tf.math.segment_min
Computes the minimum along segments of a tensor.
tf.math.segment_min(
data: Annotated[Any, tf.raw_ops.Any],
segment_ids: Annotated[Any, tf.raw_ops.Any],
name=None
) -> Annotated[Any, tf.raw_ops.Any]
Read the section on segmentation for an explanation of segments.
Computes a tensor such that \(output_i = \min_j(data_j)\) where min is over j such that segment_ids[j] == i.
If the min is empty for a given segment ID i, output[i] = 0.
For example:
c = tf.constant([[1,2,3,4], [4, 3, 2, 1], [5,6,7,8]])
tf.math.segment_min(c, tf.constant([0, 0, 1])).numpy()
array([[1, 2, 2, 1],
[5, 6, 7, 8]], dtype=int32)| Args | |
|---|---|
data | A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64. |
segment_ids | A Tensor. Must be one of the following types: int32, int64. A 1-D tensor whose size is equal to the size of data's first dimension. Values should be sorted and can be repeated.
|
name | A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor. Has the same type as data. |
© 2022 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_docs/python/tf/math/segment_min
