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. If None (the
default), reduces all dimensions.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2022-11-04 UTC."],[],[]]