Computes the max of elements across dimensions of a SparseTensor. (deprecated arguments) (deprecated arguments)
tf.compat.v1.sparse_reduce_max( sp_input, axis=None, keepdims=None, reduction_axes=None, keep_dims=None )
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.
Note: A gradient is not defined for this function, so it can't be used in training models that need gradient descent.
Reduces sp_input
along the dimensions given in reduction_axes
. Unless keepdims
is true, the rank of the tensor is reduced by 1 for each entry in reduction_axes
. If keepdims
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, similar to the indexing rules in Python.
The values not defined in sp_input
don't participate in the reduce max, as opposed to be implicitly assumed 0 -- hence it can return negative values for sparse reduction_axes
. But, in case there are no values in reduction_axes
, it will reduce to 0. See second example below.
# 'x' represents [[1, ?, 2] # [?, 3, ?]] # where ? is implicitly-zero. tf.sparse.reduce_max(x) ==> 3 tf.sparse.reduce_max(x, 0) ==> [1, 3, 2] tf.sparse.reduce_max(x, 1) ==> [2, 3] # Can also use -1 as the axis. tf.sparse.reduce_max(x, 1, keepdims=True) ==> [[2], [3]] tf.sparse.reduce_max(x, [0, 1]) ==> 3 # 'y' represents [[-7, ?] # [ 4, 3] # [ ?, ?] tf.sparse.reduce_max(x, 1) ==> [-7, 4, 0]
Args | |
---|---|
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 keepdims . |
Returns | |
---|---|
The reduced Tensor. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/sparse_reduce_max