SparseReshape
tensorflow C++ API
tensorflow::ops::SparseReshape
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.
Arguments:
- 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 asnew_shapebut with any -1 dimensions filled in.
SparseReshape block
Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_sparse.cpp

Argument:
- Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
- Input input_indices: connect Input node.
- Input input_shape: connect Input node.
- Input new_shape: connect Input node.
Return:
- Output output: Output object of SparseReshape class object.
Result:
- std::vector(Tensor) product_result : Returned object of executed result by calling session.
