T - data type for outputValues() outputOp@Operator(group="sparse") public final class SparseReduceSumSparse<T> extends PrimitiveOp
This Op takes a SparseTensor and is the sparse counterpart to `tf.reduce_sum()`. In contrast to SparseReduceSum, this Op returns a SparseTensor.
Reduces `sp_input` along the dimensions given in `reduction_axes`. Unless `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained with length 1.
If `reduction_axes` has no entries, all dimensions are reduced, and a tensor with a single element is returned. Additionally, the axes can be negative, which are interpreted according to the indexing rules in Python.
| Modifier and Type | Class | Description |
|---|---|---|
static class |
SparseReduceSumSparse.Options |
Optional attributes for
SparseReduceSumSparse |
operation| Modifier and Type | Method | Description |
|---|---|---|
static <T> SparseReduceSumSparse<T> |
create(Scope scope,
Operand<java.lang.Long> inputIndices,
Operand<T> inputValues,
Operand<java.lang.Long> inputShape,
Operand<java.lang.Integer> reductionAxes,
SparseReduceSumSparse.Options... options) |
Factory method to create a class to wrap a new SparseReduceSumSparse operation to the graph.
|
static SparseReduceSumSparse.Options |
keepDims(java.lang.Boolean keepDims) |
|
Output<java.lang.Long> |
outputIndices() |
|
Output<java.lang.Long> |
outputShape() |
|
Output<T> |
outputValues() |
clone, finalize, getClass, notify, notifyAll, wait, wait, waitequals, hashCode, toStringpublic static <T> SparseReduceSumSparse<T> create(Scope scope, Operand<java.lang.Long> inputIndices, Operand<T> inputValues, Operand<java.lang.Long> inputShape, Operand<java.lang.Integer> reductionAxes, SparseReduceSumSparse.Options... options)
scope - current graph scopeinputIndices - 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.reductionAxes - 1-D. Length-`K` vector containing the reduction axes.options - carries optional attributes valuespublic static SparseReduceSumSparse.Options keepDims(java.lang.Boolean keepDims)
keepDims - If true, retain reduced dimensions with length 1.public Output<java.lang.Long> outputIndices()
public Output<java.lang.Long> outputShape()