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pytorch-image-models/timm/models/layers
Ross Wightman 01cb46a9a5
Add gc_efficientnetv2_rw_t weights (global context instead of SE attn). Add TF XL weights even though the fine-tuned ones don't validate that well. Change default arg for GlobalContext to use scal (mul) mode.
3 years ago
..
__init__.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. 4 years ago
activations.py
activations_jit.py
activations_me.py
adaptive_avgmax_pool.py Refactoring, cleanup, improved test coverage. 4 years ago
blur_pool.py
bottleneck_attn.py Improved (hopefully) init for SA/SA-like layers used in ByoaNets 4 years ago
cbam.py Add Gather-Excite and Global Context attn modules. Refactor existing SE-like attn for consistency and refactor byob/byoanet for less redundancy. 4 years ago
classifier.py Refactoring, cleanup, improved test coverage. 4 years ago
cond_conv2d.py
config.py
conv2d_same.py
conv_bn_act.py
create_act.py Fix #661, move hardswish out of default args for LeViT. Enable native torch support for hardswish, hardsigmoid, mish if present. 4 years ago
create_attn.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. 4 years ago
create_conv2d.py
create_norm_act.py
drop.py
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. 4 years ago
evo_norm.py
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. 4 years ago
global_context.py Add gc_efficientnetv2_rw_t weights (global context instead of SE attn). Add TF XL weights even though the fine-tuned ones don't validate that well. Change default arg for GlobalContext to use scal (mul) mode. 3 years ago
halo_attn.py Improved (hopefully) init for SA/SA-like layers used in ByoaNets 4 years ago
helpers.py Throw in some FBNetV3 code I had lying around, some refactoring of SE reduction channel calcs for all EffNet archs. 4 years ago
inplace_abn.py
involution.py Add Gather-Excite and Global Context attn modules. Refactor existing SE-like attn for consistency and refactor byob/byoanet for less redundancy. 4 years ago
lambda_layer.py Improved (hopefully) init for SA/SA-like layers used in ByoaNets 4 years ago
linear.py
median_pool.py
mixed_conv2d.py
mlp.py Refactoring, cleanup, improved test coverage. 4 years ago
non_local_attn.py Fix torchscript issue in bat 4 years ago
norm.py Realized LayerNorm2d won't work in all cases as is, fixed. 4 years ago
norm_act.py
padding.py
patch_embed.py Add levit, levit_c, and visformer model defs. Largely untested and not finished cleanup. 4 years ago
pool2d_same.py Support npz custom load for vision transformer hybrid models. Add posembed rescale for npz load. 4 years ago
selective_kernel.py Remove min channels for SelectiveKernel, divisor should cover cases well enough. 4 years ago
separable_conv.py
space_to_depth.py
split_attn.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. 4 years ago
split_batchnorm.py
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. 4 years ago
std_conv.py Add file docstring to std_conv.py 4 years ago
swin_attn.py Improved (hopefully) init for SA/SA-like layers used in ByoaNets 4 years ago
test_time_pool.py
weight_init.py