,71.471,47.419,52.581,6.72,224,1.000,bicubic,-48.591,-46.299,+112
+repvgg_b2,28.444,71.556,47.040,52.960,89.02,224,0.875,bilinear,-50.350,-47.386,+39
+hrnet_w48,28.427,71.573,47.588,52.412,77.47,224,0.875,bilinear,-50.895,-46.926,+3
+gluon_resnext50_32x4d,28.383,71.617,45.356,54.644,25.03,224,0.875,bicubic,-50.981,-49.068,0
+efficientnet_b2_pruned,28.362,71.638,47.055,52.945,8.31,260,0.890,bicubic,-51.544,-47.799,-33
+tf_efficientnet_b0_ap,28.354,71.646,47.535,52.465,5.29,224,0.875,bicubic,-48.750,-45.729,+109
+seresnet33ts,28.352,71.648,47.761,52.239,19.78,256,0.900,bicubic,-52.020,-47.353,-63
+dla169,28.344,71.656,47.393,52.607,53.39,224,0.875,bilinear,-50.354,-46.939,+35
+tf_efficientnet_cc_b0_4e,28.344,71.656,47.370,52.630,13.31,224,0.875,bicubic,-48.976,-45.952,+99
+dla102x2,28.330,71.670,46.786,53.214,41.28,224,0.875,bilinear,-51.110,-47.858,-9
+mixnet_xl,28.289,71.711,46.700,53.300,11.90,224,0.875,bicubic,-52.179,-48.232,-75
+gluon_resnet50_v1d,28.238,71.762,45.922,54.078,25.58,224,0.875,bicubic,-50.826,-48.538,+15
+lamhalobotnet50ts_256,28.169,71.831,45.320,54.680,22.57,256,0.950,bicubic,-53.253,-49.736,-126
+gluon_resnet101_v1c,28.120,71.880,45.994,54.006,44.57,224,0.875,bicubic,-51.414,-48.594,-18
+wide_resnet101_2,28.116,71.884,46.425,53.575,126.89,224,0.875,bilinear,-50.738,-47.859,+21
+densenet161,28.098,71.902,46.647,53.353,28.68,224,0.875,bicubic,-49.254,-46.989,+91
+regnetx_320,28.095,71.906,45.128,54.872,107.81,224,0.875,bicubic,-52.153,-49.898,-65
+regnety_320,28.073,71.927,45.458,54.542,145.05,224,0.875,bicubic,-52.721,-49.788,-96
+gernet_s,28.040,71.960,46.745,53.255,8.17,224,0.875,bilinear,-48.866,-46.389,+105
+levit_192,28.038,71.963,45.872,54.128,10.95,224,0.900,bicubic,-51.822,-48.930,-43
+efficientnet_el_pruned,28.006,71.994,46.798,53.202,10.59,300,0.904,bicubic,-52.282,-48.424,-71
+xception41,27.892,72.108,45.894,54.106,26.97,299,0.903,bicubic,-50.640,-48.390,+27
+halo2botnet50ts_256,27.866,72.133,45.185,54.815,22.64,256,0.950,bicubic,-53.654,-50.073,-143
 regnetx_160,27.839,72.161,45.627,54.373,54.28,224,0.875,bicubic,-51.995,-49.197,-45
-tf_inception_v3,27.802,72.198,45.729,54.271,23.83,299,0.875,bicubic,-50.058,-47.917,+60
-res2net101_26w_4s,27.790,72.210,45.194,54.806,45.21,224,0.875,bilinear,-51.402,-49.244,-7
+tf_inception_v3,27.802,72.198,45.729,54.271,23.83,299,0.875,bicubic,-50.058,-47.917,+62
+res2net101_26w_4s,27.790,72.210,45.194,54.806,45.21,224,0.875,bilinear,-51.402,-49.244,-4
+halonet50ts,27.790,72.210,45.633,54.367,22.73,256,0.940,bicubic,-53.758,-49.679,-150
 tf_efficientnetv2_b1,27.762,72.238,46.584,53.416,8.14,240,0.882,bicubic,-51.712,-48.136,-30
 vit_base_patch16_sam_224,27.719,72.281,45.104,54.896,86.57,224,0.900,bicubic,-52.523,-49.658,-74
-repvgg_b1,27.662,72.338,46.505,53.495,57.42,224,0.875,bilinear,-50.716,-47.599,+29
-hrnet_w44,27.633,72.367,45.833,54.167,67.06,224,0.875,bilinear,-51.257,-48.549,+2
+repvgg_b1,27.662,72.338,46.505,53.495,57.42,224,0.875,bilinear,-50.716,-47.599,+31
+hrnet_w44,27.633,72.367,45.833,54.167,67.06,224,0.875,bilinear,-51.257,-48.549,+4
 gcresnet33ts,27.599,72.401,46.218,53.782,19.88,256,0.900,bicubic,-52.487,-48.774,-68
-inception_v3,27.582,72.418,45.265,54.735,23.83,299,0.875,bicubic,-49.882,-48.211,+68
+inception_v3,27.582,72.418,45.265,54.735,23.83,299,0.875,bicubic,-49.882,-48.211,+70
 resmlp_24_224,27.530,72.469,45.705,54.295,30.02,224,0.875,bicubic,-51.856,-48.841,-32
-pit_xs_224,27.472,72.528,45.918,54.082,10.62,224,0.900,bicubic,-50.712,-48.246,+33
-regnetx_080,27.387,72.613,44.998,55.002,39.57,224,0.875,bicubic,-51.833,-49.548,-19
-hrnet_w30,27.383,72.617,46.552,53.448,37.71,224,0.875,bilinear,-50.819,-47.676,+30
-hrnet_w32,27.379,72.621,46.024,53.976,41.23,224,0.875,bilinear,-51.063,-48.172,+17
-gluon_resnet50_v1s,27.328,72.672,45.257,54.743,25.68,224,0.875,bicubic,-51.368,-48.991,+3
-res2net50_26w_8s,27.308,72.692,44.835,55.165,48.40,224,0.875,bilinear,-51.672,-49.449,-10
-densenet201,27.279,72.721,46.210,53.790,20.01,224,0.875,bicubic,-50.011,-47.270,+66
-densenetblur121d,27.250,72.751,46.319,53.681,8.00,224,0.875,bicubic,-49.341,-46.874,+89
+pit_xs_224,27.472,72.528,45.918,54.082,10.62,224,0.900,bicubic,-50.712,-48.246,+35
+regnetx_080,27.387,72.613,44.998,55.002,39.57,224,0.875,bicubic,-51.833,-49.548,-17
+hrnet_w30,27.383,72.617,46.552,53.448,37.71,224,0.875,bilinear,-50.819,-47.676,+32
+hrnet_w32,27.379,72.621,46.024,53.976,41.23,224,0.875,bilinear,-51.063,-48.134,+18
+gluon_resnet50_v1s,27.328,72.672,45.257,54.743,25.68,224,0.875,bicubic,-51.368,-48.991,+5
+res2net50_26w_8s,27.308,72.692,44.835,55.165,48.40,224,0.875,bilinear,-51.672,-49.449,-9
+densenet201,27.279,72.721,46.210,53.790,20.01,224,0.875,bicubic,-50.011,-47.270,+68
+densenetblur121d,27.250,72.751,46.319,53.681,8.00,224,0.875,bicubic,-49.340,-46.873,+92
 regnety_064,27.226,72.774,44.856,55.144,30.58,224,0.875,bicubic,-52.504,-49.906,-58
 tf_efficientnetv2_b2,27.181,72.819,44.556,55.444,10.10,260,0.890,bicubic,-53.033,-50.488,-86
-efficientnet_b1_pruned,27.173,72.827,45.874,54.126,6.33,240,0.882,bicubic,-51.077,-47.962,+19
-resnet33ts,27.141,72.859,45.346,54.654,19.68,256,0.900,bicubic,-52.073,-49.226,-27
+efficientnet_b1_pruned,27.173,72.827,45.874,54.126,6.33,240,0.882,bicubic,-51.077,-47.962,+21
+resnet33ts,27.141,72.859,45.346,54.654,19.68,256,0.900,bicubic,-52.073,-49.226,-25
 resnetrs50,27.116,72.884,45.051,54.949,35.69,224,0.910,bicubic,-52.754,-49.919,-72
 rexnet_130,27.114,72.886,45.951,54.049,7.56,224,0.875,bicubic,-52.382,-48.723,-51
-dla102x,27.059,72.941,45.507,54.493,26.31,224,0.875,bilinear,-51.453,-48.719,-1
-resnet32ts,27.047,72.953,45.287,54.713,17.96,256,0.900,bicubic,-51.973,-49.075,-22
-gmixer_24_224,27.016,72.984,44.375,55.625,24.72,224,0.875,bicubic,-51.036,-49.293,+23
-tv_resnet101,26.974,73.026,45.236,54.764,44.55,224,0.875,bilinear,-50.394,-48.324,+52
+dla102x,27.059,72.941,45.507,54.493,26.31,224,0.875,bilinear,-51.453,-48.719,+1
+resnet32ts,27.047,72.953,45.287,54.713,17.96,256,0.900,bicubic,-51.973,-49.075,-20
+gmixer_24_224,27.016,72.984,44.375,55.625,24.72,224,0.875,bicubic,-51.036,-49.293,+25
+tv_resnet101,26.974,73.026,45.236,54.764,44.55,224,0.875,bilinear,-50.394,-48.324,+54
 resnext50d_32x4d,26.880,73.120,44.456,55.544,25.05,224,0.875,bicubic,-52.784,-50.410,-63
 regnetx_120,26.866,73.134,44.666,55.334,46.11,224,0.875,bicubic,-52.740,-50.064,-61
-rexnet_100,26.864,73.136,45.379,54.621,4.80,224,0.875,bicubic,-50.996,-48.497,+30
-densenet169,26.841,73.159,45.414,54.586,14.15,224,0.875,bicubic,-49.057,-47.610,+89
+rexnet_100,26.864,73.136,45.379,54.621,4.80,224,0.875,bicubic,-50.996,-48.497,+33
+densenet169,26.841,73.159,45.414,54.586,14.15,224,0.875,bicubic,-49.057,-47.610,+91
 regnety_120,26.811,73.189,44.489,55.511,51.82,224,0.875,bicubic,-53.575,-50.633,-115
-regnetx_064,26.805,73.195,44.945,55.055,26.21,224,0.875,bicubic,-52.255,-49.521,-32
-legacy_seresnext101_32x4d,26.797,73.203,43.497,56.503,48.96,224,0.875,bilinear,-53.424,-51.515,-103
-regnetx_032,26.721,73.279,45.255,54.745,15.30,224,0.875,bicubic,-51.429,-48.831,+9
-legacy_seresnet152,26.674,73.326,43.951,56.049,66.82,224,0.875,bilinear,-51.988,-50.425,-18
-densenet121,26.670,73.330,45.892,54.108,7.98,224,0.875,bicubic,-48.898,-46.760,+87
-efficientnet_es,26.621,73.379,45.126,54.874,5.44,224,0.875,bicubic,-51.461,-48.818,+10
-res2net50_26w_6s,26.595,73.405,44.006,55.994,37.05,224,0.875,bilinear,-51.971,-50.112,-18
-repvgg_b1g4,26.583,73.417,45.084,54.916,39.97,224,0.875,bilinear,-51.011,-48.758,+29
-dla60x,26.564,73.436,45.049,54.951,17.35,224,0.875,bilinear,-51.682,-48.975,-1
+regnetx_064,26.805,73.195,44.945,55.055,26.21,224,0.875,bicubic,-52.255,-49.521,-30
