tf.raw_ops.SparseSegmentMeanWithNumSegments

Computes the mean along sparse segments of a tensor.

Compat aliases for migration

tf.compat.v1.raw_ops.SparseSegmentMeanWithNumSegments

tf.raw_ops.SparseSegmentMeanWithNumSegments(
    data, indices, segment_ids, num_segments, name=None
)

Like SparseSegmentMean, but allows missing ids in segment_ids. If an id is missing, the output tensor at that position will be zeroed.

Read the section on segmentation for an explanation of segments.

Args
`data`	A `Tensor`. Must be one of the following types: `bfloat16`, `half`, `float32`, `float64`.
`indices`	A `Tensor`. Must be one of the following types: `int32`, `int64`. A 1-D tensor. Has same rank as `segment_ids`.
`segment_ids`	A `Tensor`. Must be one of the following types: `int32`, `int64`. A 1-D tensor. Values should be sorted and can be repeated.
`num_segments`	A `Tensor`. Must be one of the following types: `int32`, `int64`. Should equal the number of distinct segment IDs.
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type as `data`.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates. Some content is licensed under the numpy license.

Last updated 2022-10-27 UTC.

Args