Computes the sum of elements across dimensions of a SparseTensor. (deprecated arguments)
`tf.sparse_reduce_sum_sparse`Compat aliases for migration
See Migration guide for more details.
tf.sparse.reduce_sum_sparse( 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_sum(). In contrast to SparseReduceSum, this Op returns a SparseTensor.
Note: A gradient is not defined for this function, so it can't be used in training models that need gradient descent.
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.
| ||The SparseTensor to reduce. Should have numeric type.|
| || The dimensions to reduce; list or scalar. If |
| ||If true, retain reduced dimensions with length 1.|
| ||Deprecated name of axis.|
| || Deprecated alias for |
|The reduced SparseTensor.|
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