+legacy_seresnext101_32x4d,26.797,73.203,43.497,56.503,48.96,224,0.875,bilinear,-53.425,-51.515,-103
+regnetx_032,26.721,73.279,45.255,54.745,15.30,224,0.875,bicubic,-51.429,-48.831,+11
+legacy_seresnet152,26.674,73.326,43.951,56.049,66.82,224,0.875,bilinear,-51.988,-50.425,-16
+densenet121,26.670,73.330,45.892,54.108,7.98,224,0.875,bicubic,-48.898,-46.760,+89
+efficientnet_es,26.621,73.379,45.126,54.874,5.44,224,0.875,bicubic,-51.461,-48.818,+12
+res2net50_26w_6s,26.595,73.405,44.006,55.994,37.05,224,0.875,bilinear,-51.971,-50.112,-16
+repvgg_b1g4,26.583,73.417,45.084,54.916,39.97,224,0.875,bilinear,-51.011,-48.758,+31
+dla60x,26.564,73.436,45.049,54.951,17.35,224,0.875,bilinear,-51.682,-48.975,+1
 regnety_080,26.540,73.460,44.375,55.625,39.18,224,0.875,bicubic,-53.332,-50.457,-93
-coat_lite_tiny,26.530,73.470,44.642,55.358,5.72,224,0.900,bicubic,-50.984,-49.274,+31
-tf_efficientnet_b0,26.483,73.517,45.654,54.346,5.29,224,0.875,bicubic,-50.363,-47.576,+54
-mobilenetv3_large_100_miil,26.469,73.531,44.493,55.507,5.48,224,0.875,bilinear,-51.443,-48.411,+11
-res2net50_14w_8s,26.467,73.533,44.379,55.621,25.06,224,0.875,bilinear,-51.667,-49.477,0
-gluon_resnet50_v1b,26.426,73.574,44.057,55.943,25.56,224,0.875,bicubic,-51.150,-49.665,+25
-tf_efficientnet_el,26.349,73.650,44.188,55.812,10.59,300,0.904,bicubic,-53.899,-50.936,-119
-lambda_resnet26t,26.340,73.660,44.428,55.572,10.96,256,0.940,bicubic,-52.768,-50.160,-52
-levit_128,26.328,73.672,44.133,55.867,9.21,224,0.900,bicubic,-52.138,-49.877,-24
-resmlp_12_distilled_224,26.318,73.682,44.902,55.098,15.35,224,0.875,bicubic,-51.626,-48.660,+4
+coat_lite_tiny,26.530,73.470,44.642,55.358,5.72,224,0.900,bicubic,-50.984,-49.274,+33
+tf_efficientnet_b0,26.483,73.517,45.654,54.346,5.29,224,0.875,bicubic,-50.363,-47.576,+56
+mobilenetv3_large_100_miil,26.469,73.531,44.493,55.507,5.48,224,0.875,bilinear,-51.443,-48.411,+13
+res2net50_14w_8s,26.467,73.533,44.379,55.621,25.06,224,0.875,bilinear,-51.667,-49.477,+2
+gluon_resnet50_v1b,26.426,73.574,44.057,55.943,25.56,224,0.875,bicubic,-51.150,-49.665,+27
+tf_efficientnet_el,26.349,73.650,44.188,55.812,10.59,300,0.904,bicubic,-53.899,-50.936,-120
+lambda_resnet26t,26.340,73.660,44.428,55.572,10.96,256,0.940,bicubic,-52.768,-50.160,-50
+levit_128,26.328,73.672,44.133,55.867,9.21,224,0.900,bicubic,-52.138,-49.877,-22
+resmlp_12_distilled_224,26.318,73.682,44.902,55.098,15.35,224,0.875,bicubic,-51.626,-48.660,+6
 resmlp_big_24_224,26.314,73.686,43.565,56.435,129.14,224,0.875,bicubic,-54.718,-51.457,-169
-regnetx_040,26.245,73.755,44.458,55.542,22.12,224,0.875,bicubic,-52.239,-49.796,-29
-crossvit_9_dagger_240,26.180,73.820,44.548,55.452,8.78,240,0.875,bicubic,-50.809,-49.058,+38
-vit_small_patch32_224,26.178,73.822,45.118,54.882,22.88,224,0.900,bicubic,-49.816,-48.158,+62
-dpn68,26.118,73.882,44.239,55.761,12.61,224,0.875,bicubic,-50.176,-48.723,+58
-efficientnet_b1,26.065,73.935,44.084,55.916,7.79,256,1.000,bicubic,-52.739,-50.262,-45
-eca_halonext26ts,26.053,73.947,44.021,55.979,10.76,256,0.940,bicubic,-52.787,-50.235,-48
-lambda_resnet26rpt_256,26.019,73.981,44.222,55.778,10.99,256,0.940,bicubic,-52.949,-50.206,-53
-hrnet_w18,25.992,74.008,44.813,55.187,21.30,224,0.875,bilinear,-50.766,-48.625,+41
-hardcorenas_f,25.956,74.043,44.224,55.776,8.20,224,0.875,bilinear,-52.148,-49.570,-14
-regnety_040,25.929,74.071,43.850,56.150,20.65,224,0.875,bicubic,-53.299,-50.796,-71
-resnet34,25.894,74.106,43.990,56.010,21.80,224,0.875,bilinear,-49.218,-48.286,+72
-resnet26t,25.876,74.124,44.000,56.000,16.01,256,0.940,bicubic,-51.996,-49.834,-6
-res2net50_26w_4s,25.870,74.130,43.180,56.820,25.70,224,0.875,bilinear,-52.116,-50.668,-13
-tresnet_m_448,25.864,74.136,42.888,57.112,31.39,448,0.875,bilinear,-55.850,-52.682,-216
-coat_tiny,25.862,74.138,43.275,56.725,5.50,224,0.900,bicubic,-52.572,-50.759,-36
-hardcorenas_c,25.837,74.163,44.758,55.242,5.52,224,0.875,bilinear,-51.213,-48.414,+22
-gluon_resnet50_v1c,25.788,74.213,43.039,56.961,25.58,224,0.875,bicubic,-52.218,-50.949,-18
-halonet26t,25.750,74.250,43.239,56.761,12.48,256,0.950,bicubic,-53.384,-51.077,-74
-selecsls60,25.730,74.269,44.066,55.934,30.67,224,0.875,bicubic,-52.253,-49.766,-18
-dla60_res2net,25.674,74.326,43.603,56.397,20.85,224,0.875,bilinear,-52.788,-50.605,-45
-hardcorenas_e,25.664,74.336,43.426,56.574,8.07,224,0.875,bilinear,-52.136,-50.270,-8
-dla60_res2next,25.636,74.364,43.675,56.325,17.03,224,0.875,bilinear,-52.806,-50.482,-45
-ecaresnet26t,25.546,74.454,43.681,56.319,16.01,320,0.950,bicubic,-54.288,-51.403,-121
-resmlp_12_224,25.532,74.468,44.349,55.651,15.35,224,0.875,bicubic,-51.122,-48.823,+28
-tf_efficientnet_lite1,25.530,74.470,43.597,56.403,5.42,240,0.882,bicubic,-51.134,-49.637,+26
-mixnet_l,25.520,74.480,43.483,56.517,7.33,224,0.875,bicubic,-53.460,-50.697,-74
-bat_resnext26ts,25.471,74.529,43.235,56.765,10.73,256,0.900,bicubic,-52.791,-50.865,-41
-tv_resnext50_32x4d,25.469,74.531,42.817,57.183,25.03,224,0.875,bilinear,-52.141,-50.867,-12
-tf_mixnet_l,25.438,74.562,42.530,57.470,7.33,224,0.875,bicubic,-53.340,-51.470,-66
-repvgg_a2,25.436,74.564,43.980,56.020,28.21,224,0.875,bilinear,-51.044,-49.040,+29
-hardcorenas_b,25.410,74.590,44.200,55.800,5.18,224,0.875,bilinear,-51.120,-48.552,+26
-res2next50,25.402,74.598,42.516,57.484,24.67,224,0.875,bilinear,-52.840,-51.388,-43
-resnetv2_50x1_bitm,25.345,74.655,45.352,54.648,25.55,448,1.000,bilinear,-54.999,-50.334,-165
-dla102,25.328,74.672,43.819,56.181,33.27,224,0.875,bilinear,-52.700,-50.139,-36
-legacy_seresnet101,25.324,74.676,42.823,57.177,49.33,224,0.875,bilinear,-53.060,-51.441,-54
-hardcorenas_d,25.322,74.678,43.159,56.841,7.50,224,0.875,bilinear,-52.102,-50.327,-10
-selecsls60b,25.314,74.686,43.575,56.425,32.77,224,0.875,bicubic,-53.094,-50.601,-57
-resnest14d,25.294,74.706,44.092,55.908,10.61,224,0.875,bilinear,-50.212,-48.428,+36
-legacy_seresnext50_32x4d,25.226,74.775,41.968,58.032,27.56,224,0.875,bilinear,-53.853,-52.464,-92
-mixer_b16_224,25.143,74.857,41.223,58.777,59.88,224,0.875,bicubic,-51.479,-51.005,+13
-res2net50_48w_2s,25.029,74.971,42.215,57.785,25.29,224,0.875,bilinear,-52.505,-51.343,-20
-efficientnet_b0,25.019,74.981,42.801,57.199,5.29,224,0.875,bicubic,-52.685,-50.721,-28
-dla60,24.929,75.071,43.310,56.690,22.04,224,0.875,bilinear,-52.105,-50.014,-4
-gluon_resnet34_v1b,24.929,75.071,42.249,57.751,21.80,224,0.875,bicubic,-49.663,-49.747,+49
-mobilenetv2_120d,24.925,75.075,43.053,56.947,5.83,224,0.875,bicubic,-52.361,-50.459,-14
+regnetx_040,26.245,73.755,44.458,55.542,22.12,224,0.875,bicubic,-52.239,-49.796,-27
+crossvit_9_dagger_240,26.180,73.820,44.548,55.452,8.78,240,0.875,bicubic,-50.810,-49.058,+40
+vit_small_patch32_224,26.178,73.822,45.118,54.882,22.88,224,0.900,bicubic,-49.816,-48.158,+63
+dpn68,26.118,73.882,44.239,55.761,12.61,224,0.875,bicubic,-50.176,-48.723,+60
+efficientnet_b1,26.065,73.935,44.084,55.916,7.79,256,1.000,bicubic,-52.739,-50.262,-43
+eca_halonext26ts,26.053,73.947,44.021,55.979,10.76,256,0.940,bicubic,-52.787,-50.235,-46
+lambda_resnet26rpt_256,26.019,73.981,44.222,55.778,10.99,256,0.940,bicubic,-52.949,-50.206,-51
+hrnet_w18,25.992,74.008,44.813,55.187,21.30,224,0.875,bilinear,-50.766,-48.625,+43
+hardcorenas_f,25.956,74.043,44.224,55.776,8.20,224,0.875,bilinear,-52.148,-49.570,-12
+regnety_040,25.929,74.071,43.850,56.150,20.65,224,0.875,bicubic,-53.299,-50.796,-69
+resnet34,25.894,74.106,43.990,56.010,21.80,224,0.875,bilinear,-49.218,-48.286,+74
+resnet26t,25.876,74.124,44.000,56.000,16.01,256,0.940,bicubic,-51.996,-49.834,-4
+res2net50_26w_4s,25.870,74.130,43.180,56.820,25.70,224,0.875,bilinear,-52.116,-50.668,-11
