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Fabio Ferreira
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DCO Remediation Commit for Fabio Ferreira <[email protected]>
I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: de2b6bd I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 66edcb5 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: feefcaa I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: f673ca1 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 69540ff I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 42ec757 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: a2e8474 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 4c4782e I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 515c659 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: da5a3a4 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 43dec88 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 84c0f48 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 5805515 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 1aa8e3c I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: 447d9f2 I, Fabio Ferreira <[email protected]>, hereby add my Signed-off-by to this commit: b20a19e Signed-off-by: Fabio Ferreira <[email protected]>
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tests/networks/nets/test_checkpointunet.py

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@@ -124,13 +124,7 @@
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class TestCheckpointUNet(unittest.TestCase):
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@parameterized.expand(CASES)
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def test_shape(self, input_param, input_shape, expected_shape):
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"""Validate CheckpointUNet output shapes across configurations.
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Args:
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input_param: Mapping of constructor kwargs for the network under test.
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input_shape: Shape tuple for the synthetic input tensor.
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expected_shape: Expected output tensor shape.
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"""
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"""Validate CheckpointUNet output shapes across configurations."""
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net = CheckpointUNet(**input_param).to(device)
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with eval_mode(net):
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result = net.forward(torch.randn(input_shape).to(device))

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