Major module / path restructure, timm.models.layers -> timm.layers, add _ prefix to all non model modules in timm.models

Author: rwightman

avg_checkpoints.py

@@ -16,7 +16,7 @@
 import os
 import glob
 import hashlib
-from timm.models.helpers import load_state_dict
+from timm.models import load_state_dict
 
 parser = argparse.ArgumentParser(description='PyTorch Checkpoint Averager')
 parser.add_argument('--input', default='', type=str, metavar='PATH',

clean_checkpoint.py

@@ -13,7 +13,7 @@
 import hashlib
 import shutil
 from collections import OrderedDict
-from timm.models.helpers import load_state_dict
+from timm.models import load_state_dict
 
 parser = argparse.ArgumentParser(description='PyTorch Checkpoint Cleaner')
 parser.add_argument('--checkpoint', default='', type=str, metavar='PATH',

hubconf.py

@@ -1,4 +1,3 @@
 dependencies = ['torch']
-from timm.models import registry
-
-globals().update(registry._model_entrypoints)
+import timm
+globals().update(timm.models._registry._model_entrypoints)

inference.py

@@ -5,24 +5,23 @@
 
 Hacked together by / Copyright 2020 Ross Wightman (https://github.com/rwightman)
 """
-import os
-import time
 import argparse
 import json
 import logging
+import os
+import time
 from contextlib import suppress
 from functools import partial
 
 import numpy as np
 import pandas as pd
 import torch
 
-from timm.models import create_model, apply_test_time_pool, load_checkpoint
 from timm.data import create_dataset, create_loader, resolve_data_config
+from timm.layers import apply_test_time_pool
+from timm.models import create_model
 from timm.utils import AverageMeter, setup_default_logging, set_jit_fuser
 
-
-
 try:
     from apex import amp
     has_apex = True

tests/test_layers.py

@@ -1,10 +1,7 @@
-import pytest
 import torch
 import torch.nn as nn
-import platform
-import os
 
-from timm.models.layers import create_act_layer, get_act_layer, set_layer_config
+from timm.layers import create_act_layer, set_layer_config
 
 
 class MLP(nn.Module):

tests/test_models.py

@@ -14,7 +14,7 @@
 
 import timm
 from timm import list_models, create_model, set_scriptable, get_pretrained_cfg_value
-from timm.models.fx_features import _leaf_modules, _autowrap_functions    
+from timm.models._features_fx import _leaf_modules, _autowrap_functions
 
 if hasattr(torch._C, '_jit_set_profiling_executor'):
     # legacy executor is too slow to compile large models for unit tests

timm/__init__.py

@@ -1,4 +1,4 @@
 from .version import __version__
+from .layers import is_scriptable, is_exportable, set_scriptable, set_exportable
 from .models import create_model, list_models, list_pretrained, is_model, list_modules, model_entrypoint, \
-    is_scriptable, is_exportable, set_scriptable, set_exportable, \
     is_model_pretrained, get_pretrained_cfg, get_pretrained_cfg_value

timm/data/readers/class_map.py

@@ -1,6 +1,7 @@
 import os
 import pickle
 
+
 def load_class_map(map_or_filename, root=''):
     if isinstance(map_or_filename, dict):
         assert dict, 'class_map dict must be non-empty'
@@ -14,7 +15,7 @@ def load_class_map(map_or_filename, root=''):
         with open(class_map_path) as f:
             class_to_idx = {v.strip(): k for k, v in enumerate(f)}
     elif class_map_ext == '.pkl':
-        with open(class_map_path,'rb') as f:
+        with open(class_map_path, 'rb') as f:
             class_to_idx = pickle.load(f)
     else:
         assert False, f'Unsupported class map file extension ({class_map_ext}).'

