jcf94 commented on a change in pull request #8607:
URL: https://github.com/apache/tvm/pull/8607#discussion_r680612911
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File path: python/tvm/relay/frontend/onnx.py
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@@ -770,10 +770,8 @@ def flatten_to_nd(x, x_shape, nd=3):
# Convert a and b into 3 dimensional tensors.
a = flatten_to_nd(inputs[0], a_shape, 3)
b = flatten_to_nd(inputs[1], b_shape, 3)
- # Transpose matrix dimensions of b.
- b = _op.transpose(b, [0, 2, 1])
# Perform a batch matmul.
- output = _op.nn.batch_matmul(a, b)
+ output = _op.nn.batch_matmul(a, b, transpose_b=False)
Review comment:
Thanks! @ymwangg
Just a little concern about changing the default behavior of framework
frontend, since currently the default topi schedule support for NN format is
not as strong as the original NT one.
This may cause confusions to those who have used onnx frontend before or who
is using onnx frontend now.
To give an example, I've added an extra config to TensorFlow frontend which
uses the NT format by default but provides an option to use the normal format.
I think that would be better before we have prepared a strong enough topi.
p.s.: You see, I've also kept the default layout for `nn.batch_matmul` to be
the original NT.
https://github.com/apache/tvm/blob/765397295410c7ec15a5df8be0df05c2e18d5ea0/python/tvm/relay/frontend/tensorflow_ops.py#L1191-L1199
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