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Fix type parse error about AdaptiveMaxPool #15016

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merged 2 commits into from
Jun 4, 2023
Merged

Fix type parse error about AdaptiveMaxPool #15016

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5a00310
fix type parse error about max_pool
jikechao Jun 3, 2023
f8cec26
add new test case to caputure bug in adaptive_max_pool
jikechao Jun 3, 2023
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4 changes: 4 additions & 0 deletions python/tvm/relay/frontend/pytorch.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1124,6 +1124,10 @@ def func(x):
def adaptive_max_pool(self, op, inputs, input_types):
data = inputs[0]
output_size = inputs[1]
for i, item in enumerate(output_size):
if isinstance(item, tvm.relay.expr.Constant):
# convert Constant to int
output_size[i] = item.data.numpy()[()]
# returns dummy indices too
return op(data, output_size=output_size), None

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7 changes: 7 additions & 0 deletions tests/python/frontend/pytorch/test_forward.py
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Expand Up @@ -886,6 +886,8 @@ def test_forward_adaptive_avgpool():

input_data = torch.rand([1, 3, 5, 6]).float()
verify_model(torch.nn.AdaptiveAvgPool2d([3, None]).eval(), input_data=input_data)
input_data = torch.rand([1, 1, 3, 5, 6]).float()
verify_model(torch.nn.AdaptiveAvgPool3d([3, None, None]).eval(), input_data=input_data)


@tvm.testing.uses_gpu
Expand All @@ -901,6 +903,11 @@ def test_forward_adaptive_maxpool():
verify_model(torch.nn.AdaptiveMaxPool1d([1]).eval(), input_data=input_data)
verify_model(torch.nn.AdaptiveMaxPool1d([5]).eval(), input_data=input_data)

input_data = torch.rand([1, 3, 5, 6]).float()
verify_model(torch.nn.AdaptiveMaxPool2d([3, None]).eval(), input_data=input_data)
input_data = torch.rand([1, 1, 3, 5, 6]).float()
verify_model(torch.nn.AdaptiveMaxPool3d([3, None, None]).eval(), input_data=input_data)


@tvm.testing.uses_gpu
def test_forward_maxpool2d():
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