Computes the sum of elements across dimensions of a SparseTensor. (deprecated arguments)

tf.compat.v1.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.

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. |

`keepdims` | If true, retain reduced dimensions with length 1. |

`reduction_axes` | Deprecated name of axis. |

`keep_dims` | Deprecated alias for `keepdims` . |

Returns | |
---|---|

The reduced SparseTensor. |

© 2020 The TensorFlow Authors. All rights reserved.

Licensed under the Creative Commons Attribution License 3.0.

Code samples licensed under the Apache 2.0 License.

https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/sparse_reduce_sum_sparse