+tresnet_m_448,25.864,74.136,42.888,57.112,31.39,448,0.875,bilinear,-55.850,-52.682,-219
+coat_tiny,25.862,74.138,43.275,56.725,5.50,224,0.900,bicubic,-52.572,-50.759,-34
+hardcorenas_c,25.837,74.163,44.758,55.242,5.52,224,0.875,bilinear,-51.213,-48.414,+24
+gluon_resnet50_v1c,25.788,74.213,43.039,56.961,25.58,224,0.875,bicubic,-52.218,-50.949,-16
+halonet26t,25.750,74.250,43.239,56.761,12.48,256,0.950,bicubic,-53.384,-51.077,-72
+selecsls60,25.730,74.269,44.066,55.934,30.67,224,0.875,bicubic,-52.254,-49.766,-16
+dla60_res2net,25.674,74.326,43.603,56.397,20.85,224,0.875,bilinear,-52.788,-50.605,-43
+hardcorenas_e,25.664,74.336,43.426,56.574,8.07,224,0.875,bilinear,-52.136,-50.270,-6
+dla60_res2next,25.636,74.364,43.675,56.325,17.03,224,0.875,bilinear,-52.806,-50.521,-42
+ecaresnet26t,25.546,74.454,43.681,56.319,16.01,320,0.950,bicubic,-54.288,-51.403,-122
+resmlp_12_224,25.532,74.468,44.349,55.651,15.35,224,0.875,bicubic,-51.122,-48.823,+30
+tf_efficientnet_lite1,25.530,74.470,43.597,56.403,5.42,240,0.882,bicubic,-51.134,-49.637,+28
+mixnet_l,25.520,74.480,43.483,56.517,7.33,224,0.875,bicubic,-53.460,-50.697,-71
+bat_resnext26ts,25.471,74.529,43.235,56.765,10.73,256,0.900,bicubic,-52.791,-50.865,-39
+tv_resnext50_32x4d,25.469,74.531,42.817,57.183,25.03,224,0.875,bilinear,-52.141,-50.867,-10
+botnet26t_256,25.453,74.547,42.656,57.344,12.49,256,0.950,bicubic,-53.807,-51.878,-91
+tf_mixnet_l,25.438,74.562,42.530,57.470,7.33,224,0.875,bicubic,-53.340,-51.470,-65
+repvgg_a2,25.436,74.564,43.980,56.020,28.21,224,0.875,bilinear,-51.044,-49.040,+30
+hardcorenas_b,25.410,74.590,44.200,55.800,5.18,224,0.875,bilinear,-51.120,-48.552,+27
+res2next50,25.402,74.598,42.516,57.484,24.67,224,0.875,bilinear,-52.840,-51.388,-42
+resnetv2_50x1_bitm,25.345,74.655,45.352,54.648,25.55,448,1.000,bilinear,-54.999,-50.334,-166
+dla102,25.328,74.672,43.819,56.181,33.27,224,0.875,bilinear,-52.700,-50.139,-35
+legacy_seresnet101,25.324,74.676,42.823,57.177,49.33,224,0.875,bilinear,-53.060,-51.441,-53
+hardcorenas_d,25.322,74.678,43.159,56.841,7.50,224,0.875,bilinear,-52.102,-50.327,-9
+selecsls60b,25.314,74.686,43.575,56.425,32.77,224,0.875,bicubic,-53.094,-50.601,-56
+resnest14d,25.294,74.706,44.092,55.908,10.61,224,0.875,bilinear,-50.212,-48.428,+37
+legacy_seresnext50_32x4d,25.226,74.775,41.968,58.032,27.56,224,0.875,bilinear,-53.852,-52.464,-91
+mixer_b16_224,25.143,74.857,41.223,58.777,59.88,224,0.875,bicubic,-51.479,-51.005,+14
+res2net50_48w_2s,25.029,74.971,42.215,57.785,25.29,224,0.875,bilinear,-52.505,-51.343,-19
+efficientnet_b0,25.019,74.981,42.801,57.199,5.29,224,0.875,bicubic,-52.685,-50.721,-27
+gluon_resnet34_v1b,24.929,75.071,42.249,57.751,21.80,224,0.875,bicubic,-49.663,-49.747,+50
+dla60,24.929,75.071,43.310,56.690,22.04,224,0.875,bilinear,-52.105,-50.014,-3
+mobilenetv2_120d,24.925,75.075,43.053,56.947,5.83,224,0.875,bicubic,-52.361,-50.459,-13
+eca_botnext26ts_256,24.864,75.136,42.944,57.056,10.59,256,0.950,bicubic,-54.410,-51.662,-110
 regnety_016,24.815,75.185,42.628,57.372,11.20,224,0.875,bicubic,-53.049,-51.096,-39
 xcit_nano_12_p8_224_dist,24.807,75.193,43.088,56.912,3.05,224,1.000,bicubic,-51.523,-49.998,+13
 seresnext26ts,24.693,75.307,43.102,56.898,10.39,256,0.900,bicubic,-53.155,-50.686,-38
 eca_resnext26ts,24.660,75.340,42.872,57.128,10.30,256,0.900,bicubic,-52.790,-50.706,-24
 tf_efficientnet_lite2,24.530,75.470,42.251,57.749,6.09,260,0.890,bicubic,-52.952,-51.497,-27
 regnetx_016,24.502,75.498,42.514,57.486,9.19,224,0.875,bicubic,-52.444,-50.912,-9
-skresnet18,24.485,75.515,42.545,57.455,11.96,224,0.875,bicubic,-48.537,-48.625,+59
-pit_ti_distilled_224,24.400,75.600,42.734,57.266,5.10,224,0.900,bicubic,-50.130,-49.366,+41
-tf_efficientnet_lite0,24.400,75.600,42.490,57.510,4.65,224,0.875,bicubic,-50.432,-49.686,+34
+skresnet18,24.485,75.515,42.545,57.455,11.96,224,0.875,bicubic,-48.537,-48.625,+58
+tf_efficientnet_lite0,24.400,75.600,42.490,57.510,4.65,224,0.875,bicubic,-50.432,-49.686,+35
+pit_ti_distilled_224,24.400,75.600,42.734,57.266,5.10,224,0.900,bicubic,-50.130,-49.366,+40
 hardcorenas_a,24.363,75.637,43.292,56.708,5.26,224,0.875,bilinear,-51.549,-49.222,+12
 tv_resnet50,24.080,75.920,41.325,58.675,25.56,224,0.875,bilinear,-52.072,-51.553,+7
 levit_128s,24.068,75.932,41.017,58.983,7.78,224,0.900,bicubic,-52.470,-51.847,-1
@@ -437,7 +442,7 @@ legacy_seresnet34,24.035,75.965,41.901,58.099,21.96,224,0.875,bilinear,-50.757,-
 xcit_nano_12_p16_384_dist,24.027,75.973,42.308,57.692,3.05,384,1.000,bicubic,-51.441,-50.368,+17
 xcit_nano_12_p8_384_dist,23.966,76.034,41.956,58.044,3.05,384,1.000,bicubic,-53.852,-52.078,-48
 gcresnext26ts,23.952,76.048,41.364,58.636,10.48,256,0.900,bicubic,-53.868,-52.462,-50
-resnet18d,23.936,76.064,42.300,57.700,11.71,224,0.875,bicubic,-48.332,-48.384,+57
+resnet18d,23.936,76.064,42.300,57.700,11.71,224,0.875,bicubic,-48.332,-48.384,+56
 efficientnet_lite0,23.925,76.075,42.097,57.903,4.65,224,0.875,bicubic,-51.579,-50.419,+12
 resnext26ts,23.889,76.111,41.123,58.877,10.30,256,0.900,bicubic,-52.883,-52.007,-16
 efficientnet_es_pruned,23.854,76.146,42.003,57.997,5.44,224,0.875,bicubic,-51.142,-50.437,+22
@@ -448,21 +453,21 @@ mixnet_m,23.697,76.303,41.158,58.842,5.01,224,0.875,bicubic,-53.577,-52.264,-37
 legacy_seresnet50,23.646,76.354,40.107,59.893,28.09,224,0.875,bilinear,-53.992,-53.639,-55
 ese_vovnet19b_dw,23.545,76.455,41.276,58.724,6.54,224,0.875,bicubic,-53.279,-52.004,-24
 tf_mixnet_m,23.500,76.500,40.991,59.009,5.01,224,0.875,bicubic,-53.458,-52.175,-31
-tv_resnet34,23.490,76.510,41.398,58.602,21.80,224,0.875,bilinear,-49.814,-50.024,+35
+tv_resnet34,23.490,76.510,41.398,58.602,21.80,224,0.875,bilinear,-49.814,-50.024,+34
 selecsls42b,23.404,76.596,40.659,59.341,32.46,224,0.875,bicubic,-53.786,-52.731,-41
-tf_efficientnet_em,23.394,76.606,40.411,59.589,6.90,240,0.882,bicubic,-54.748,-53.646,-82
+tf_efficientnet_em,23.394,76.606,40.411,59.589,6.90,240,0.882,bicubic,-54.748,-53.647,-82
 repvgg_b0,23.317,76.683,41.192,58.808,15.82,224,0.875,bilinear,-51.835,-51.222,+5
-xcit_nano_12_p16_224_dist,23.249,76.751,41.388,58.612,3.05,224,1.000,bicubic,-49.063,-49.464,+41
+xcit_nano_12_p16_224_dist,23.249,76.751,41.388,58.612,3.05,224,1.000,bicubic,-49.063,-49.464,+40
 mobilenetv2_110d,23.076,76.924,40.736,59.264,4.52,224,0.875,bicubic,-51.976,-51.452,+8
-vit_base_patch32_sam_224,23.042,76.958,39.557,60.443,88.22,224,0.900,bicubic,-50.658,-51.451,+25
+vit_base_patch32_sam_224,23.042,76.958,39.557,60.443,88.22,224,0.900,bicubic,-50.658,-51.451,+24
 deit_tiny_distilled_patch16_224,22.712,77.288,40.773,59.227,5.91,224,0.900,bicubic,-51.812,-51.123,+15
 mobilenetv3_large_100,22.647,77.353,40.781,59.219,5.48,224,0.875,bicubic,-53.127,-51.759,-12
-mobilenetv3_rw,22.636,77.365,40.410,59.590,5.48,224,0.875,bicubic,-52.982,-52.303,-11
+mobilenetv3_rw,22.636,77.365,40.410,59.590,5.48,224,0.875,bicubic,-52.982,-52.302,-11
 tf_mobilenetv3_large_100,22.563,77.437,39.747,60.253,5.48,224,0.875,bilinear,-52.947,-52.861,-10
-tf_efficientnet_es,22.427,77.573,39.095,60.905,5.44,224,0.875,bicubic,-54.163,-54.117,-29
+tf_efficientnet_es,22.427,77.573,39.095,60.905,5.44,224,0.875,bicubic,-54.163,-54.117,-30
 xcit_nano_12_p8_224,22.396,77.604,40.675,59.325,3.05,224,1.000,bicubic,-51.516,-51.491,+16
-hrnet_w18_small_v2,22.357,77.644,39.899,60.101,15.60,224,0.875,bilinear,-52.750,-52.513,-2
-convit_tiny,22.256,77.744,39.684,60.316,5.71,224,0.875,bicubic,-50.856,-52.036,+23
+hrnet_w18_small_v2,22.357,77.644,39.899,60.101,15.60,224,0.875,bilinear,-52.749,-52.513,-2
+convit_tiny,22.256,77.744,39.684,60.316,5.71,224,0.875,bicubic,-50.856,-52.036,+22
