Fiddling...

timm/models/efficientnet.py

@@ -322,6 +322,7 @@ class EfficientNet(nn.Module):
         # Stem
         if not fix_stem:
             stem_size = round_channels(stem_size, channel_multiplier, channel_divisor, channel_min)
+        print(stem_size)
         self.conv_stem = create_conv2d(self._in_chs, stem_size, 3, stride=2, padding=pad_type)
         self.bn1 = norm_layer(stem_size, **norm_kwargs)
         self.act1 = act_layer(inplace=True)
@@ -569,7 +570,8 @@ def _gen_mnasnet_small(variant, channel_multiplier=1.0, pretrained=False, **kwar
     return model
 
 
-def _gen_mobilenet_v2(variant, channel_multiplier=1.0, depth_multiplier=1.0, pretrained=False, **kwargs):
+def _gen_mobilenet_v2(
+        variant, channel_multiplier=1.0, depth_multiplier=1.0, fix_stem_head=False, pretrained=False, **kwargs):
     """ Generate MobileNet-V2 network
     Ref impl: https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/mobilenet_v2.py
     Paper: https://arxiv.org/abs/1801.04381
@@ -584,8 +586,10 @@ def _gen_mobilenet_v2(variant, channel_multiplier=1.0, depth_multiplier=1.0, pre
         ['ir_r1_k3_s1_e6_c320'],
     ]
     model_kwargs = dict(
-        block_args=decode_arch_def(arch_def, depth_multiplier=depth_multiplier),
+        block_args=decode_arch_def(arch_def, depth_multiplier=depth_multiplier, fix_first_last=fix_stem_head),
+        num_features=1280 if fix_stem_head else round_channels(1280, channel_multiplier, 8, None),
         stem_size=32,
+        fix_stem=fix_stem_head,
         channel_multiplier=channel_multiplier,
         norm_kwargs=resolve_bn_args(kwargs),
         act_layer=nn.ReLU6,
@@ -955,23 +959,25 @@ def mobilenetv2_100(pretrained=False, **kwargs):
 
 
 @register_model
-def mobilenetv2_100d(pretrained=False, **kwargs):
+def mobilenetv2_140(pretrained=False, **kwargs):
     """ MobileNet V2 """
-    model = _gen_mobilenet_v2('mobilenetv2_100d', 1.0, depth_multiplier=1.1, pretrained=pretrained, **kwargs)
+    model = _gen_mobilenet_v2('mobilenetv2_140', 1.4, pretrained=pretrained, **kwargs)
     return model
 
 
 @register_model
 def mobilenetv2_110d(pretrained=False, **kwargs):
     """ MobileNet V2 """
-    model = _gen_mobilenet_v2('mobilenetv2_110d', 1.1, depth_multiplier=1.2, pretrained=pretrained, **kwargs)
+    model = _gen_mobilenet_v2(
+        'mobilenetv2_100d', 1.1, depth_multiplier=1.2, fix_stem_head=True, pretrained=pretrained, **kwargs)
     return model
 
 
 @register_model
-def mobilenetv2_140(pretrained=False, **kwargs):
+def mobilenetv2_120d(pretrained=False, **kwargs):
     """ MobileNet V2 """
-    model = _gen_mobilenet_v2('mobilenetv2_140', 1.4, pretrained=pretrained, **kwargs)
+    model = _gen_mobilenet_v2(
+        'mobilenetv2_110d', 1.2, depth_multiplier=1.4, fix_stem_head=True, pretrained=pretrained, **kwargs)
     return model