tf.sparse_reduce_sum_sparse( sp_input, axis=None, keep_dims=False, reduction_axes=None )
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.
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.
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 axis
The reduced SparseTensor.
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Code samples licensed under the Apache 2.0 License.