 regnety_008,22.121,77.879,38.918,61.082,6.26,224,0.875,bicubic,-54.199,-54.150,-27
 seresnext26t_32x4d,22.009,77.991,38.501,61.499,16.81,224,0.875,bicubic,-55.969,-55.241,-87
 regnety_006,21.983,78.017,38.963,61.037,6.06,224,0.875,bicubic,-53.283,-53.571,-10
@@ -470,50 +475,48 @@ regnetx_008,21.963,78.037,38.936,61.064,7.26,224,0.875,bicubic,-53.093,-53.412,-
 vit_tiny_r_s16_p8_384,21.942,78.058,39.439,60.561,6.36,384,1.000,bicubic,-54.030,-53.833,-26
 resnet26d,21.930,78.070,38.639,61.361,16.01,224,0.875,bicubic,-54.760,-54.509,-43
 semnasnet_100,21.903,78.097,38.604,61.396,3.89,224,0.875,bicubic,-53.549,-54.002,-16
-pit_ti_224,21.869,78.131,39.537,60.463,4.85,224,0.900,bicubic,-51.053,-51.873,+18
-regnetx_006,21.739,78.260,38.932,61.068,6.20,224,0.875,bicubic,-52.107,-52.750,+7
+pit_ti_224,21.869,78.131,39.537,60.463,4.85,224,0.900,bicubic,-51.053,-51.873,+17
+regnetx_006,21.739,78.260,38.932,61.068,6.20,224,0.875,bicubic,-52.107,-52.750,+6
 vit_tiny_patch16_384,21.728,78.272,39.335,60.665,5.79,384,1.000,bicubic,-56.718,-55.209,-121
 crossvit_9_240,21.706,78.294,39.268,60.732,8.55,240,0.875,bicubic,-52.276,-52.702,+2
 vgg19_bn,21.635,78.365,39.280,60.720,143.68,224,0.875,bilinear,-52.599,-52.574,-3
-ghostnet_100,21.625,78.374,38.714,61.286,5.18,224,0.875,bilinear,-52.358,-52.746,-1
-gluon_resnet18_v1b,21.547,78.453,38.895,61.105,11.69,224,0.875,bicubic,-49.287,-50.866,+26
+ghostnet_100,21.625,78.374,38.714,61.286,5.18,224,0.875,bilinear,-52.359,-52.746,-1
+gluon_resnet18_v1b,21.547,78.453,38.895,61.105,11.69,224,0.875,bicubic,-49.287,-50.865,+25
 fbnetc_100,21.508,78.492,38.146,61.854,5.57,224,0.875,bilinear,-53.612,-54.228,-20
-xcit_nano_12_p16_224,21.437,78.563,39.804,60.196,3.05,224,1.000,bicubic,-48.535,-49.954,+27
+xcit_nano_12_p16_224,21.437,78.563,39.804,60.196,3.05,224,1.000,bicubic,-48.535,-49.954,+26
 mnasnet_100,21.368,78.632,37.719,62.281,4.38,224,0.875,bicubic,-53.306,-54.379,-13
-ssl_resnet18,21.297,78.703,39.132,60.868,11.69,224,0.875,bilinear,-51.315,-52.288,+9
+ssl_resnet18,21.297,78.703,39.132,60.868,11.69,224,0.875,bilinear,-51.315,-52.288,+8
 resnet26,21.290,78.710,38.040,61.960,16.00,224,0.875,bicubic,-54.002,-54.534,-27
-seresnext26d_32x4d,21.285,78.715,37.332,62.668,16.81,224,0.875,bicubic,-56.300,-56.272,-89
-mixnet_s,21.268,78.732,38.209,61.791,4.13,224,0.875,bicubic,-54.726,-54.583,-44
+seresnext26d_32x4d,21.285,78.715,37.332,62.668,16.81,224,0.875,bicubic,-56.301,-56.272,-89
+mixnet_s,21.268,78.732,38.209,61.791,4.13,224,0.875,bicubic,-54.726,-54.583,-43
 legacy_seresnext26_32x4d,21.075,78.925,37.629,62.371,16.79,224,0.875,bicubic,-56.019,-55.681,-72
-crossvit_tiny_240,21.054,78.946,38.071,61.929,7.01,240,0.875,bicubic,-52.290,-53.851,-3
-regnetx_004,20.908,79.092,37.568,62.432,5.16,224,0.875,bicubic,-51.482,-53.250,+4
+crossvit_tiny_240,21.054,78.946,38.071,61.929,7.01,240,0.875,bicubic,-52.290,-53.851,-4
+regnetx_004,20.908,79.092,37.568,62.432,5.16,224,0.875,bicubic,-51.482,-53.250,+3
 spnasnet_100,20.853,79.147,37.912,62.088,4.42,224,0.875,bilinear,-53.225,-53.908,-15
-legacy_seresnet18,20.800,79.200,37.619,62.381,11.78,224,0.875,bicubic,-50.934,-52.719,+11
-mobilenetv2_100,20.775,79.225,37.774,62.226,3.50,224,0.875,bicubic,-52.177,-53.228,-2
+legacy_seresnet18,20.800,79.200,37.619,62.381,11.78,224,0.875,bicubic,-50.934,-52.719,+10
+mobilenetv2_100,20.775,79.225,37.774,62.226,3.50,224,0.875,bicubic,-52.177,-53.228,-3
 tf_mixnet_s,20.470,79.530,36.639,63.361,4.13,224,0.875,bicubic,-55.214,-55.997,-45
 vit_tiny_patch16_224,20.452,79.548,37.625,62.375,5.72,224,0.900,bicubic,-55.002,-55.227,-39
 regnety_004,20.423,79.577,37.022,62.978,4.34,224,0.875,bicubic,-53.589,-54.744,-19
-hrnet_w18_small,20.366,79.634,37.100,62.900,13.19,224,0.875,bilinear,-51.966,-53.586,-1
-tf_mobilenetv3_large_075,20.362,79.638,36.770,63.230,3.99,224,0.875,bilinear,-53.088,-54.570,-14
-resnet18,20.238,79.762,37.260,62.740,11.69,224,0.875,bilinear,-49.502,-51.826,+12
-mixer_l16_224,20.160,79.840,32.950,67.050,208.20,224,0.875,bicubic,-51.906,-54.704,+1
-deit_tiny_patch16_224,20.142,79.858,37.578,62.422,5.72,224,0.900,bicubic,-52.018,-53.534,-1
-tf_mobilenetv3_large_minimal_100,20.120,79.880,36.902,63.098,3.92,224,0.875,bilinear,-52.132,-53.734,-3
-vgg16_bn,19.969,80.031,36.310,63.690,138.37,224,0.875,bilinear,-53.391,-55.182,-18
-vit_tiny_r_s16_p8_224,19.342,80.658,36.061,63.939,6.34,224,0.900,bicubic,-52.456,-54.763,-2
-vgg19,17.929,82.071,33.060,66.940,143.67,224,0.875,bilinear,-54.459,-57.826,-10
-vgg13_bn,17.821,82.179,34.047,65.953,133.05,224,0.875,bilinear,-53.743,-56.327,-1
-vgg16,17.540,82.460,32.767,67.233,138.36,224,0.875,bilinear,-54.044,-57.623,-3
-regnety_002,17.454,82.546,32.453,67.547,3.16,224,0.875,bicubic,-52.828,-57.091,0
-vgg11_bn,17.409,82.591,33.039,66.961,132.87,224,0.875,bilinear,-52.953,-56.767,-2
-regnetx_002,16.962,83.038,32.237,67.763,2.68,224,0.875,bicubic,-51.788,-56.323,+3
-dla60x_c,16.320,83.680,31.773,68.227,1.32,224,0.875,bilinear,-51.592,-56.645,+5
-eca_botnext26ts_256,16.257,83.743,30.623,69.376,10.59,256,0.950,bicubic,-57.621,-61.164,-31
-tf_mobilenetv3_small_100,16.224,83.776,31.241,68.760,2.54,224,0.875,bilinear,-51.703,-56.436,+2
-vgg13,16.116,83.885,30.987,69.013,133.05,224,0.875,bilinear,-53.823,-58.271,-4
+hrnet_w18_small,20.366,79.634,37.100,62.900,13.19,224,0.875,bilinear,-51.966,-53.586,-2
+tf_mobilenetv3_large_075,20.362,79.638,36.770,63.230,3.99,224,0.875,bilinear,-53.088,-54.570,-15
+resnet18,20.238,79.762,37.260,62.740,11.69,224,0.875,bilinear,-49.502,-51.826,+11
+mixer_l16_224,20.160,79.840,32.950,67.050,208.20,224,0.875,bicubic,-51.906,-54.704,0
+deit_tiny_patch16_224,20.142,79.858,37.578,62.422,5.72,224,0.900,bicubic,-52.018,-53.534,-2
+tf_mobilenetv3_large_minimal_100,20.120,79.880,36.902,63.098,3.92,224,0.875,bilinear,-52.132,-53.734,-4
+vgg16_bn,19.969,80.031,36.310,63.690,138.37,224,0.875,bilinear,-53.391,-55.182,-19
+vit_tiny_r_s16_p8_224,19.342,80.658,36.061,63.939,6.34,224,0.900,bicubic,-52.456,-54.763,-3
+vgg19,17.929,82.071,33.060,66.940,143.67,224,0.875,bilinear,-54.459,-57.826,-11
+vgg13_bn,17.821,82.179,34.047,65.953,133.05,224,0.875,bilinear,-53.743,-56.327,-2
+vgg16,17.540,82.460,32.767,67.233,138.36,224,0.875,bilinear,-54.044,-57.623,-4
+regnety_002,17.454,82.546,32.453,67.547,3.16,224,0.875,bicubic,-52.828,-57.091,-1
+vgg11_bn,17.409,82.591,33.039,66.961,132.87,224,0.875,bilinear,-52.953,-56.767,-3
+regnetx_002,16.962,83.038,32.237,67.763,2.68,224,0.875,bicubic,-51.788,-56.323,+2
+dla60x_c,16.320,83.680,31.773,68.227,1.32,224,0.875,bilinear,-51.592,-56.645,+3
+tf_mobilenetv3_small_100,16.224,83.776,31.241,68.760,2.54,224,0.875,bilinear,-51.702,-56.435,+1
+vgg13,16.116,83.885,30.987,69.013,133.05,224,0.875,bilinear,-53.822,-58.271,-4
 vgg11,15.728,84.272,30.464,69.536,132.86,224,0.875,bilinear,-53.320,-58.172,-3
-tf_mobilenetv3_small_075,14.942,85.058,29.594,70.406,2.04,224,0.875,bilinear,-50.778,-56.542,+2
-dla46_c,14.677,85.323,29.372,70.628,1.30,224,0.875,bilinear,-50.193,-56.922,+2
-dla46x_c,14.382,85.618,29.197,70.803,1.07,224,0.875,bilinear,-51.594,-57.791,-1
-tf_mobilenetv3_small_minimal_100,13.983,86.017,27.992,72.008,2.04,224,0.875,bilinear,-48.925,-56.254,+1
-botnet26t_256,13.543,86.457,26.420,73.580,12.49,256,0.950,bicubic,-55.003,-62.276,-6
+tf_mobilenetv3_small_075,14.942,85.058,29.594,70.406,2.04,224,0.875,bilinear,-50.778,-56.542,+1
+dla46_c,14.677,85.323,29.372,70.628,1.30,224,0.875,bilinear,-50.193,-56.922,+1
+dla46x_c,14.382,85.618,29.197,70.803,1.07,224,0.875,bilinear,-51.594,-57.791,-2
+tf_mobilenetv3_small_minimal_100,13.983,86.017,27.992,72.008,2.04,224,0.875,bilinear,-48.925,-56.254,0

