68 Commits (08d60f4a9a385b1eaf132a0ac1cff37b4ad94ac8)

Author	SHA1	Message	Date
Ross Wightman	08d60f4a9a	resnetrs50 pool sizing wrong	4 years ago
Ross Wightman	67d0665b46	Post ResNet-RS merge cleanup. Add weight urls, adjust train/test/crop pct.	4 years ago
Aman Arora	560eae38f5	[WIP] Add ResNet-RS models (#554) ... * Add ResNet-RS models * Only include resnet-rs changes * remove whitespace diff * EOF newline * Update time * increase time * Add first conv * Try running only resnetv2_101x1_bitm on Linux runner * Add to exclude filter * Run test_model_forward_features for all * Add to exclude ftrs * back to defaults * only run test_forward_features * run all tests * Run all tests * Add bigger resnetrs to model filters to fix Github CLI * Remove resnetv2_101x1_bitm from exclude feat features * Remove hardcoded values * Make sure reduction ratio in resnetrs is 0.25 * There is no bias in replaced maxpool so remove it	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	d584e7f617	Support for huggingface hub via create_model and default_cfgs. ... * improve consistency of model creation helper fns * add comments to some of the model helpers * support passing external default_cfgs so they can be sourced from hub	4 years ago
Ross Wightman	3b57490a63	Fix some half removed resnet model defs, pooling for ecaresnet269d	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	22748f1a2d	Convert samples/targets in ParserImageInTar to numpy arrays, slightly less mem usage for massive datasets. Add a few more se/eca model defs to resnet.py	4 years ago
Ross Wightman	4e2533db77	Add 320x320 model default cfgs for 101D and 152D ResNets. Add SEResNet-152D weights and 320x320 cfg.	4 years ago
Ross Wightman	392595c7eb	Add pool_size to default cfgs for new models to prevent tests from failing. Add explicit 200D_320 model entrypoint for next benchmark run.	4 years ago
Ross Wightman	b1f1228a41	Add ResNet101D, 152D, and 200D weights, remove meh 66d model	4 years ago
Ross Wightman	c40384f5bd	Add ResNet weights. 80.5 (top-1) ResNet-50-D, 77.1 ResNet-34-D, 72.7 ResNet-18-D.	4 years ago
Ross Wightman	33f8a1bf36	Updated README, add wide_resnet50_2 and seresnext50_32x4d weights	4 years ago
Yusuke Uchida	f6b56602f9	fix test_model_default_cfgs	4 years ago
Ross Wightman	b1f1a54de9	More uniform treatment of classifiers across all models, reduce code duplication.	4 years ago
Ross Wightman	d72ddafe56	Fix some checkpoint / model str regressions	4 years ago
Ross Wightman	9ecd16bd7b	Add new seresnet50 (non-legacy) model weights, 80.274 top-1	4 years ago
Ross Wightman	6c17d57a2c	Fix some attributions, add copyrights to some file docstrings	4 years ago
Ross Wightman	3b9004bef9	Lots of changes to model creation helpers, close to finalizing feature extraction / interfaces	4 years ago
Ross Wightman	f122f0274b	Significant ResNet refactor: ... * stage creation + make_layer moved to separate fn with more sensible dilation/output_stride calc * drop path rate decay easy to impl with refactored block creation loops * fix dilation + blur pool combo	4 years ago
Ross Wightman	a66df5fb91	More model feature extraction support, start to deprecate senet.py, dilations added to regnet, add proper aligned xception	4 years ago
Ross Wightman	7729f40dca	Fix another bug, update all gluon resnet models to use new creation method (feature support)	4 years ago
Ross Wightman	d0113f9cdb	Fix a few issues that came up in tests	4 years ago
Ross Wightman	d23a2697d0	Working on feature extraction, interfaces refined, a number of models working, some in progress.	4 years ago
