Computes the mean along sparse segments of a tensor.

tf.compat.v1.sparse_segment_mean( data, indices, segment_ids, name=None, num_segments=None )

Read the section on segmentation for an explanation of segments.

Like `tf.math.segment_mean`

, but `segment_ids`

can have rank less than `data`

's first dimension, selecting a subset of dimension 0, specified by `indices`

. `segment_ids`

is allowed to have missing ids, in which case the output will be zeros at those indices. In those cases `num_segments`

is used to determine the size of the output.

Args | |
---|---|

`data` | A `Tensor` with data that will be assembled in the output. |

`indices` | A 1-D `Tensor` with indices into `data` . Has same rank as `segment_ids` . |

`segment_ids` | A 1-D `Tensor` with indices into the output `Tensor` . Values should be sorted and can be repeated. |

`name` | A name for the operation (optional). |

`num_segments` | An optional int32 scalar. Indicates the size of the output `Tensor` . |

Returns | |
---|---|

A `tensor` of the shape as data, except for dimension 0 which has size `k` , the number of segments specified via `num_segments` or inferred for the last element in `segments_ids` . |

© 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_segment_mean