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Remove the limitation of int max for dim_size in SparseDenseCwise ops

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This fix tries to address the issue raised in 25701 where
the dim_size in SparseDenseCwise ops was set to
`std::numeric_limits<int>::max`. The restriction is likely unnecesary,
due to historical reasons. This fix remove this limitation.

This fix fixes 25701.

Signed-off-by: Yong Tang <yong.tang.github@outlook.com>
This commit is contained in:
Yong Tang 2019-02-12 21:02:12 +00:00
parent b85cb440e2
commit 40e1acd4fc
1 changed files with 1 additions and 4 deletions
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5
tensorflow/core/kernels/sparse_dense_binary_op_shared.cc
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@ -78,9 +78,6 @@ class SparseDenseBinaryOpShared : public OpKernel {
"but received shapes: ",
values_t->shape().DebugString(), " and ",
shape_t->shape().DebugString()));
OP_REQUIRES(ctx, indices_t->dim_size(0) < std::numeric_limits<int>::max(),
errors::InvalidArgument(
"Number of non-zero elements exceeds int32 range"));
const auto indices_mat = indices_t->matrix<int64>();
const auto shape_vec = shape_t->vec<int64>();
@ -106,7 +103,7 @@ class SparseDenseBinaryOpShared : public OpKernel {
Tensor *output_values = nullptr;
Tensor dense_gathered;
const int nnz = static_cast<int>(indices_t->dim_size(0));
const int64 nnz = indices_t->dim_size(0);
OP_REQUIRES_OK(ctx,
ctx->allocate_output(0, TensorShape({nnz}), &output_values));
OP_REQUIRES_OK(