|---|
| [ View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.13.1/tensorflow/python/ops/sparse_ops.py#L1470-L1546) |
Computes [`tf.sparse.add`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/sparse/add) of elements across dimensions of a SparseTensor.
tf.sparse.reduce_sum(
sp_input, axis=None, keepdims=None, output_is_sparse=False, name=None
)
This is the reduction operation for the elementwise [`tf.sparse.add`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/sparse/add) op.
This Op takes a SparseTensor and is the sparse counterpart to
[`tf.reduce_sum()`](https://www.tensorflow.org/versions/r2.13/api_docs/python/tf/math/reduce_sum). In particular, this Op also returns a dense `Tensor`
if `output_is_sparse` is `False`, or a `SparseTensor` if `output_is_sparse`
is `True`.
> [!NOTE]
> **Note:** if `output_is_sparse` is True, a gradient is not defined for this function, so it can't be used in training models that need gradient descent.
Reduces `sp_input` along the dimensions given in `axis`. Unless `keepdims` is
true, the rank of the tensor is reduced by 1 for each entry in `axis`. If
`keepdims` is true, the reduced dimensions are retained with length 1.
If `axis` 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. x = tf.sparse.SparseTensor([[0, 0], [0, 2], [1, 1]], [1, 1, 1], [2, 3]) tf.sparse.reduce_sum(x) tf.sparse.reduce_sum(x, 0) tf.sparse.reduce_sum(x, 1) # Can also use -1 as the axis tf.sparse.reduce_sum(x, 1, keepdims=True) tf.sparse.reduce_sum(x, [0, 1])
||
| ## 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. |
| `keepdims` | If true, retain reduced dimensions with length 1. |
| `output_is_sparse` | If true, returns a `SparseTensor` instead of a dense `Tensor` (the default). |
| `name` | A name for the operation (optional). |
| ## Returns ||
|---|---|
| The reduced Tensor or the reduced SparseTensor if `output_is_sparse` is True. ||