ANSHUMAN87 commented on a change in pull request #7267:
URL: https://github.com/apache/tvm/pull/7267#discussion_r563293629
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File path: python/tvm/relay/frontend/tensorflow.py
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@@ -941,9 +934,48 @@ def _impl(inputs, attr, params, mod):
(values_tensor, (rows, cols)),
shape=tuple(dense_shape_tensor.tolist())
)
+ # As per tensorflow implementation, we have 4 possible input
combination
+ # and the first input(A) is always sparse and second input(B) is
always dense.
+ # Case 1: A , B , adjoint_a=False, adjoint_b=False --> A * B
+ # Case 2: A , B , adjoint_a=True, adjoint_b=False --> A.T * B
+ # Case 3: A , B , adjoint_a=False, adjoint_b=True --> A * B.T
+ # Case 4: A , B , adjoint_a=True, adjoint_b=True --> (A.T * B.T).T
+ #
+ # Topi implementation for sparse_dense(matmul) has 2 possible input
+ # combination where first input(A) is always dense
+ # and second input(B) is always sparse.
+ # Case 1: A , B, sparse_lhs = False --> A * B.T
+ # Case 2: A , B, sparse_lhs = True --> B * A.T
+ #
+ # The mapping would be as below:
+ # TF Case 1: A , B , adjoint_a=False, adjoint_b=False
Review comment:
This part is already explained in the above comment section, it is
implicit. I think it is okay.
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