mirror of https://github.com/hpcaitech/ColossalAI
50 lines
1.6 KiB
Python
50 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 .zoo import tm_models, tmm_models
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try:
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from colossalai._analyzer._subclasses import MetaTensorMode
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from colossalai._analyzer.fx import symbolic_profile, symbolic_trace
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except:
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pass
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def _check_gm_validity(gm: torch.fx.GraphModule):
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for node in gm.graph.nodes:
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assert len(node.meta['info'].global_ctx), f'In {gm.__class__.__name__}, {node} has empty global context.'
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@pytest.mark.skipif(torch.__version__ < '1.12.0', reason='torch version < 12')
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@pytest.mark.parametrize('m', tm_models)
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def test_torchvision_profile(m, verbose=False, bias_addition_split=False):
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with MetaTensorMode():
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model = m()
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data = torch.rand(8, 3, 224, 224)
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meta_args = {
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"x": data,
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}
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gm = symbolic_trace(model, meta_args=meta_args, bias_addition_split=bias_addition_split)
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symbolic_profile(gm, data, verbose=verbose)
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_check_gm_validity(gm)
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@pytest.mark.skipif(torch.__version__ < '1.12.0', reason='torch version < 12')
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@pytest.mark.parametrize('m', tmm_models)
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def test_timm_profile(m, verbose=False, bias_addition_split=False):
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with MetaTensorMode():
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model = m()
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data = torch.rand(8, 3, 224, 224)
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meta_args = {
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"x": data,
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}
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gm = symbolic_trace(model, meta_args=meta_args, bias_addition_split=bias_addition_split)
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symbolic_profile(gm, data, verbose=verbose)
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_check_gm_validity(gm)
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if __name__ == "__main__":
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test_torchvision_profile(tm.vit_b_16, verbose=True, bias_addition_split=False)
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test_timm_profile(tmm.gmlp_b16_224, verbose=True, bias_addition_split=False)
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