tensorflow::
ops::
SparseReshape
#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_in
matrix with the indices of non-empty values in a SparseTensor. -
input_shape: 1-D.
R_in
vector with the input SparseTensor's dense shape. -
new_shape: 1-D.
R_out
vector with the requested new dense shape.
Returns:
-
Output
output_indices: 2-D.N x R_out
matrix with the updated indices of non-empty values in the output SparseTensor. -
Output
output_shape: 1-D.R_out
vector with the full dense shape of the output SparseTensor. This is the same asnew_shape
but with any -1 dimensions filled in.
Constructors and Destructors |
|
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SparseReshape
(const ::
tensorflow::Scope
& scope, ::
tensorflow::Input
input_indices, ::
tensorflow::Input
input_shape, ::
tensorflow::Input
new_shape)
|
Public attributes |
|
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operation
|
|
output_indices
|
|
output_shape
|
Public attributes
Public functions
SparseReshape
SparseReshape( const ::tensorflow::Scope & scope, ::tensorflow::Input input_indices, ::tensorflow::Input input_shape, ::tensorflow::Input new_shape )