tensorflow::ops::SparseReduceMax

Computes the max of elements across dimensions of a SparseTensor.

Summary

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.

Args:

• scope: A Scope object
• input_indices: 2-D. N x R matrix with the indices of non-empty values in a SparseTensor, possibly not in canonical ordering.
• input_values: 1-D. N non-empty values corresponding to input_indices.
• input_shape: 1-D. Shape of the input SparseTensor.
• reduction_axes: 1-D. Length-K vector containing the reduction axes.

Optional attributes (see Attrs):

• keep_dims: If true, retain reduced dimensions with length 1.

Returns:

• Output: R-K-D. The reduced Tensor.

Public attributes

Operation operation

::tensorflow::Output output

Public functions

 SparseReduceMax(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input_indices,
  ::tensorflow::Input input_values,
  ::tensorflow::Input input_shape,
  ::tensorflow::Input reduction_axes
)

 SparseReduceMax(
  const ::tensorflow::Scope & scope,
  ::tensorflow::Input input_indices,
  ::tensorflow::Input input_values,
  ::tensorflow::Input input_shape,
  ::tensorflow::Input reduction_axes,
  const SparseReduceMax::Attrs & attrs
)

::tensorflow::Node * node() const 

 operator::tensorflow::Input() const 

 operator::tensorflow::Output() const 

Public static functions

Attrs KeepDims(
  bool x
)