tf.sparse_reduce_sum_sparse( sp_input, axis=None, keep_dims=False, reduction_axes=None )
Defined in tensorflow/python/ops/sparse_ops.py
.
See the guide: Sparse Tensors > Reduction
Computes the sum of elements across dimensions of a SparseTensor.
This Op takes a SparseTensor and is the sparse counterpart to tf.reduce_sum()
. In contrast to SparseReduceSum, this Op returns a SparseTensor.
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.
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.keep_dims
: If true, retain reduced dimensions with length 1.reduction_axes
: Deprecated name of axisThe reduced SparseTensor.
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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/api_docs/python/tf/sparse_reduce_sum_sparse