tensorflow::
#include <sparse_ops.h>
Reshapes a SparseTensor to represent values in a new dense shape.
Summary
This operation has the same semantics as reshape on the represented dense tensor. The input_indices are recomputed based on the requested new_shape.
If one component of new_shape is the special value -1, the size of that dimension is computed so that the total dense size remains constant. At most one component of new_shape can be -1. The number of dense elements implied by new_shape must be the same as the number of dense elements originally implied by input_shape.
Reshaping does not affect the order of values in the SparseTensor.
If the input tensor has rank R_in and N non-empty values, and new_shape has length R_out, then input_indices has shape [N, R_in], input_shape has length R_in, output_indices has shape [N, R_out], and output_shape has length R_out.
Args:
- scope: A Scope object
- input_indices: 2-D. N x R_inmatrix with the indices of non-empty values in a SparseTensor.
- input_shape: 1-D. R_invector with the input SparseTensor's dense shape.
- new_shape: 1-D. R_outvector with the requested new dense shape.
Returns:
- Outputoutput_indices: 2-D.- N x R_outmatrix with the updated indices of non-empty values in the output SparseTensor.
- Outputoutput_shape: 1-D.- R_outvector with the full dense shape of the output SparseTensor. This is the same as- new_shapebut with any -1 dimensions filled in.
| Constructors and Destructors | |
|---|---|
| SparseReshape(const ::tensorflow::Scope & scope, ::tensorflow::Input input_indices, ::tensorflow::Input input_shape, ::tensorflow::Input new_shape) | 
| Public attributes | |
|---|---|
| operation | |
| output_indices | |
| output_shape | |
Public attributes
operation
Operation operation
output_indices
::tensorflow::Output output_indices
output_shape
::tensorflow::Output output_shape
Public functions
SparseReshape
SparseReshape( const ::tensorflow::Scope & scope, ::tensorflow::Input input_indices, ::tensorflow::Input input_shape, ::tensorflow::Input new_shape )