mindspore.ops.unsorted_segment_max

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mindspore.ops.unsorted_segment_max(x, segment_ids, num_segments)[source]

Compute the maximum of the input tensor along segments.

The following figure shows the calculation process of unsorted_segment_max:

../../_images/UnsortedSegmentMax.png
\[\text { output }_i=\text{max}_{j \ldots} \text { data }[j \ldots]\]

where \(max\) over tuples \(j...\) such that \(segment\_ids[j...] == i\).

Note

  • If the segment_id i is absent in the segment_ids, then output[i] will be filled with the minimum value of the x's type.

  • The segment_ids must be non-negative tensor.

Parameters

  • x (Tensor) – The input tensor.

  • segment_ids (Tensor) – Indicate the segment to which each element belongs. Set the shape as \((x_1, x_2, ..., x_N)\), where 0 < N <= R.

  • num_segments (Union[int, Tensor]) – Number of segments, it can be an int or 0-D tensor.

Returns

Tensor

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> x = mindspore.tensor([[1, 2, 3], [4, 5, 6], [4, 2, 1]])
>>> segment_ids = mindspore.tensor([0, 1, 1])
>>> num_segments = 2
>>> mindspore.ops.unsorted_segment_max(x, segment_ids, num_segments)
Tensor(shape=[2, 3], dtype=Int64, value=
[[1, 2, 3],
 [4, 5, 6]])