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Fix nxp unittests #15384

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Merged
merged 2 commits into from
Oct 24, 2025
Merged

Fix nxp unittests #15384

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08280cc
Fix nxp unittests
larryliu0820 Oct 24, 2025
5455390
Fix
larryliu0820 Oct 24, 2025
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18 changes: 10 additions & 8 deletions backends/nxp/tests/test_batch_norm_fusion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -105,10 +105,11 @@ def test_batch_norm_conv_fusing(bias: bool, input_shape: list[int]):
og_nodes = list(program.graph.nodes)
transformed_nodes = list(graph_module_out.graph.nodes)

assert len(og_nodes) == (11 if bias else 10)
assert og_nodes[9 if bias else 8].target.__name__ == "batch_norm.default"
assert any(
node.op == "call_function" and node.target.__name__ == "batch_norm.default"
for node in og_nodes
)

assert len(transformed_nodes) == 5
assert not any(
node.op == "call_function" and "batch_norm" in node.target.__name__
for node in transformed_nodes
Expand All @@ -118,7 +119,7 @@ def test_batch_norm_conv_fusing(bias: bool, input_shape: list[int]):
input_data = torch.randn(input_shape, dtype=torch.float32)
out1 = og_module(input_data).detach().numpy()
out2 = graph_module_out(input_data).detach().numpy()
assert np.allclose(out1, out2, atol=3.0e-7)
torch.testing.assert_close(out1, out2)


@pytest.mark.parametrize(
Expand All @@ -139,10 +140,11 @@ def test_batch_norm_linear_fusing(bias: bool):
og_nodes = list(og_module.graph.nodes)
transformed_nodes = list(graph_module_out.graph.nodes)

assert len(og_nodes) == (11 if bias else 10)
assert og_nodes[8 if bias else 7].target.__name__ == "linear.default"
assert any(
node.op == "call_function" and node.target.__name__ == "linear.default"
for node in og_nodes
)

assert len(transformed_nodes) == 5
assert not any(
node.op == "call_function" and "batch_norm" in node.target.__name__
for node in transformed_nodes
Expand All @@ -152,7 +154,7 @@ def test_batch_norm_linear_fusing(bias: bool):
input_data = torch.randn(input_shape, dtype=torch.float32)
out1 = og_module(input_data).detach().numpy()
out2 = graph_module_out(input_data).detach().numpy()
assert np.allclose(out1, out2, atol=1.2e-7)
torch.testing.assert_close(out1, out2)


@pytest.mark.parametrize(
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