timm/layers/__init__.py

@@ -0,0 +1,44 @@
+from .activations import *
+from .adaptive_avgmax_pool import \
+    adaptive_avgmax_pool2d, select_adaptive_pool2d, AdaptiveAvgMaxPool2d, SelectAdaptivePool2d
+from .blur_pool import BlurPool2d
+from .classifier import ClassifierHead, create_classifier
+from .cond_conv2d import CondConv2d, get_condconv_initializer
+from .config import is_exportable, is_scriptable, is_no_jit, set_exportable, set_scriptable, set_no_jit,\
+    set_layer_config
+from .conv2d_same import Conv2dSame, conv2d_same
+from .conv_bn_act import ConvNormAct, ConvNormActAa, ConvBnAct
+from .create_act import create_act_layer, get_act_layer, get_act_fn
+from .create_attn import get_attn, create_attn
+from .create_conv2d import create_conv2d
+from .create_norm import get_norm_layer, create_norm_layer
+from .create_norm_act import get_norm_act_layer, create_norm_act_layer, get_norm_act_layer
+from .drop import DropBlock2d, DropPath, drop_block_2d, drop_path
+from .eca import EcaModule, CecaModule, EfficientChannelAttn, CircularEfficientChannelAttn
+from .evo_norm import EvoNorm2dB0, EvoNorm2dB1, EvoNorm2dB2,\
+    EvoNorm2dS0, EvoNorm2dS0a, EvoNorm2dS1, EvoNorm2dS1a, EvoNorm2dS2, EvoNorm2dS2a
+from .fast_norm import is_fast_norm, set_fast_norm, fast_group_norm, fast_layer_norm
+from .filter_response_norm import FilterResponseNormTlu2d, FilterResponseNormAct2d
+from .gather_excite import GatherExcite
+from .global_context import GlobalContext
+from .helpers import to_ntuple, to_2tuple, to_3tuple, to_4tuple, make_divisible, extend_tuple
+from .inplace_abn import InplaceAbn
+from .linear import Linear
+from .mixed_conv2d import MixedConv2d
+from .mlp import Mlp, GluMlp, GatedMlp, ConvMlp
+from .non_local_attn import NonLocalAttn, BatNonLocalAttn
+from .norm import GroupNorm, GroupNorm1, LayerNorm, LayerNorm2d
+from .norm_act import BatchNormAct2d, GroupNormAct, convert_sync_batchnorm
+from .padding import get_padding, get_same_padding, pad_same
+from .patch_embed import PatchEmbed
+from .pool2d_same import AvgPool2dSame, create_pool2d
+from .squeeze_excite import SEModule, SqueezeExcite, EffectiveSEModule, EffectiveSqueezeExcite
+from .selective_kernel import SelectiveKernel
+from .separable_conv import SeparableConv2d, SeparableConvNormAct
+from .space_to_depth import SpaceToDepthModule
+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_, trunc_normal_tf_, variance_scaling_, lecun_normal_

timm/models/layers/activations.py timm/layers/activations.py

@@ -64,12 +64,18 @@
 from .xception_aligned import *
 from .xcit import *
 
-from .factory import create_model, parse_model_name, safe_model_name
-from .helpers import load_checkpoint, resume_checkpoint, model_parameters
-from .layers import TestTimePoolHead, apply_test_time_pool
-from .layers import convert_splitbn_model, convert_sync_batchnorm
-from .layers import is_scriptable, is_exportable, set_scriptable, set_exportable, is_no_jit, set_no_jit
-from .layers import set_fast_norm
-from .pretrained import PretrainedCfg, filter_pretrained_cfg, generate_default_cfgs, split_model_name_tag
-from .registry import register_model, model_entrypoint, list_models, list_pretrained, is_model, list_modules,\
+from ._builder import build_model_with_cfg, load_pretrained, load_custom_pretrained, resolve_pretrained_cfg, \
+    set_pretrained_download_progress, set_pretrained_check_hash
+from ._factory import create_model, parse_model_name, safe_model_name
+from ._features import FeatureInfo, FeatureHooks, FeatureHookNet, FeatureListNet, FeatureDictNet
+from ._features_fx import FeatureGraphNet, GraphExtractNet, create_feature_extractor, \
+    register_notrace_module, register_notrace_function
+from ._helpers import clean_state_dict, load_state_dict, load_checkpoint, remap_checkpoint, resume_checkpoint
+from ._hub import load_model_config_from_hf, load_state_dict_from_hf, push_to_hf_hub
+from ._manipulate import model_parameters, named_apply, named_modules, named_modules_with_params, \
+    group_modules, group_parameters, checkpoint_seq, adapt_input_conv
+from ._pretrained import PretrainedCfg, DefaultCfg, \
+    filter_pretrained_cfg, generate_default_cfgs, split_model_name_tag
+from ._prune import adapt_model_from_string
+from ._registry import register_model, model_entrypoint, list_models, list_pretrained, is_model, list_modules, \
     is_model_in_modules, is_model_pretrained, get_pretrained_cfg, get_pretrained_cfg_value