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Fix SparseDenseCwise's broadcasting issue

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This fix tries to address the issue raised in 24072.
In `sparse_dense_cwise_mul/add` operations the broadcasting
only support dense to sparse, though the validation was not
captured.

This fix fixes the validation in SparseDenseBinaryOpShared
so that error could be thrown correctly.

This fix fixes 24072.

Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
This commit is contained in:
Yong Tang 2018-12-01 20:58:09 +00:00
parent f23efde510
commit 8584f21392
1 changed files with 3 additions and 4 deletions
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7
tensorflow/core/kernels/sparse_dense_binary_op_shared.cc
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@ -88,12 +88,11 @@ class SparseDenseBinaryOpShared : public OpKernel {
const auto rhs_dims = BCast::FromShape(dense_t->shape());
BCast b(lhs_dims, rhs_dims, false); // false for keeping the same num dims.
// True iff (size(lhs) > size(rhs)), or (sizes equal, lhs cwise rhs).
// True iff (size(lhs) >= size(rhs)) and all dims in lhs is smaller or equal to dims in rhs (from right to left).
auto VecGreaterEq = [](ArraySlice<int64> lhs, ArraySlice<int64> rhs) {
if (lhs.size() > rhs.size()) return true;
if (lhs.size() < rhs.size()) return false;
for (size_t i = 0; i < lhs.size(); ++i) {
if (lhs[i] < rhs[i]) return false;
for (size_t i = 0; i < rhs.size(); ++i) {
if (lhs[lhs.size() - 1 - i] < rhs[rhs.size() - 1 - i]) return false;
}
return true;
};