Aliases:
tf.sparse.reduce_sum_sparse
tf.sparse_reduce_sum_sparse
tf.sparse.reduce_sum_sparse(
sp_input,
axis=None,
keepdims=None,
reduction_axes=None,
keep_dims=None
)
Defined in tensorflow/python/ops/sparse_ops.py
.
Computes the sum of elements across dimensions of a SparseTensor. (deprecated arguments)
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
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,
which are interpreted according to the indexing rules in Python.
Args:
sp_input
: The SparseTensor to reduce. Should have numeric type.axis
: The dimensions to reduce; list or scalar. IfNone
(the default), reduces all dimensions.keepdims
: If true, retain reduced dimensions with length 1.reduction_axes
: Deprecated name of axis.keep_dims
: Deprecated alias forkeepdims
.
Returns:
The reduced SparseTensor.