diff options
Diffstat (limited to 'tensorflow/core/kernels/linalg_ops_common.cc')
| -rw-r--r-- | tensorflow/core/kernels/linalg_ops_common.cc | 32 |
1 files changed, 15 insertions, 17 deletions
diff --git a/tensorflow/core/kernels/linalg_ops_common.cc b/tensorflow/core/kernels/linalg_ops_common.cc index a38ddf76eb..155d9d1084 100644 --- a/tensorflow/core/kernels/linalg_ops_common.cc +++ b/tensorflow/core/kernels/linalg_ops_common.cc @@ -15,6 +15,8 @@ limitations under the License. #include "tensorflow/core/kernels/linalg_ops_common.h" +#include <utility> + #include "third_party/eigen3/Eigen/Core" #include "tensorflow/core/framework/device_base.h" #include "tensorflow/core/framework/kernel_def_builder.h" @@ -153,10 +155,9 @@ void LinearAlgebraOp<Scalar>::AnalyzeInputs(OpKernelContext* context, const int col_dimension = input_rank - 1; const int64 num_rows = in.dim_size(row_dimension); const int64 num_cols = in.dim_size(col_dimension); - // TODO(rmlarsen): Use emplace_back when it is added to InlinedVector. Same - // in several places below. - input_matrix_shapes->push_back(TensorShape({num_rows, num_cols})); - inputs->push_back(&in); + input_matrix_shapes->emplace_back( + std::initializer_list<int64>({num_rows, num_cols})); + inputs->emplace_back(&in); } // Have the derived class validate that the inputs are as expected. ValidateInputMatrixShapes(context, *input_matrix_shapes); @@ -198,9 +199,7 @@ void LinearAlgebraOp<Scalar>::PrepareOutputs( // concatenated with the output_matrix_shape (if the output is not // scalar). output_tensor_shape = batch_shape; - for (int dim = 0; dim < output_matrix_shape.dims(); ++dim) { - output_tensor_shape.AddDim(output_matrix_shape.dim_size(dim)); - } + output_tensor_shape.AppendShape(output_matrix_shape); } Tensor* out = nullptr; // See if there is an input buffer we can reuse for this output. @@ -219,7 +218,7 @@ void LinearAlgebraOp<Scalar>::PrepareOutputs( OP_REQUIRES_OK(context, context->allocate_output( output_idx, output_tensor_shape, &out)); } - outputs->push_back(out); + outputs->emplace_back(out); } } @@ -232,11 +231,10 @@ void LinearAlgebraOp<Scalar>::ComputeTensorSlice( for (size_t i = 0; i < inputs.size(); ++i) { // TODO(kalakris): Handle alignment if possible. Eigen::Map is // unaligned by default. - matrix_inputs.push_back( - ConstMatrixMap(inputs[i]->flat<Scalar>().data() + - matrix_index * input_matrix_shapes[i].num_elements(), - input_matrix_shapes[i].dim_size(0), - input_matrix_shapes[i].dim_size(1))); + matrix_inputs.emplace_back( + inputs[i]->flat<Scalar>().data() + + matrix_index * input_matrix_shapes[i].num_elements(), + input_matrix_shapes[i].dim_size(0), input_matrix_shapes[i].dim_size(1)); } MatrixMaps matrix_outputs; @@ -248,10 +246,10 @@ void LinearAlgebraOp<Scalar>::ComputeTensorSlice( int num_output_cols = output_matrix_shapes[i].dims() == 2 ? output_matrix_shapes[i].dim_size(1) : 1; - matrix_outputs.push_back( - MatrixMap(outputs[i]->flat<Scalar>().data() + - matrix_index * output_matrix_shapes[i].num_elements(), - num_output_rows, num_output_cols)); + matrix_outputs.emplace_back( + outputs[i]->flat<Scalar>().data() + + matrix_index * output_matrix_shapes[i].num_elements(), + num_output_rows, num_output_cols); } ComputeMatrix(context, matrix_inputs, &matrix_outputs); } |