timm/data/auto_augment.py

@@ -332,6 +332,7 @@ class AugmentOp:
 
     def __init__(self, name, prob=0.5, magnitude=10, hparams=None):
         hparams = hparams or _HPARAMS_DEFAULT
+        self.name = name
         self.aug_fn = NAME_TO_OP[name]
         self.level_fn = LEVEL_TO_ARG[name]
         self.prob = prob
@@ -367,6 +368,14 @@ class AugmentOp:
         level_args = self.level_fn(magnitude, self.hparams) if self.level_fn is not None else tuple()
         return self.aug_fn(img, *level_args, **self.kwargs)
 
+    def __repr__(self):
+        fs = self.__class__.__name__ + f'(name={self.name}, p={self.prob}'
+        fs += f', m={self.magnitude}, mstd={self.magnitude_std}'
+        if self.magnitude_max is not None:
+            fs += f', mmax={self.magnitude_max}'
+        fs += ')'
+        return fs
+
 
 def auto_augment_policy_v0(hparams):
     # ImageNet v0 policy from TPU EfficientNet impl, cannot find a paper reference.
@@ -526,6 +535,15 @@ class AutoAugment:
             img = op(img)
         return img
 
+    def __repr__(self):
+        fs = self.__class__.__name__ + f'(policy='
+        for p in self.policy:
+            fs += '\n\t['
+            fs += ', '.join([str(op) for op in p])
+            fs += ']'
+        fs += ')'
+        return fs
+
 
 def auto_augment_transform(config_str, hparams):
     """
@@ -650,6 +668,13 @@ class RandAugment:
             img = op(img)
         return img
 
+    def __repr__(self):
+        fs = self.__class__.__name__ + f'(n={self.num_layers}, ops='
+        for op in self.ops:
+            fs += f'\n\t{op}'
+        fs += ')'
+        return fs
+
 
 def rand_augment_transform(config_str, hparams):
     """
@@ -798,6 +823,13 @@ class AugMixAugment:
             mixed = self._apply_basic(img, mixing_weights, m)
         return mixed
 
+    def __repr__(self):
+        fs = self.__class__.__name__ + f'(alpha={self.alpha}, width={self.width}, depth={self.depth}, ops='
+        for op in self.ops:
+            fs += f'\n\t{op}'
+        fs += ')'
+        return fs
+
 
 def augment_and_mix_transform(config_str, hparams):
     """ Create AugMix PyTorch transform

timm/data/dataset.py

@@ -23,15 +23,17 @@ class ImageDataset(data.Dataset):
             self,
             root,
             parser=None,
-            class_map='',
+            class_map=None,
             load_bytes=False,
             transform=None,
+            target_transform=None,
     ):
         if parser is None or isinstance(parser, str):
             parser = create_parser(parser or '', root=root, class_map=class_map)
         self.parser = parser
         self.load_bytes = load_bytes
         self.transform = transform
+        self.target_transform = target_transform
         self._consecutive_errors = 0
 
     def __getitem__(self, index):
@@ -49,7 +51,9 @@ class ImageDataset(data.Dataset):
         if self.transform is not None:
             img = self.transform(img)
         if target is None:
-            target = torch.tensor(-1, dtype=torch.long)
+            target = -1
+        elif self.target_transform is not None:
+            target = self.target_transform(target)
         return img, target
 
     def __len__(self):
@@ -71,26 +75,28 @@ class IterableImageDataset(data.IterableDataset):
             split='train',
             is_training=False,
             batch_size=None,
-            class_map='',
-            load_bytes=False,
             repeats=0,
+            download=False,
             transform=None,
+            target_transform=None,
     ):
         assert parser is not None
         if isinstance(parser, str):
             self.parser = create_parser(
-                parser, root=root, split=split, is_training=is_training, batch_size=batch_size, repeats=repeats)
+                parser, root=root, split=split, is_training=is_training,
+                batch_size=batch_size, repeats=repeats, download=download)
         else:
             self.parser = parser
         self.transform = transform
+        self.target_transform = target_transform
         self._consecutive_errors = 0
 
     def __iter__(self):
         for img, target in self.parser:
             if self.transform is not None:
                 img = self.transform(img)
-            if target is None:
-                target = torch.tensor(-1, dtype=torch.long)
+            if self.target_transform is not None:
+                target = self.target_transform(target)
             yield img, target
 
     def __len__(self):

timm/data/dataset_factory.py

@@ -1,7 +1,26 @@
 import os
 
+from torchvision.datasets import CIFAR100, CIFAR10, MNIST, QMNIST, KMNIST, FashionMNIST,\
+    Places365, ImageNet, ImageFolder
+try:
+    from torchvision.datasets import INaturalist
+    has_inaturalist = True
+except ImportError:
+    has_inaturalist = False
+
 from .dataset import IterableImageDataset, ImageDataset
 
