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Signed-off-by: Justin Chu <[email protected]>
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tests/function_libs/torch_lib/extra_opinfo.py

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@@ -48,10 +48,10 @@ def sample_inputs_bilinear(op_info, device, dtype, requires_grad, **kwargs):
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# Test cases: (batch_size, in1_features, in2_features, out_features)
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cases = [
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(2, 3, 4, 5), # Basic case
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(1, 2, 2, 1), # Minimal case
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(3, 5, 7, 4), # Different dimensions
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(2, 1, 1, 3), # Single input features
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(2, 3, 4, 5), # Basic case
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(1, 2, 2, 1), # Minimal case
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(3, 5, 7, 4), # Different dimensions
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(2, 1, 1, 3), # Single input features
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]
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for batch_size, in1_features, in2_features, out_features in cases:

tests/function_libs/torch_lib/ops_test_data.py

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@@ -657,7 +657,9 @@ def _where_input_wrangler(
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),
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TorchLibOpInfo("baddbmm", core_ops.aten_baddbmm, tolerance={torch.float16: (1e-3, 1e-2)}),
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TorchLibOpInfo("bernoulli", core_ops.aten_bernoulli, nondeterministic=True),
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TorchLibOpInfo("bilinear", core_ops.aten_bilinear, tolerance={torch.float32: (1e-4, 1e-4)}),
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TorchLibOpInfo(
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"bilinear", core_ops.aten_bilinear, tolerance={torch.float32: (2e-5, 2e-5)}
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),
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TorchLibOpInfo(
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# This string is a unique ID. In extra_opinfo.py, we
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# also define test data for this ID with

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