Commit Graph

104 Commits (45dec179e5d47d69dbbf9d6b7b7fb6e9bf733a76)

Author SHA1 Message Date
Ross Wightman bda8ab015a Remove min channels for SelectiveKernel, divisor should cover cases well enough.
4 years ago
Ross Wightman a27f4aec4a Missed args for skresnext w/ refactoring.
4 years ago
Ross Wightman 307a935b79 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
Ross Wightman 8bf63b6c6c Able to use other attn layer in EfficientNet now. Create test ECA + GC B0 configs. Make ECA more configurable.
4 years ago
Ross Wightman 9611458e19 Throw in some FBNetV3 code I had lying around, some refactoring of SE reduction channel calcs for all EffNet archs.
4 years ago
Ross Wightman f615474be3 Fix broken test, repvgg block doesn't have attn_last attr.
4 years ago
Ross Wightman 742c2d5247 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
Ross Wightman 9c78de8c02 Fix #661, move hardswish out of default args for LeViT. Enable native torch support for hardswish, hardsigmoid, mish if present.
4 years ago
Ross Wightman f45de37690 Merge branch 'master' into levit_visformer_rednet
4 years ago
Ross Wightman d5af752117 Add preliminary gMLP and ResMLP impl to Mlp-Mixer
4 years ago
Ross Wightman 3bffc701f1 Merge branch 'master' into levit_visformer_rednet
4 years ago
Ross Wightman ecc7552c5c Add levit, levit_c, and visformer model defs. Largely untested and not finished cleanup.
4 years ago
Ross Wightman 165fb354b2 Add initial RedNet model / Involution layer impl for testing
4 years ago
Ross Wightman c4f482a08b EfficientNetV2 official impl w/ weights ported from TF. Cleanup/refactor of related EfficientNet classes and models.
4 years ago
Ross Wightman 715519a5ef Rethink name of patch embed grid info
4 years ago
Ross Wightman b2c305c2aa Move Mlp and PatchEmbed modules into layers. Being used in lots of models now...
4 years ago
Ross Wightman 0721559511 Improved (hopefully) init for SA/SA-like layers used in ByoaNets
4 years ago
Ross Wightman 0d87650fea Remove filter hack from BlurPool w/ non-persistent buffer. Use BlurPool2d instead of AntiAliasing.. for TResNet. Breaks PyTorch < 1.6.
4 years ago
Ross Wightman 9cc7dda6e5 Fixup byoanet configs to pass unit tests. Add swin_attn and swinnet26t model for testing.
4 years ago
Ross Wightman e15c3886ba Defaul lambda r=7. Define '26t' stage 4/5 256x256 variants for all of bot/halo/lambda nets for experiment. Add resnet50t for exp. Fix a few comments.
4 years ago
Ross Wightman 4e4b863b15 Missed norm.py
4 years ago
Ross Wightman ce62f96d4d ByoaNet with bottleneck transformer, lambda resnet, and halo net experiments
4 years ago
Ross Wightman a5310a3451 Merge remote-tracking branch 'origin/benchmark-fixes-vit_hybrids' into pit_and_vit_update
4 years ago
Ross Wightman cf5fec5047 Cleanup experimental vit weight init a bit
4 years ago
Ross Wightman 740f32c96a Add ECA-NFNet-L0 weights and update model name. Update README and bump version to 0.4.6
4 years ago
Ross Wightman f57db99101 Update README, fix iabn pip version print.
4 years ago
Ross Wightman 8563609b28 Update notes in ScaledStdConv impl
4 years ago
Ross Wightman 678ba4e0a2 Add NFNet-F model weights ported from DeepMind Haiku impl and new set of models w/ compatible config.
4 years ago
Ross Wightman d8e69206be
Merge pull request #419 from rwightman/byob_vgg_models
4 years ago
Reuben 94ca140b67 update collections.abc import
4 years ago
Ross Wightman 1bcc69e0ad Use in_channels for depthwise groups, allows using `out_channels=N * in_channels` (does not impact existing models). Fix #354.
4 years ago
Ross Wightman 9811e229f7 Fix regression in models with 1001 class pretrained weights. Improve batchnorm arg and BatchNormAct layer handling in several models.
4 years ago
Ross Wightman a39c3ee216
Merge branch 'master' into eca-weights
4 years ago
Ross Wightman 68a4144882 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.
4 years ago
Ross Wightman b9843f954b
Merge pull request #282 from tigert1998/patch-1
4 years ago
hwangdeyu 7a4be5c035 add operator HardSwishJitAutoFn export to onnx
4 years ago
Ross Wightman 90980de4a9 Fix up a few details in NFResNet models, managed stable training. Add support for gamma gain to be applied in activation or ScaleStdConv. Some tweaks to ScaledStdConv.
4 years ago
Ross Wightman 5a8e1e643e Initial Normalizer-Free Reg/ResNet impl. A bit of related layer refactoring.
4 years ago
Ross Wightman 231d04e91a ResNetV2 pre-act and non-preact model, w/ BiT pretrained weights and support for ViT R50 model. Tweaks for in21k num_classes passing. More to do... tests failing.
4 years ago
Ross Wightman 2ed8f24715 A few more changes for 0.3.2 maint release. Linear layer change for mobilenetv3 and inception_v3, support no bias for linear wrapper.
4 years ago
Ross Wightman 460eba7f24 Work around casting issue with combination of native torch AMP and torchscript for Linear layers
4 years ago
Ross Wightman 5f4b6076d8 Fix inplace arg compat for GELU and PreLU via activation factory
4 years ago
Ross Wightman fd962c4b4a Native SiLU (Swish) op doesn't export to ONNX
4 years ago
tigertang 43f2500c26
Add symbolic for SwishJitAutoFn to support onnx
4 years ago
Ross Wightman e90edce438 Support native silu activation (aka swish). An optimized ver is available in PyTorch 1.7.
4 years ago
Ross Wightman f31933cb37 Initial Vision Transformer impl w/ patch and hybrid variants. Refactor tuple helpers.
4 years ago
Ross Wightman fcb6258877 Add missing leaky_relu layer factory defn, update Apex/Native loss scaler interfaces to support unscaled grad clipping. Bump ver to 0.2.2 for pending release.
4 years ago
Ross Wightman e8ca45854c More models in sotabench, more control over sotabench run, dataset filename extraction consistency
4 years ago
Ross Wightman 80c9d9cc72 Add 'fast' global pool option, remove redundant SEModule from tresnet, normal one is now 'fast'
4 years ago
Ross Wightman 110a7c4982 AdaptiveAvgPool2d -> mean((2,3)) for all SE/attn layers to avoid NaN with AMP + channels_last layout. See https://github.com/pytorch/pytorch/issues/43992
4 years ago