tf.sparse.reduce_max_sparse( sp_input, axis=None, keepdims=None, reduction_axes=None, keep_dims=None )
Computes the max of elements across dimensions of a SparseTensor. (deprecated arguments)
SOME ARGUMENTS ARE DEPRECATED. They will be removed in a future version. Instructions for updating: keep_dims is deprecated, use keepdims instead
This Op takes a SparseTensor and is the sparse counterpart to
tf.reduce_max(). In contrast to SparseReduceSum, this Op returns a
sp_input along the dimensions given in
keepdims is true, the rank of the tensor is reduced by 1 for each entry in
keepdims 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.
sp_input: The SparseTensor to reduce. Should have numeric type.
axis: The dimensions to reduce; list or scalar. If
None(the default), reduces all dimensions.
keepdims: If true, retain reduced dimensions with length 1.
reduction_axes: Deprecated name of axis.
keep_dims: Deprecated alias for
The reduced SparseTensor.