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