+_TORCH_BASIC_DS = dict(
+    cifar10=CIFAR10,
+    cifar100=CIFAR100,
+    mnist=MNIST,
+    qmist=QMNIST,
+    kmnist=KMNIST,
+    fashion_mnist=FashionMNIST,
+)
+_TRAIN_SYNONYM = {'train', 'training'}
+_EVAL_SYNONYM = {'val', 'valid', 'validation', 'eval', 'evaluation'}
+
 
 def _search_split(root, split):
     # look for sub-folder with name of split in root and use that if it exists
@@ -9,22 +28,107 @@ def _search_split(root, split):
     try_root = os.path.join(root, split_name)
     if os.path.exists(try_root):
         return try_root
-    if split_name == 'validation':
-        try_root = os.path.join(root, 'val')
-        if os.path.exists(try_root):
-            return try_root
+
+    def _try(syn):
+        for s in syn:
+            try_root = os.path.join(root, s)
+            if os.path.exists(try_root):
+                return try_root
+        return root
+    if split_name in _TRAIN_SYNONYM:
+        root = _try(_TRAIN_SYNONYM)
+    elif split_name in _EVAL_SYNONYM:
+        root = _try(_EVAL_SYNONYM)
     return root
 
 
-def create_dataset(name, root, split='validation', search_split=True, is_training=False, batch_size=None, **kwargs):
+def create_dataset(
+        name,
+        root,
+        split='validation',
+        search_split=True,
+        class_map=None,
+        load_bytes=False,
+        is_training=False,
+        download=False,
+        batch_size=None,
+        repeats=0,
+        **kwargs
+):
+    """ Dataset factory method
+
+    In parenthesis after each arg are the type of dataset supported for each arg, one of:
+      * folder - default, timm folder (or tar) based ImageDataset
+      * torch - torchvision based datasets
+      * TFDS - Tensorflow-datasets wrapper in IterabeDataset interface via IterableImageDataset
+      * all - any of the above
+
+    Args:
+        name: dataset name, empty is okay for folder based datasets
+        root: root folder of dataset (all)
+        split: dataset split (all)
+        search_split: search for split specific child fold from root so one can specify
+            `imagenet/` instead of `/imagenet/val`, etc on cmd line / config. (folder, torch/folder)
+        class_map: specify class -> index mapping via text file or dict (folder)
+        load_bytes: load data, return images as undecoded bytes (folder)
+        download: download dataset if not present and supported (TFDS, torch)
+        is_training: create dataset in train mode, this is different from the split.
+            For Iterable / TDFS it enables shuffle, ignored for other datasets. (TFDS)
+        batch_size: batch size hint for (TFDS)
+        repeats: dataset repeats per iteration i.e. epoch (TFDS)
+        **kwargs: other args to pass to dataset
+
+    Returns:
+        Dataset object
+    """
     name = name.lower()
-    if name.startswith('tfds'):
+    if name.startswith('torch/'):
+        name = name.split('/', 2)[-1]
+        torch_kwargs = dict(root=root, download=download, **kwargs)
+        if name in _TORCH_BASIC_DS:
+            ds_class = _TORCH_BASIC_DS[name]
+            use_train = split in _TRAIN_SYNONYM
+            ds = ds_class(train=use_train, **torch_kwargs)
+        elif name == 'inaturalist' or name == 'inat':
+            assert has_inaturalist, 'Please update to PyTorch 1.10, torchvision 0.11+ for Inaturalist'
+            target_type = 'full'
+            split_split = split.split('/')
+            if len(split_split) > 1:
+                target_type = split_split[0].split('_')
+                if len(target_type) == 1:
+                    target_type = target_type[0]
+                split = split_split[-1]
+            if split in _TRAIN_SYNONYM:
+                split = '2021_train'
+            elif split in _EVAL_SYNONYM:
+                split = '2021_valid'
+            ds = INaturalist(version=split, target_type=target_type, **torch_kwargs)
+        elif name == 'places365':
+            if split in _TRAIN_SYNONYM:
+                split = 'train-standard'
+            elif split in _EVAL_SYNONYM:
+                split = 'val'
+            ds = Places365(split=split, **torch_kwargs)
+        elif name == 'imagenet':
+            if split in _EVAL_SYNONYM:
+                split = 'val'
+            ds = ImageNet(split=split, **torch_kwargs)
+        elif name == 'image_folder' or name == 'folder':
+            # in case torchvision ImageFolder is preferred over timm ImageDataset for some reason
+            if search_split and os.path.isdir(root):
+                # look for split specific sub-folder in root
+                root = _search_split(root, split)
+            ds = ImageFolder(root, **kwargs)
+        else:
+            assert False, f"Unknown torchvision dataset {name}"
+    elif name.startswith('tfds/'):
         ds = IterableImageDataset(
-            root, parser=name, split=split, is_training=is_training, batch_size=batch_size, **kwargs)
+            root, parser=name, split=split, is_training=is_training,
+            download=download, batch_size=batch_size, repeats=repeats, **kwargs)
     else:
         # FIXME support more advance split cfg for ImageFolder/Tar datasets in the future
-        kwargs.pop('repeats', 0)  # FIXME currently only Iterable dataset support the repeat multiplier
         if search_split and os.path.isdir(root):
+            # look for split specific sub-folder in root
             root = _search_split(root, split)
-        ds = ImageDataset(root, parser=name, **kwargs)
+        ds = ImageDataset(root, parser=name, class_map=class_map, load_bytes=load_bytes, **kwargs)
     return ds

timm/data/parsers/class_map.py

@@ -1,16 +1,19 @@
 import os
 
 
-def load_class_map(filename, root=''):
-    class_map_path = filename
+def load_class_map(map_or_filename, root=''):
+    if isinstance(map_or_filename, dict):
+        assert dict, 'class_map dict must be non-empty'
+        return map_or_filename
+    class_map_path = map_or_filename
     if not os.path.exists(class_map_path):
-        class_map_path = os.path.join(root, filename)
-        assert os.path.exists(class_map_path), 'Cannot locate specified class map file (%s)' % filename
-    class_map_ext = os.path.splitext(filename)[-1].lower()
+        class_map_path = os.path.join(root, class_map_path)
+        assert os.path.exists(class_map_path), 'Cannot locate specified class map file (%s)' % map_or_filename
+    class_map_ext = os.path.splitext(map_or_filename)[-1].lower()
     if class_map_ext == '.txt':
         with open(class_map_path) as f:
             class_to_idx = {v.strip(): k for k, v in enumerate(f)}
     else:
-        assert False, 'Unsupported class map extension'
+        assert False, f'Unsupported class map file extension ({class_map_ext}).'
     return class_to_idx
 

timm/data/parsers/parser_factory.py

@@ -17,7 +17,7 @@ def create_parser(name, root, split='train', **kwargs):
     # explicitly select other options shortly
     if prefix == 'tfds':
         from .parser_tfds import ParserTfds  # defer tensorflow import
-        parser = ParserTfds(root, name, split=split, shuffle=kwargs.pop('shuffle', False), **kwargs)
+        parser = ParserTfds(root, name, split=split, **kwargs)
     else:
         assert os.path.exists(root)
         # default fallback path (backwards compat), use image tar if root is a .tar file, otherwise image folder

timm/data/parsers/parser_tfds.py

@@ -6,17 +6,21 @@ https://www.tensorflow.org/datasets/catalog/overview#image_classification
 
 Hacked together by / Copyright 2020 Ross Wightman
 """
-import os
-import io
 import math
 import torch
-import torch.distributed as dist
 from PIL import Image
 
 try:
     import tensorflow as tf
     tf.config.set_visible_devices([], 'GPU')  # Hands off my GPU! (or pip install tensorflow-cpu)
     import tensorflow_datasets as tfds
+    try:
+        tfds.even_splits('', 1, drop_remainder=False)  # non-buggy even_splits has drop_remainder arg
+        has_buggy_even_splits = False
+    except TypeError:
+        print("Warning: This version of tfds doesn't have the latest even_splits impl. "
+              "Please update or use tfds-nightly for better fine-grained split behaviour.")
+        has_buggy_even_splits = True
 except ImportError as e:
     print(e)
     print("Please install tensorflow_datasets package `pip install tensorflow-datasets`.")
@@ -26,7 +30,7 @@ from .parser import Parser
 from timm.bits import get_global_device
 
 MAX_TP_SIZE = 8  # maximum TF threadpool size, only doing jpeg decodes and queuing activities
-SHUFFLE_SIZE = 20480  # samples to shuffle in DS queue
+SHUFFLE_SIZE = 16384  # samples to shuffle in DS queue
 PREFETCH_SIZE = 2048  # samples to prefetch
 
 
@@ -58,36 +62,71 @@ class ParserTfds(Parser):
         components.
 
     """
-    def __init__(self, root, name, split='train', shuffle=False, is_training=False, batch_size=None, repeats=0):
+    def __init__(
+            self,
+            root,
+            name,
+            split='train',
+            is_training=False,
+            batch_size=None,
+            download=False,
+            repeats=0,
+            seed=42,
+            prefetch_size=None,
+            shuffle_size=None,
+            max_threadpool_size=None
+    ):
+        """ Tensorflow-datasets Wrapper
+
+        Args:
+            root: root data dir (ie your TFDS_DATA_DIR. not dataset specific sub-dir)
+            name: tfds dataset name (eg `imagenet2012`)
+            split: tfds dataset split (can use all TFDS split strings eg `train[:10%]`)
+            is_training: training mode, shuffle enabled, dataset len rounded by batch_size
+            batch_size: batch_size to use to unsure total samples % batch_size == 0 in training across all dis nodes
+            download: download and build TFDS dataset if set, otherwise must use tfds CLI
+            repeats: iterate through (repeat) the dataset this many times per iteration (once if 0 or 1)
+            seed: common seed for shard shuffle across all distributed/worker instances
+            prefetch_size: override default tf.data prefetch buffer size
+            shuffle_size: override default tf.data shuffle buffer size
+            max_threadpool_size: override default threadpool size for tf.data
+        """
         super().__init__()
         self.root = root
         self.split = split
-        self.shuffle = shuffle
         self.is_training = is_training
         if self.is_training:
             assert batch_size is not None,\
                 "Must specify batch_size in training mode for reasonable behaviour w/ TFDS wrapper"
         self.batch_size = batch_size
         self.repeats = repeats
-        self.subsplit = None
+        self.common_seed = seed  # a seed that's fixed across all worker / distributed instances
+        self.prefetch_size = prefetch_size or PREFETCH_SIZE
+        self.shuffle_size = shuffle_size or SHUFFLE_SIZE
+        self.max_threadpool_size = max_threadpool_size or MAX_TP_SIZE
 
