rohanmukh commented on a change in pull request #8251:
URL: https://github.com/apache/tvm/pull/8251#discussion_r652209025
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File path: python/tvm/relay/frontend/tensorflow_ops.py
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@@ -1162,6 +1163,9 @@ def _impl(inputs, attr, params, mod):
adj_x = attr["adj_x"]
adj_y = attr["adj_y"]
input_x = _op.transpose(input_x, axes=[0, 2, 1]) if adj_x else input_x
+ shape_y = _infer_shape(input_y, mod)
+ if len(shape_y) < 3:
+ input_y = _op.reshape(input_y, (1, orig_shape_y[-2],
orig_shape_y[-1]))
Review comment:
Thanks @comaniac . It is important for cases where `ndim=len(shape_x)`
is <=3. I have test cases that fail without this line. Like
`_test_batch_matmul((1, 8, 64), (64, 1), "float32", False, False)`. However
the case that you mentioned can also happen for certain input configurations. I
refactored the logic to avoid that.
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