Computes the max of elements across dimensions of a SparseTensor.
Compat aliases for migration
See Migration guide for more details.
tf.raw_ops.SparseReduceMax( input_indices, input_values, input_shape, reduction_axes, keep_dims=False, name=None )
This Op takes a SparseTensor and is the sparse counterpart to
tf.reduce_max(). In particular, this Op also returns a dense
instead of a sparse one.
sp_input along the dimensions given in
keep_dims is true, the rank of the tensor is reduced by 1 for each entry in
keep_dims is true, the reduced dimensions are retained
with length 1.
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.