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56 lines
1.8 KiB
56 lines
1.8 KiB
import pytest
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import torch
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import torch.nn.functional as F
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import torchvision.models as tm
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from packaging import version
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from tests.test_analyzer.test_fx.zoo import tm_models, tmm_models
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try:
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from colossalai._analyzer._subclasses import MetaTensorMode, flop_count
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except:
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pass
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@pytest.mark.skipif(version.parse(torch.__version__) < version.parse("1.12.0"), reason="torch version < 12")
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@pytest.mark.parametrize("m", tm_models + tmm_models)
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def test_flop_count_module(m):
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x = torch.rand(2, 3, 224, 224)
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with MetaTensorMode(): # save time for testing
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module = m()
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rs_fwd, rs_bwd = flop_count(module, x, verbose=True)
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assert rs_fwd > 0, f"fwd flop count of {m.__name__} is {rs_fwd}"
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assert rs_bwd > 0, f"bwd flop count of {m.__name__} is {rs_bwd}"
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odd_cases = [
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(F.relu, (torch.rand(2, 3, 224, 224, requires_grad=True),), {"inplace": True}),
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(
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F.max_pool2d,
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(torch.rand(2, 3, 224, 224, requires_grad=True),),
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{"kernel_size": 3, "stride": 2, "padding": 1, "dilation": 2},
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),
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(
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torch.where,
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(
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torch.rand(2, 3, 224, 224) > 0.5,
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torch.rand(2, 3, 224, 224, requires_grad=True),
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torch.rand(2, 3, 224, 224, requires_grad=True),
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),
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{},
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),
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]
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@pytest.mark.skipif(version.parse(torch.__version__) < version.parse("1.12.0"), reason="torch version < 12")
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@pytest.mark.parametrize("func, args, kwargs", odd_cases)
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def test_flop_count_function(func, args, kwargs):
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rs_fwd, rs_bwd = flop_count(func, *args, **kwargs, verbose=True)
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assert rs_fwd > 0, f"fwd flop count of {func.__name__} is {rs_fwd}"
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assert rs_bwd > 0, f"bwd flop count of {func.__name__} is {rs_bwd}"
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if __name__ == "__main__":
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test_flop_count_module(tm.resnet18)
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test_flop_count_function(F.relu, (torch.rand(2, 3, 224, 224, requires_grad=True),), {"inplace": True})
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