Reshapes a SparseTensor to represent values in a new dense shape.
tf.raw_ops.SparseReshape(
input_indices, input_shape, new_shape, name=None
)
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 | |
|---|---|
input_indices
|
A Tensor of type int64.
2-D. N x R_in matrix with the indices of non-empty values in a
SparseTensor.
|
input_shape
|
A Tensor of type int64.
1-D. R_in vector with the input SparseTensor's dense shape.
|
new_shape
|
A Tensor of type int64.
1-D. R_out vector with the requested new dense shape.
|
name
|
A name for the operation (optional). |
Returns | |
|---|---|
A tuple of Tensor objects (output_indices, output_shape).
|
|
output_indices
|
A Tensor of type int64.
|
output_shape
|
A Tensor of type int64.
|