83487e2a0d
Lower max backward size for tests.
4 years ago
bfc72f75d3
Expand scope of testing for non-std vision transformer / mlp models. Some related cleanup and create fn cleanup for all vision transformer and mlp models. More CoaT weights.
4 years ago
f45de37690
Merge branch 'master' into levit_visformer_rednet
4 years ago
306c86b668
Merge branch 'convit' of https://github.com/amaarora/pytorch-image-models into amaarora-convit
4 years ago
50d6aab0ef
Add convit to non-std filters as vit_
4 years ago
1633317489
update tests and exclude convit_base
4 years ago
d046498e0b
update test_models.py
4 years ago
6d81374b88
Update tests for new mlp models
4 years ago
ecc7552c5c
Add levit, levit_c, and visformer model defs. Largely untested and not finished cleanup.
4 years ago
d45e50b9db
Update test for cait 448x448 model
4 years ago
5fcddb96a8
Merge branch 'master' into cait
4 years ago
2d8b09fe8b
Add official pretrained weights to MLP-Mixer, complete model cfgs.
4 years ago
1daa15ecc3
Initial Cait commit. Still some cleanup to do.
4 years ago
67d0665b46
Post ResNet-RS merge cleanup. Add weight urls, adjust train/test/crop pct.
4 years ago
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
06841427cd
Add files via upload
4 years ago
d793deb51a
Merge branch 'master' of https://github.com/iamhankai/pytorch-image-models into iamhankai-master
4 years ago
277a9a78f9
Fix unit test filter update.
4 years ago
858728799c
Update README again. Add 101x3 BiT-M model to CI ignore since it's starting to fail in GitHub runners.
4 years ago
f606c45c38
Add Swin Transformer models from https://github.com/microsoft/Swin-Transformer
4 years ago
de445e7827
Add GhostNet
4 years ago
16f7aa9f54
Add default_cfg options for min_input_size / fixed_input_size, queries in model registry, and use for testing self-attn models
4 years ago
2b49ab7a36
Fix ResNetV2 pretrained classifier issue. Fixes #540
4 years ago
0dfc5a66bb
Add PiT model from https://github.com/naver-ai/pit
4 years ago
51febd869b
Small tweak to tests for tnt model, reorder model imports.
4 years ago
809271b0f3
Update test_models.py
4 years ago
317ea3e599
Tweak NFNet, ResNetV2, RexNet feature extraction, use pre-act features for simplicty. Update tests for pytorch 1.8. 0.4.5 version bump.
4 years ago
da4839530c
Fix test model filter to include dm_ variants that break GitHub CI limits
4 years ago
0d253e2c5e
Fix issue with nfnet tests, bit more cleanup.
4 years ago
9811e229f7
Fix regression in models with 1001 class pretrained weights. Improve batchnorm arg and BatchNormAct layer handling in several models.
4 years ago
55f7dfa9ea
Refactor vision_transformer entrpy fns, add pos embedding resize support for fine tuning, add some deit models for testing
4 years ago
0a1668f63e
Update tests
4 years ago
20516abc18
Fix some broken tests for ResNetV2 BiT models
4 years ago
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
da6cd2cc1f
Fix regression for pretrained classifier loading when using entrypt functions directly
4 years ago
be53107e8a
Update README, ensure vit excluded from all tests (not ready)
4 years ago
f31933cb37
Initial Vision Transformer impl w/ patch and hybrid variants. Refactor tuple helpers.
4 years ago
90a01f47d1
hrnet features_only pretrained weight loading issue. Fix #232 .
4 years ago
470220b1f4
Fix MobileNetV3 crash with global_pool='', output consistent with other models but not equivalent due to efficient head.
4 years ago
b1b6e7c361
Fix a few more issues related to #216 w/ TResNet (space2depth) and FP16 weights in wide resnets. Also don't completely dump pretrained weights in in_chans != 1 or 3 cases.
4 years ago
e717250ed4
remove comments
4 years ago
f6b56602f9
fix test_model_default_cfgs
4 years ago
d5145fa4d5
Change default_cfg names for senet to include the legacy and match model names
4 years ago
b1f1a54de9
More uniform treatment of classifiers across all models, reduce code duplication.
4 years ago
d72ddafe56
Fix some checkpoint / model str regressions
4 years ago
ea58e0bc16
Disable big models for MacOS test since they are starting to fail frequently.
4 years ago
7ba5a384d3
Add ReXNet w/ remapped weights, feature support
4 years ago
c9d54bc1c3
Add HRNet feature extraction, fix senet type, lower feature testing res to 96x96
4 years ago
2ac663f340
Add feature support to legacy senets, add 32x32 resnext models to exclude list for feature testing.
4 years ago
4e61c6a12d
Cleanup, refactoring of Feature extraction code, add tests, fix tests, non hook feature extraction working with torchscript
4 years ago
9eba134d79
More models supporting feature extraction, xception, gluon_xception, inception_v3, inception_v4, pnasnet, nasnet, dla. Fix DLA unused projection params.
4 years ago
151679c2f1
Add custom grad tests, fix cut & paste error with hard_mish ME, add a few more pytorch act fns to factory
4 years ago
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
5 years ago
4d13db538f
Add x48d ResNext101s to test exclude for ubuntu
5 years ago
4212cd3b9f
Another attempt at getting Ubuntu test runner to work
5 years ago
20329f2630
Bring down test resolutions to see if we can at least do a fwd on the L2 models
5 years ago
3873ea710e
Minor test change
5 years ago
afb6bd0669
Add backward and default_cfg tests and fix a few issues found. Fix #153
5 years ago
5bd1ad13e7
Refactor test indent
5 years ago
9cc289f18c
Exclude EfficientNet-L2 models from test
5 years ago
e545bb9401
Update test_inference.py
...
Not six min
5 years ago
305a2db705
Update test_inference.py
...
Make the timeout 5-min for now, see if we can get a pass...
5 years ago
69d725c9fe
Basic forward pass test for all registered models
5 years ago
Ross Wightman