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Computes tf.sparse.add
of elements across dimensions of a SparseTensor. (deprecated arguments) (deprecated arguments)
tf.compat.v1.sparse_reduce_sum(
sp_input, axis=None, keepdims=None, reduction_axes=None, keep_dims=None
)
This is the reduction operation for the elementwise tf.sparse.add
op.
This Op takes a SparseTensor and is the sparse counterpart to
tf.reduce_sum()
. In particular, this Op also returns a dense Tensor
instead of a sparse one.
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.
For example | |
---|---|
'x' represents [[1, ?, 1][?, 1, ?]]where ? is implicitly-zero.
|
Returns | |
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The reduced Tensor. |