SparseReduceMax

public final class SparseReduceMax

Computes the max of elements across dimensions of a SparseTensor.

This Op takes a SparseTensor and is the sparse counterpart to `tf.reduce_max()`. In particular, this Op also returns a dense `Tensor` instead of a sparse one.

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.

Nested Classes

class SparseReduceMax.Options Optional attributes for SparseReduceMax

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output <T>
asOutput ()
Returns the symbolic handle of the tensor.
static <T extends TNumber > SparseReduceMax <T>
create ( Scope scope, Operand < TInt64 > inputIndices, Operand <T> inputValues, Operand < TInt64 > inputShape, Operand < TInt32 > reductionAxes, Options... options)
Factory method to create a class wrapping a new SparseReduceMax operation.
static SparseReduceMax.Options
keepDims (Boolean keepDims)
Output <T>
output ()
`R-K`-D.

Inherited Methods

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "SparseReduceMax"

Public Methods

public Output <T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static SparseReduceMax <T> create ( Scope scope, Operand < TInt64 > inputIndices, Operand <T> inputValues, Operand < TInt64 > inputShape, Operand < TInt32 > reductionAxes, Options... options)

Factory method to create a class wrapping a new SparseReduceMax 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.
reductionAxes 1-D. Length-`K` vector containing the reduction axes.
options carries optional attributes values
Returns
  • a new instance of SparseReduceMax

public static SparseReduceMax.Options keepDims (Boolean keepDims)

Parameters
keepDims If true, retain reduced dimensions with length 1.

public Output <T> output ()

`R-K`-D. The reduced Tensor.