diff options
| author |  Josh Levenberg <josh11b@tensorflow.org> | 2016-01-07 18:37:54 -0800 |
|---|---|---|
| committer |  Vijay Vasudevan <vrv@google.com> | 2016-01-07 18:37:54 -0800 |
| commit | 02dff6d0d838397860b6ff5256413b54da482996 (patch) | |
| tree | 6c4c6614ed9b365b86016003a956bd8d8ac6bda6 /tensorflow/core/kernels/concat_op.cc | |
| parent | d38fecedf54d405270377a096f58413101068792 (diff) | |
Fix bug where attrs with values that are the empty list
were not being properly set via the Python API.
Change: 111635679
Diffstat (limited to 'tensorflow/core/kernels/concat_op.cc')
| -rw-r--r-- | tensorflow/core/kernels/concat_op.cc | 12 |
1 files changed, 6 insertions, 6 deletions
diff --git a/tensorflow/core/kernels/concat_op.cc b/tensorflow/core/kernels/concat_op.cc index 4e2ddc2954..db4ae1f18e 100644 --- a/tensorflow/core/kernels/concat_op.cc +++ b/tensorflow/core/kernels/concat_op.cc @@ -45,7 +45,7 @@ class ConcatOp : public OpKernel { const Tensor* concat_dim_tensor; OP_REQUIRES_OK(c, c->input("concat_dim", &concat_dim_tensor)); OP_REQUIRES( - c, TensorShapeUtils::IsLegacyScalar(concat_dim_tensor->shape()), + c, IsLegacyScalar(concat_dim_tensor->shape()), errors::InvalidArgument( "Concat dim tensor should be a scalar integer, but got shape ", concat_dim_tensor->shape().DebugString())); @@ -57,7 +57,7 @@ class ConcatOp : public OpKernel { const TensorShape& input_shape = values[0].shape(); OP_REQUIRES( c, (0 <= concat_dim && concat_dim < input_dims) || - (kAllowLegacyScalars && concat_dim == 0), + (allow_legacy_scalars() && concat_dim == 0), errors::InvalidArgument( "ConcatOp : Expected concatenating dimensions in the range [", 0, ", ", input_dims, "), but got ", concat_dim)); @@ -74,10 +74,10 @@ class ConcatOp : public OpKernel { inputs_flat_dim0 *= input_shape.dim_size(d); } int output_concat_dim = 0; - const bool input_is_scalar = TensorShapeUtils::IsLegacyScalar(input_shape); + const bool input_is_scalar = IsLegacyScalar(input_shape); for (int i = 0; i < N; ++i) { const auto in = values[i]; - const bool in_is_scalar = TensorShapeUtils::IsLegacyScalar(in.shape()); + const bool in_is_scalar = IsLegacyScalar(in.shape()); OP_REQUIRES( c, in.dims() == input_dims || (input_is_scalar && in_is_scalar), errors::InvalidArgument( @@ -100,12 +100,12 @@ class ConcatOp : public OpKernel { inputs_flat.emplace_back(new typename TTypes<T, 2>::ConstMatrix( in.shaped<T, 2>({inputs_flat_dim0, inputs_flat_dim1}))); } - // TODO(irving): Remove check once !kAllowLegacyScalars + // TODO(irving): Remove check once !allow_legacy_scalars(). output_concat_dim += in.dims() > 0 ? in.dim_size(concat_dim) : 1; } TensorShape output_shape(input_shape); - // TODO(irving): Remove rank 0 case once !kAllowLegacyScalars + // TODO(irving): Remove rank 0 case once !allow_legacy_scalars(). if (output_shape.dims() == 0) { output_shape.AddDim(output_concat_dim); } else { |