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pytorch-image-models/timm/models/layers
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Ross Wightman 372ad5fa0d Significant model refactor and additions: 
* All models updated with revised foward_features / forward_head interface
* Vision transformer and MLP based models consistently output sequence from forward_features (pooling or token selection considered part of 'head')
* WIP param grouping interface to allow consistent grouping of parameters for layer-wise decay across all model types
* Add gradient checkpointing support to a significant % of models, especially popular architectures
* Formatting and interface consistency improvements across models
* layer-wise LR decay impl part of optimizer factory w/ scale support in scheduler
* Poolformer and Volo architectures added
 		2022-02-28 13:56:23 -08:00
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__init__.py Merge remote-tracking branch 'origin/master' into norm_norm_norm 2022-01-25 22:20:45 -08:00
activations.py
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activations_jit.py
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activations_me.py Merge pull request #282 from tigert1998/patch-1 2021-02-04 12:18:40 -08:00
adaptive_avgmax_pool.py Refactoring, cleanup, improved test coverage. 2021-06-12 16:40:02 -07:00
attention_pool2d.py Significant model refactor and additions: 2022-02-28 13:56:23 -08:00
blur_pool.py Remove filter hack from BlurPool w/ non-persistent buffer. Use BlurPool2d instead of AntiAliasing.. for TResNet. Breaks PyTorch < 1.6. 2021-05-04 16:56:28 -07:00
bottleneck_attn.py wip - pre-rebase 2021-11-12 20:45:05 +00:00
cbam.py Significant norm update 2021-12-14 13:48:30 -08:00
classifier.py Significant model refactor and additions: 2022-02-28 13:56:23 -08:00
cond_conv2d.py
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config.py
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conv2d_same.py
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conv_bn_act.py Significant norm update 2021-12-14 13:48:30 -08:00
create_act.py Updated EvoNorm implementations with some experimentation. Add FilterResponseNorm. Updated RegnetZ and ResNetV2 model defs for trials. 2021-12-01 12:09:01 -08:00
create_attn.py Update attention / self-attn based models from a series of experiments: 2021-08-20 16:13:11 -07:00
create_conv2d.py Significant norm update 2021-12-14 13:48:30 -08:00
create_norm_act.py Significant norm update 2021-12-14 13:48:30 -08:00
drop.py Merge remote-tracking branch 'origin/master' into norm_norm_norm 2022-01-25 22:20:45 -08:00
eca.py Add non-local and BAT attention. Merge attn and self-attn factories into one. Add attention references to README. Add mlp 'mode' to ECA. 2021-05-31 13:18:11 -07:00
evo_norm.py Significant model refactor and additions: 2022-02-28 13:56:23 -08:00
filter_response_norm.py Updated EvoNorm implementations with some experimentation. Add FilterResponseNorm. Updated RegnetZ and ResNetV2 model defs for trials. 2021-12-01 12:09:01 -08:00
gather_excite.py Add Gather-Excite and Global Context attn modules. Refactor existing SE-like attn for consistency and refactor byob/byoanet for less redundancy. 2021-05-27 18:03:29 -07:00
global_context.py wip - pre-rebase 2021-11-12 20:45:05 +00:00
halo_attn.py wip - pre-rebase 2021-11-12 20:45:05 +00:00
helpers.py Throw in some FBNetV3 code I had lying around, some refactoring of SE reduction channel calcs for all EffNet archs. 2021-05-28 20:47:24 -07:00
inplace_abn.py Significant norm update 2021-12-14 13:48:30 -08:00
lambda_layer.py wip - pre-rebase 2021-11-12 20:45:05 +00:00
linear.py A few more changes for 0.3.2 maint release. Linear layer change for mobilenetv3 and inception_v3, support no bias for linear wrapper. 2020-11-30 16:19:52 -08:00
median_pool.py
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mixed_conv2d.py Use in_channels for depthwise groups, allows using `out_channels=N * in_channels` (does not impact existing models). Fix #354. 2021-02-09 16:22:52 -08:00
mlp.py Cleanup re-use of Dropout modules in Mlp modules after some twitter feedback :p 2021-10-25 00:40:59 -07:00
non_local_attn.py Significant norm update 2021-12-14 13:48:30 -08:00
norm.py Add ResNet-50 w/ GN (resnet50_gn) and SEBotNet-33-TS (sebotnet33ts_256) model defs and weights. Update halonet50ts weights w/ slightly better variant in1k val, more robust to test sets. 2021-11-19 14:24:43 -08:00
norm_act.py Significant norm update 2021-12-14 13:48:30 -08:00
padding.py
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patch_embed.py wip - attempting to rebase 2021-11-12 20:45:05 +00:00
pool2d_same.py Support npz custom load for vision transformer hybrid models. Add posembed rescale for npz load. 2021-06-14 12:31:44 -07:00
pos_embed.py Significant model refactor and additions: 2022-02-28 13:56:23 -08:00
selective_kernel.py Significant norm update 2021-12-14 13:48:30 -08:00
separable_conv.py Significant norm update 2021-12-14 13:48:30 -08:00
space_to_depth.py
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split_attn.py Significant norm update 2021-12-14 13:48:30 -08:00
split_batchnorm.py
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squeeze_excite.py Add non-local and BAT attention. Merge attn and self-attn factories into one. Add attention references to README. Add mlp 'mode' to ECA. 2021-05-31 13:18:11 -07:00
std_conv.py Use reshape instead of view in std_conv, causing issues in recent PyTorch in channels_last 2021-09-23 15:43:48 -07:00
test_time_pool.py Add new weights for ecaresnet26t/50t/269d models. Remove distinction between 't' and 'tn' (tiered models), tn is now t. Add test time img size spec to default cfg. 2021-02-06 16:30:02 -08:00
trace_utils.py Better fix for #954 that doesn't break torchscript, pull torch._assert into timm namespace when it exists 2021-11-02 11:22:33 -07:00
weight_init.py Cleanup experimental vit weight init a bit 2021-03-20 09:44:24 -07:00