Reshapes a SparseTensor to represent values in a new dense shape.
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`.
|String||OP_NAME||The name of this op, as known by TensorFlow core engine|
wait(long arg0, int arg1)
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
public static SparseReshape create (Scope scope, Operand<TInt64> inputIndices, Operand<TInt64> inputShape, Operand<TInt64> newShape)
Factory method to create a class wrapping a new SparseReshape operation.
|inputIndices||2-D. `N x R_in` matrix with the indices of non-empty values in a SparseTensor.|
|inputShape||1-D. `R_in` vector with the input SparseTensor's dense shape.|
|newShape||1-D. `R_out` vector with the requested new dense shape.|
- a new instance of SparseReshape
2-D. `N x R_out` matrix with the updated indices of non-empty values in the output SparseTensor.