Computes the mean along sparse segments of a tensor.
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, 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. |
© 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/raw_ops/SparseSegmentMeanWithNumSegments