+        # TFDS builder and split information
         self.builder = tfds.builder(name, data_dir=root)
-        # NOTE: please use tfds command line app to download & prepare datasets, I don't want to call
-        # download_and_prepare() by default here as it's caused issues generating unwanted paths.
-        self.num_samples = self.builder.info.splits[split].num_examples
-        self.ds = None  # initialized lazily on each dataloader worker process
+        # NOTE: the tfds command line app can be used download & prepare datasets if you don't enable download flag
+        if download:
+            self.builder.download_and_prepare()
+        self.split_info = self.builder.info.splits[split]
+        self.num_samples = self.split_info.num_examples
 
-        self.worker_info = None
+        # Distributed world state
         self.dist_rank = 0
         self.dist_num_replicas = 1
-        dev_env = get_global_device()
-        # FIXME allow to work without devenv usage?
+        dev_env = get_global_device()  # FIXME allow to work without devenv usage?
         if dev_env.distributed and dev_env.world_size > 1:
             self.dist_rank = dev_env.global_rank
             self.dist_num_replicas = dev_env.world_size
-        # if dist.is_available() and dist.is_initialized() and dist.get_world_size() > 1:
-        #     self.dist_rank = dist.get_rank()
-        #     self.dist_num_replicas = dist.get_world_size()
+
+        # Attributes that are updated in _lazy_init, including the tf.data pipeline itself
+        self.global_num_workers = 1
+        self.worker_info = None
+        self.worker_seed = 0  # seed unique to each work instance
+        self.subsplit = None  # set when data is distributed across workers using sub-splits
+        self.ds = None  # initialized lazily on each dataloader worker process
 
     def _lazy_init(self):
         """ Lazily initialize the dataset.
@@ -103,78 +142,83 @@ class ParserTfds(Parser):
         worker_info = torch.utils.data.get_worker_info()
 
         # setup input context to split dataset across distributed processes
-        split = self.split
         num_workers = 1
+        global_worker_id = 0
         if worker_info is not None:
             self.worker_info = worker_info
+            self.worker_seed = worker_info.seed
             num_workers = worker_info.num_workers
-            global_num_workers = self.dist_num_replicas * num_workers
-            worker_id = worker_info.id
+            self.global_num_workers = self.dist_num_replicas * num_workers
+            global_worker_id = self.dist_rank * num_workers + worker_info.id
 
-            # FIXME I need to spend more time figuring out the best way to distribute/split data across
-            # combo of distributed replicas + dataloader worker processes
-            """
+            """ Data sharding
             InputContext will assign subset of underlying TFRecord files to each 'pipeline' if used.
             My understanding is that using split, the underling TFRecord files will shuffle (shuffle_files=True)
             between the splits each iteration, but that understanding could be wrong.
-            Possible split options include:
-              * InputContext for both distributed & worker processes (current)
-              * InputContext for distributed and sub-splits for worker processes
-              * sub-splits for both
+            
+            I am currently using a mix of InputContext shard assignment and fine-grained sub-splits for distributing
+            the data across workers. For training InputContext is used to assign shards to nodes unless num_shards
+            in dataset < total number of workers. Otherwise sub-split API is used for datasets without enough shards or
+            for validation where we can't drop samples and need to avoid minimize uneven splits to avoid padding.
             """
-            # split_size = self.num_samples // num_workers
-            # start = worker_id * split_size
-            # if worker_id == num_workers - 1:
-            #     split = split + '[{}:]'.format(start)
-            # else:
-            #     split = split + '[{}:{}]'.format(start, start + split_size)
-            if not self.is_training and '[' not in self.split:
-                # If not training, and split doesn't define a subsplit, manually split the dataset
-                # for more even samples / worker
-                self.subsplit = even_split_indices(self.split, global_num_workers, self.num_samples)[
-                    self.dist_rank * num_workers + worker_id]
-
-        if self.subsplit is None:
+            should_subsplit = self.global_num_workers > 1 and (
+                    self.split_info.num_shards < self.global_num_workers or not self.is_training)
+            if should_subsplit:
+                # split the dataset w/o using sharding for more even samples / worker, can result in less optimal
+                # read patterns for distributed training (overlap across shards) so better to use InputContext there
+                if has_buggy_even_splits:
+                    # my even_split workaround doesn't work on subsplits, upgrade tfds!
+                    if not isinstance(self.split_info, tfds.core.splits.SubSplitInfo):
+                        subsplits = even_split_indices(self.split, self.global_num_workers, self.num_samples)
+                        self.subsplit = subsplits[global_worker_id]
+                else:
+                    subsplits = tfds.even_splits(self.split, self.global_num_workers)
+                    self.subsplit = subsplits[global_worker_id]
+
+        input_context = None
+        if self.global_num_workers > 1 and self.subsplit is None:
+            # set input context to divide shards among distributed replicas
             input_context = tf.distribute.InputContext(
-                num_input_pipelines=self.dist_num_replicas * num_workers,
-                input_pipeline_id=self.dist_rank * num_workers + worker_id,
+                num_input_pipelines=self.global_num_workers,
+                input_pipeline_id=global_worker_id,
                 num_replicas_in_sync=self.dist_num_replicas  # FIXME does this arg have any impact?
             )
-        else:
-            input_context = None
-
         read_config = tfds.ReadConfig(
-            shuffle_seed=42,
+            shuffle_seed=self.common_seed,
             shuffle_reshuffle_each_iteration=True,
             input_context=input_context)
         ds = self.builder.as_dataset(
-            split=self.subsplit or self.split, shuffle_files=self.shuffle, read_config=read_config)
-        # avoid overloading threading w/ combo fo TF ds threads + PyTorch workers
+            split=self.subsplit or self.split, shuffle_files=self.is_training, read_config=read_config)
+        # avoid overloading threading w/ combo of TF ds threads + PyTorch workers
         options = tf.data.Options()
-        options.experimental_threading.private_threadpool_size = max(1, MAX_TP_SIZE // num_workers)
-        options.experimental_threading.max_intra_op_parallelism = 1
+        thread_member = 'threading' if hasattr(options, 'threading') else 'experimental_threading'
+        getattr(options, thread_member).private_threadpool_size = max(1, self.max_threadpool_size // num_workers)
+        getattr(options, thread_member).max_intra_op_parallelism = 1
         ds = ds.with_options(options)
         if self.is_training or self.repeats > 1:
             # to prevent excessive drop_last batch behaviour w/ IterableDatasets
             # see warnings at https://pytorch.org/docs/stable/data.html#multi-process-data-loading
             ds = ds.repeat()  # allow wrap around and break iteration manually
-        if self.shuffle:
-            ds = ds.shuffle(min(self.num_samples, SHUFFLE_SIZE) // self._num_pipelines, seed=worker_info.seed)
-        ds = ds.prefetch(min(self.num_samples // self._num_pipelines, PREFETCH_SIZE))
+        if self.is_training:
+            ds = ds.shuffle(min(self.num_samples, self.shuffle_size) // self.global_num_workers, seed=self.worker_seed)
+        ds = ds.prefetch(min(self.num_samples // self.global_num_workers, self.prefetch_size))
         self.ds = tfds.as_numpy(ds)
 
     def __iter__(self):
         if self.ds is None:
             self._lazy_init()
-        # compute a rounded up sample count that is used to:
+
+        # Compute a rounded up sample count that is used to:
         #   1. make batches even cross workers & replicas in distributed validation.
         #     This adds extra samples and will slightly alter validation results.
         #   2. determine loop ending condition in training w/ repeat enabled so that only full batch_size
         #     batches are produced (underlying tfds iter wraps around)
-        target_sample_count = math.ceil(max(1, self.repeats) * self.num_samples / self._num_pipelines)
+        target_sample_count = math.ceil(max(1, self.repeats) * self.num_samples / self.global_num_workers)
         if self.is_training:
             # round up to nearest batch_size per worker-replica
             target_sample_count = math.ceil(target_sample_count / self.batch_size) * self.batch_size
+
+        # Iterate until exhausted or sample count hits target when training (ds.repeat enabled)
         sample_count = 0
         for sample in self.ds:
             img = Image.fromarray(sample['image'], mode='RGB')
@@ -185,21 +229,17 @@ class ParserTfds(Parser):
                 # this results in extra samples per epoch but seems more desirable than dropping
                 # up to N*J batches per epoch (where N = num distributed processes, and J = num worker processes)
                 break
-        if not self.is_training and self.dist_num_replicas and 0 < sample_count < target_sample_count:
+
+        # Pad across distributed nodes (make counts equal by adding samples)
+        if not self.is_training and self.dist_num_replicas > 1 and self.subsplit is not None and \
+                0 < sample_count < target_sample_count:
             # Validation batch padding only done for distributed training where results are reduced across nodes.
             # For single process case, it won't matter if workers return different batch sizes.
-            # FIXME if using input_context or % based subsplits, sample count can vary by more than +/- 1 and this
-            # approach is not optimal
-            yield img, sample['label']  # yield prev sample again
-            sample_count += 1
-
-    @property
-    def _num_workers(self):
-        return 1 if self.worker_info is None else self.worker_info.num_workers
-
-    @property
-    def _num_pipelines(self):
-        return self._num_workers * self.dist_num_replicas
+            # If using input_context or % based splits, sample count can vary significantly across workers and this
+            # approach should not be used (hence disabled if self.subsplit isn't set).
+            while sample_count < target_sample_count:
+                yield img, sample['label']  # yield prev sample again
+                sample_count += 1
 
     def __len__(self):
         # this is just an estimate and does not factor in extra samples added to pad batches based on
@@ -207,7 +247,7 @@ class ParserTfds(Parser):
         return math.ceil(max(1, self.repeats) * self.num_samples / self.dist_num_replicas)
 
     def _filename(self, index, basename=False, absolute=False):
-        assert False, "Not supported" # no random access to samples
+        assert False, "Not supported"  # no random access to samples
 
     def filenames(self, basename=False, absolute=False):
         """ Return all filenames in dataset, overrides base"""

timm/models/byoanet.py

@@ -51,17 +51,17 @@ default_cfgs = {
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/sehalonet33ts_256-87e053f9.pth',
         input_size=(3, 256, 256), pool_size=(8, 8), min_input_size=(3, 256, 256), crop_pct=0.94),
     'halonet50ts': _cfg(
-        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/halonet50ts_256_ra3-f07eab9f.pth',
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/halonet50ts_a1h_256-c6d7ff15.pth',
         input_size=(3, 256, 256), pool_size=(8, 8), min_input_size=(3, 256, 256), crop_pct=0.94),
     'eca_halonext26ts': _cfg(
-        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/eca_halonext26ts_256-1e55880b.pth',
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/eca_halonext26ts_c_256-06906299.pth',
         input_size=(3, 256, 256), pool_size=(8, 8), min_input_size=(3, 256, 256), crop_pct=0.94),
 
