public final class
SparseReorder
Reorders a SparseTensor into the canonical, row-major ordering.
Note that by convention, all sparse ops preserve the canonical ordering along increasing dimension number. The only time ordering can be violated is during manual manipulation of the indices and values vectors to add entries.
Reordering does not affect the shape of the SparseTensor.
If the tensor has rank `R` and `N` non-empty values, `input_indices` has shape `[N, R]`, input_values has length `N`, and input_shape has length `R`.
Constants
| String | OP_NAME | The name of this op, as known by TensorFlow core engine |
Public Methods
| static <T extends TType> SparseReorder<T> | |
| Output<TInt64> |
outputIndices()
2-D.
|
| Output<T> |
outputValues()
1-D.
|
Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
Constant Value:
"SparseReorder"
Public Methods
public static SparseReorder<T> create (Scope scope, Operand<TInt64> inputIndices, Operand<T> inputValues, Operand<TInt64> inputShape)
Factory method to create a class wrapping a new SparseReorder operation.
Parameters
| scope | current scope |
|---|---|
| inputIndices | 2-D. `N x R` matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering. |
| inputValues | 1-D. `N` non-empty values corresponding to `input_indices`. |
| inputShape | 1-D. Shape of the input SparseTensor. |
Returns
- a new instance of SparseReorder
public Output<TInt64> outputIndices ()
2-D. `N x R` matrix with the same indices as input_indices, but in canonical row-major ordering.