Big move, layer modules and fn to timm/models/layers

timm/models/__init__.py

@@ -21,5 +21,5 @@ from .sknet import *
 from .registry import *
 from .factory import create_model
 from .helpers import load_checkpoint, resume_checkpoint
-from .test_time_pool import TestTimePoolHead, apply_test_time_pool
-from .split_batchnorm import convert_splitbn_model
+from .layers import TestTimePoolHead, apply_test_time_pool
+from .layers import convert_splitbn_model

timm/models/densenet.py

@@ -10,7 +10,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 import re
 

timm/models/dla.py

@@ -13,7 +13,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 

timm/models/dpn.py

@@ -16,7 +16,7 @@ from collections import OrderedDict
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DPN_MEAN, IMAGENET_DPN_STD
 
 

timm/models/efficientnet.py

@@ -27,8 +27,7 @@ from .efficientnet_builder import *
 from .feature_hooks import FeatureHooks
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
-from .conv2d_layers import select_conv2d
+from .layers import SelectAdaptivePool2d, select_conv2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
 
 

timm/models/efficientnet_blocks.py

@@ -4,8 +4,8 @@ from functools import partial
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from .activations import sigmoid
-from .conv2d_layers import *
+from .layers.activations import sigmoid
+from .layers.conv2d_layers import *
 
 
 # Defaults used for Google/Tensorflow training of mobile networks /w RMSprop as per

timm/models/efficientnet_builder.py

@@ -5,7 +5,7 @@ from collections.__init__ import OrderedDict
 from copy import deepcopy
 
 import torch.nn as nn
-from .activations import sigmoid, HardSwish, Swish
+from .layers.activations import sigmoid, HardSwish, Swish
 from .efficientnet_blocks import *
 
 

timm/models/gluon_xception.py

@@ -13,7 +13,7 @@ from collections import OrderedDict
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 __all__ = ['Xception65', 'Xception71']

timm/models/hrnet.py

@@ -25,7 +25,7 @@ import torch.nn.functional as F
 from .resnet import BasicBlock, Bottleneck  # leveraging ResNet blocks w/ additional features like SE
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 _BN_MOMENTUM = 0.1

timm/models/inception_resnet_v2.py

@@ -8,7 +8,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
 
 __all__ = ['InceptionResnetV2']

timm/models/inception_v4.py

@@ -8,7 +8,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
 
 __all__ = ['InceptionV4']

timm/models/layers/__init__.py

@@ -1 +1,8 @@
+from .conv2d_layers import select_conv2d, MixedConv2d, CondConv2d, ConvBnAct, SelectiveKernelConv
 from .eca import EcaModule, CecaModule
+from .activations import *
+from .adaptive_avgmax_pool import \
+    adaptive_avgmax_pool2d, select_adaptive_pool2d, AdaptiveAvgMaxPool2d, SelectAdaptivePool2d
+from .nn_ops import DropBlock2d, DropPath
+from .test_time_pool import TestTimePoolHead, apply_test_time_pool
+from .split_batchnorm import SplitBatchNorm2d, convert_splitbn_model

timm/models/mobilenetv3.py

@@ -11,11 +11,10 @@ import torch.nn as nn
 import torch.nn.functional as F
 
 from .efficientnet_builder import *
-from .activations import HardSwish, hard_sigmoid
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
-from .conv2d_layers import select_conv2d
+from .layers import SelectAdaptivePool2d, select_conv2d
+from .layers.activations import HardSwish, hard_sigmoid
 from .feature_hooks import FeatureHooks
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_INCEPTION_MEAN, IMAGENET_INCEPTION_STD
 

timm/models/nasnet.py

@@ -4,7 +4,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 
 
 __all__ = ['NASNetALarge']

timm/models/pnasnet.py

@@ -14,7 +14,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 
 __all__ = ['PNASNet5Large']
 

timm/models/res2net.py

@@ -11,7 +11,7 @@ import torch.nn.functional as F
 from .resnet import ResNet, SEModule
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 __all__ = []

timm/models/resnet.py

@@ -13,9 +13,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
-from .layers import EcaModule
-from .nn_ops import DropBlock2d, DropPath
+from .layers import EcaModule, SelectAdaptivePool2d, DropBlock2d, DropPath
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 

timm/models/selecsls.py

@@ -17,7 +17,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 __all__ = ['SelecSLS']  # model_registry will add each entrypoint fn to this

timm/models/senet.py

@@ -16,7 +16,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 __all__ = ['SENet']

timm/models/sknet.py

@@ -2,10 +2,10 @@ import math
 
 from torch import nn as nn
 
-from timm.models.registry import register_model
-from timm.models.helpers import load_pretrained
-from timm.models.conv2d_layers import SelectiveKernelConv, ConvBnAct
-from timm.models.resnet import ResNet, SEModule
+from .registry import register_model
+from .helpers import load_pretrained
+from .layers import SelectiveKernelConv, ConvBnAct
+from .resnet import ResNet, SEModule
 from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
 
 

timm/models/xception.py

@@ -29,7 +29,7 @@ import torch.nn.functional as F
 
 from .registry import register_model
 from .helpers import load_pretrained
-from .adaptive_avgmax_pool import SelectAdaptivePool2d
+from .layers import SelectAdaptivePool2d
 
 __all__ = ['Xception']