mirror of https://github.com/hpcaitech/ColossalAI
54 lines
1.6 KiB
Python
54 lines
1.6 KiB
Python
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, tmm.beit.beit_base_patch16_224, tmm.cait.cait_s24_224, tmm.efficientnet.efficientnetv2_m,
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tmm.resmlp_12_224, tmm.vision_transformer.vit_base_patch16_224, tmm.deit_base_distilled_patch16_224,
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tmm.convnext.convnext_base, tmm.vgg.vgg11, tmm.dpn.dpn68, tmm.densenet.densenet121, 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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graph = 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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graph = 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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