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@torch_op("aten::linear") |
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def aten_linear(input: TFloat, weight: TFloat) -> TFloat: |
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"""linear(Tensor input, Tensor weight, Tensor? bias=None) -> Tensor""" |
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# NOTE: The symbolic function in torch.onnx also uses Gemm in certain cases |
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# Optimizers may consider this path and replace it with Gemm |
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# We do not use Gemm here because input can have batch dimensions, which Gemm does not support |
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weight_transposed = op.Transpose(weight, perm=[1, 0]) |
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return op.MatMul(input, weight_transposed) |
as it is decomposed by pytorch to Gemm and is required for model accuracy.
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onnxscript/onnxscript/function_libs/torch_lib/ops/nn.py
Lines 825 to 833 in acda045