import pytest import timm.models as tmm import torch import torchvision.models as tm from colossalai.fx._compatibility import is_compatible_with_meta if is_compatible_with_meta(): from colossalai.fx import meta_trace from colossalai.testing import clear_cache_before_run tm_models = [ tm.vgg11, tm.resnet18, tm.densenet121, tm.mobilenet_v3_small, tm.resnext50_32x4d, tm.wide_resnet50_2, tm.regnet_x_16gf, tm.mnasnet0_5, tm.efficientnet_b0, ] tmm_models = [ tmm.resnest.resnest50d, tmm.beit.beit_base_patch16_224, tmm.cait.cait_s24_224, tmm.efficientnet.efficientnetv2_m, tmm.resmlp_12_224, tmm.vision_transformer.vit_base_patch16_224, tmm.deit_base_distilled_patch16_224, tmm.convnext.convnext_base, tmm.vgg.vgg11, tmm.dpn.dpn68, tmm.densenet.densenet121, tmm.rexnet.rexnet_100, tmm.swin_transformer.swin_base_patch4_window7_224 ] @pytest.mark.skipif(not is_compatible_with_meta(), reason='torch version is lower than 1.12.0') @clear_cache_before_run() def test_torchvision_models_trace(): for m in tm_models: model = m() data = torch.rand(1000, 3, 224, 224, device='meta') graph = meta_trace(model, torch.device('cpu'), data) @pytest.mark.skipif(not is_compatible_with_meta(), reason='torch version is lower than 1.12.0') @clear_cache_before_run() def test_timm_models_trace(): for m in tmm_models: model = m() data = torch.rand(1000, 3, 224, 224, device='meta') graph = meta_trace(model, torch.device('cpu'), data) if __name__ == '__main__': test_torchvision_models_trace() test_timm_models_trace()