Ross Wightman	eb7653614f	Monster commit, activation refactor, VoVNet, norm_act improvements, more ... * refactor activations into basic PyTorch, jit scripted, and memory efficient custom auto * implement hard-mish, better grad for hard-swish * add initial VovNet V1/V2 impl, fix #151 * VovNet and DenseNet first models to use NormAct layers (support BatchNormAct2d, EvoNorm, InplaceIABN) * Wrap IABN for any models that use it * make more models torchscript compatible (DPN, PNasNet, Res2Net, SelecSLS) and add tests	4 years ago
Vyacheslav Shults	a7ebe09029	Replace all None by nn.Identity() in all models reset_classifier when False-values num_classes is given. ... Make small code refactoring	5 years ago
Ross Wightman	2681a8d618	Final blurpool2d cleanup and add resnetblur50 weights, match tresnet Downsample arg order to BlurPool2d for interop	5 years ago
Ross Wightman	9590f301a9	Merge branch 'blur' of https://github.com/VRandme/pytorch-image-models into VRandme-blur	5 years ago
Ross Wightman	0834fbc01c	Move pruned model adapt strings to separate txt files. A few minor formatting alignment tweaks.	5 years ago
AFLALO, Jonathan Isaac	07f19dd699	added eca resnet	5 years ago
Chris Ha	06a50a94a8	Fix minor typos in create_attn.py and resnet.py ... 'eca'->'ceca' and doest not-> does not	5 years ago
Ross Wightman	6cdeca24a3	Some cleanup and fixes for initial BlurPool impl. Still some testing and tweaks to go...	5 years ago
Chris Ha	acd1b6cccd	Implement Functional Blur on resnet.py ... 1. add ResNet argument blur='' 2. implement blur for maxpool and strided convs in downsampling blocks	5 years ago
Ross Wightman	5a16c533ff	Add better resnext50_32x4d weights trained by andravin	5 years ago
Ross Wightman	f1d5f8a6c4	Update comments for Selective Kernel and DropBlock/Path impl, add skresnet34 weights	5 years ago
Ross Wightman	f902bcd54c	Layer refactoring continues, ResNet downsample rewrite for proper dilation in 3x3 and avg_pool cases ... * select_conv2d -> create_conv2d * added create_attn to create attention module from string/bool/module * factor padding helpers into own file, use in both conv2d_same and avg_pool2d_same * add some more test eca resnet variants * minor tweaks, naming, comments, consistency	5 years ago
Ross Wightman	13746a33fc	Big move, layer modules and fn to timm/models/layers	5 years ago
Ross Wightman	f54612f648	Merge branch 'select_kernel' into attention	5 years ago
Ross Wightman	4defbbbaa8	Fix module name mistake, start layers sub-package	5 years ago
Chris Ha	db91ba053b	EcaModule(CamelCase) ... CamelCased EcaModule. Renamed all instances of ecalayer to EcaModule. eca_module.py->EcaModule.py	5 years ago
Chris Ha	f87fcd7e88	Implement Eca modules ... implement ECA module by 1. adopting original eca_module.py into models folder 2. adding use_eca layer besides every instance of SE layer	5 years ago
Ross Wightman	a9d2424fd1	Add separate zero_init_last_bn function to support more block variety without a mess	5 years ago
Ross Wightman	9f11b4e8a2	Add ConvBnAct layer to parallel integrated SelectKernelConv, add support for DropPath and DropBlock to ResNet base and SK blocks	5 years ago
Ross Wightman	cefc9b7761	Move SelectKernelConv to conv2d_layers and more ... * always apply attention in SelectKernelConv, leave MixedConv for no attention alternative * make MixedConv torchscript compatible * refactor first/previous dilation name to make more sense in ResNet* networks	5 years ago
Ross Wightman	58e28dc7e7	Move Selective Kernel blocks/convs to their own sknet.py file	5 years ago
Ross Wightman	a93bae6dc5	A SelectiveKernelBasicBlock for more experiments	5 years ago
Ross Wightman	ad087b4b17	Missed bias=False in selection conv	5 years ago
Ross Wightman	c8b3d6b81a	Initial impl of Selective Kernel Networks. Very much a WIP.	5 years ago
Ross Wightman	12dbc74742	New ResNet50 JSD + RandAugment weights	5 years ago
Ross Wightman	2f41905ba5	Update ResNet50 weights to AuxMix trained 78.994 top-1. A few commentes re 'tiered_narrow' tn variant.	5 years ago