     'lambda_resnet26t': _cfg(
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26t_c_256-e5a5c857.pth',
         min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8), crop_pct=0.94),
     'lambda_resnet50ts': _cfg(
-        url='',
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet50ts_a1h_256-b87370f7.pth',
         min_input_size=(3, 128, 128), input_size=(3, 256, 256), pool_size=(8, 8)),
     'lambda_resnet26rpt_256': _cfg(
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lambda_resnet26rpt_c_256-ab00292d.pth',
@@ -71,8 +71,12 @@ default_cfgs = {
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/haloregnetz_c_raa_256-c8ad7616.pth',
         mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5),
         first_conv='stem.conv', input_size=(3, 224, 224), pool_size=(7, 7), min_input_size=(3, 224, 224), crop_pct=0.94),
-    'trionet50ts_256': _cfg(
-        url='',
+
+    'lamhalobotnet50ts_256': _cfg(
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/lamhalobotnet_a1h_256-c9bc4e74.pth',
+        fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)),
+    'halo2botnet50ts_256': _cfg(
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-attn-weights/halo2botnet50ts_a1h_256-ad9e16fb.pth',
         fixed_input_size=True, input_size=(3, 256, 256), pool_size=(8, 8)),
 }
 
@@ -262,7 +266,7 @@ model_cfgs = dict(
     ),
 
     # experimental
-    trionet50ts=ByoModelCfg(
+    lamhalobotnet50ts=ByoModelCfg(
         blocks=(
             ByoBlockCfg(type='bottle', d=3, c=256, s=1, gs=0, br=0.25),
             interleave_blocks(
@@ -280,6 +284,24 @@ model_cfgs = dict(
         stem_pool='',
         act_layer='silu',
     ),
+    halo2botnet50ts=ByoModelCfg(
+        blocks=(
+            ByoBlockCfg(type='bottle', d=3, c=256, s=1, gs=0, br=0.25),
+            interleave_blocks(
+                types=('bottle', 'self_attn'), d=4, c=512, s=2, gs=0, br=0.25,
+                self_attn_layer='halo', self_attn_kwargs=dict(halo_size=3)),
+            interleave_blocks(
+                types=('bottle', 'self_attn'), d=6, c=1024, s=2, gs=0, br=0.25,
+                self_attn_layer='halo', self_attn_kwargs=dict(halo_size=3)),
+            interleave_blocks(
+                types=('bottle', 'self_attn'), d=3, c=2048, s=2, gs=0, br=0.25,
+                self_attn_layer='bottleneck', self_attn_kwargs=dict()),
+        ),
+        stem_chs=64,
+        stem_type='tiered',
+        stem_pool='',
+        act_layer='silu',
+    ),
 )
 
 
@@ -382,7 +404,14 @@ def haloregnetz_b(pretrained=False, **kwargs):
 
 
 @register_model
-def trionet50ts_256(pretrained=False, **kwargs):
-    """ TrioNet
+def lamhalobotnet50ts_256(pretrained=False, **kwargs):
+    """ Combo Attention (Lambda + Halo + Bot) Network
+    """
+    return _create_byoanet('lamhalobotnet50ts_256', 'lamhalobotnet50ts', pretrained=pretrained, **kwargs)
+
+
+@register_model
+def halo2botnet50ts_256(pretrained=False, **kwargs):
+    """ Combo Attention (Halo + Halo + Bot) Network
     """
-    return _create_byoanet('trionet50ts_256', 'trionet50ts', pretrained=pretrained, **kwargs)
+    return _create_byoanet('halo2botnet50ts_256', 'halo2botnet50ts', pretrained=pretrained, **kwargs)

timm/models/layers/__init__.py

@@ -36,4 +36,5 @@ from .split_attn import SplitAttn
 from .split_batchnorm import SplitBatchNorm2d, convert_splitbn_model
 from .std_conv import StdConv2d, StdConv2dSame, ScaledStdConv2d, ScaledStdConv2dSame
 from .test_time_pool import TestTimePoolHead, apply_test_time_pool
+from .trace_utils import _assert, _float_to_int
 from .weight_init import trunc_normal_, variance_scaling_, lecun_normal_

timm/models/layers/patch_embed.py

@@ -6,10 +6,10 @@ Based on the impl in https://github.com/google-research/vision_transformer
 
 Hacked together by / Copyright 2020 Ross Wightman
 """
-import torch
 from torch import nn as nn
 
 from .helpers import to_2tuple
+from .trace_utils import _assert
 
 
 class PatchEmbed(nn.Module):
@@ -30,8 +30,8 @@ class PatchEmbed(nn.Module):
 
     def forward(self, x):
         B, C, H, W = x.shape
-        torch._assert(H == self.img_size[0], f"Input image height ({H}) doesn't match model ({self.img_size[0]}).")
-        torch._assert(W == self.img_size[1], f"Input image width ({W}) doesn't match model ({self.img_size[1]}).")
+        _assert(H == self.img_size[0], f"Input image height ({H}) doesn't match model ({self.img_size[0]}).")
+        _assert(W == self.img_size[1], f"Input image width ({W}) doesn't match model ({self.img_size[1]}).")
         x = self.proj(x)
         if self.flatten:
             x = x.flatten(2).transpose(1, 2)  # BCHW -> BNC

timm/models/layers/trace_utils.py

@@ -0,0 +1,13 @@
+try:
+    from torch import _assert
+except ImportError:
+    def _assert(condition: bool, message: str):
+        assert condition, message
+
+
+def _float_to_int(x: float) -> int:
+    """
+    Symbolic tracing helper to substitute for inbuilt `int`.
+    Hint: Inbuilt `int` can't accept an argument of type `Proxy`
+    """
+    return int(x)

timm/models/resnet.py

@@ -61,12 +61,16 @@ default_cfgs = {
     'resnet50t': _cfg(
         url='',
         interpolation='bicubic', first_conv='conv1.0'),
-    'resnet101': _cfg(url='', interpolation='bicubic'),
+    'resnet101': _cfg(
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/resnet101_a1h-36d3f2aa.pth',
+        interpolation='bicubic', crop_pct=0.95),
     'resnet101d': _cfg(
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnet101d_ra2-2803ffab.pth',
         interpolation='bicubic', first_conv='conv1.0', input_size=(3, 256, 256), pool_size=(8, 8),
         crop_pct=1.0, test_input_size=(3, 320, 320)),
-    'resnet152': _cfg(url='', interpolation='bicubic'),
+    'resnet152': _cfg(
+        url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-rsb-weights/resnet152_a1h-dc400468.pth',
+        interpolation='bicubic', crop_pct=0.95),
     'resnet152d': _cfg(
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-weights/resnet152d_ra2-5cac0439.pth',
         interpolation='bicubic', first_conv='conv1.0', input_size=(3, 256, 256), pool_size=(8, 8),

train.py

@@ -51,7 +51,7 @@ parser.add_argument('-c', '--config', default='', type=str, metavar='FILE',
 
 parser = argparse.ArgumentParser(description='PyTorch ImageNet Training')
 
-# Dataset / Model parameters
+# Dataset parameters
 parser.add_argument('data_dir', metavar='DIR',
                     help='path to dataset')
 parser.add_argument('--dataset', '-d', metavar='NAME', default='',
@@ -60,6 +60,12 @@ parser.add_argument('--train-split', metavar='NAME', default='train',
                     help='dataset train split (default: train)')
 parser.add_argument('--val-split', metavar='NAME', default='validation',
                     help='dataset validation split (default: validation)')
+parser.add_argument('--dataset-download', action='store_true', default=False,
+                    help='Allow download of dataset for torch/ and tfds/ datasets that support it.')
+parser.add_argument('--class-map', default='', type=str, metavar='FILENAME',
+                    help='path to class to idx mapping file (default: "")')
+
+# Model parameters
 parser.add_argument('--model', default='resnet50', type=str, metavar='MODEL',
                     help='Name of model to train (default: "resnet50"')
 parser.add_argument('--pretrained', action='store_true', default=False,
@@ -500,13 +506,17 @@ def setup_data(args, default_cfg, dev_env: DeviceEnv, mixup_active: bool):
 
     # create the train and eval datasets
     dataset_train = create_dataset(
-        args.dataset,
-        root=args.data_dir, split=args.train_split, is_training=True,
-        batch_size=args.batch_size, repeats=args.epoch_repeats)
+        name=args.dataset, root=args.data_dir, split=args.train_split, is_training=True,
+        class_map=args.class_map,
+        download=args.dataset_download,
+        batch_size=args.batch_size,
+        repeats=args.epoch_repeats)
 
     dataset_eval = create_dataset(
-        args.dataset,
-        root=args.data_dir, split=args.val_split, is_training=False, batch_size=args.batch_size)
+        name=args.dataset, root=args.data_dir, split=args.val_split, is_training=False,
+        class_map=args.class_map,
+        download=args.dataset_download,
+        batch_size=args.batch_size)
 
     # setup mixup / cutmix
     mixup_cfg = None

validate.py

@@ -35,6 +35,8 @@ parser.add_argument('--dataset', '-d', metavar='NAME', default='',
                     help='dataset type (default: ImageFolder/ImageTar if empty)')
 parser.add_argument('--split', metavar='NAME', default='validation',
                     help='dataset split (default: validation)')
+parser.add_argument('--dataset-download', action='store_true', default=False,
+                    help='Allow download of dataset for torch/ and tfds/ datasets that support it.')
 parser.add_argument('--model', '-m', metavar='NAME', default='resnet50',
                     help='model architecture (default: resnet50)')
 parser.add_argument('-j', '--workers', default=4, type=int, metavar='N',
@@ -130,7 +132,7 @@ def validate(args):
 
     dataset = create_dataset(
         root=args.data, name=args.dataset, split=args.split,
-        load_bytes=args.tf_preprocessing, class_map=args.class_map)
+        download=args.dataset_download, load_bytes=args.tf_preprocessing, class_map=args.class_map)
 
     if args.valid_labels:
         with open(args.valid_labels, 'r') as f: