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mindspore.ops.UnsortedSegmentMin

class mindspore.ops.UnsortedSegmentMin

Computes the minimum of a tensor along segments.

Refer to mindspore.ops.unsorted_segment_min() for more details.

Inputs:

• input_x (Tensor) - The shape is $(x_1,x_2,...,x_R)$. The data type must be float16, float32 or int32.

• segment_ids (Tensor) - The label indicates the segment to which each element belongs. Set the shape as $(x_1,x_2,...,x_N)$, where 0 < N <= R.

• num_segments (int) - The value specifies the number of distinct segment_ids.

Outputs:

Tensor, set the number of num_segments as N, the shape is $(N,x_2,...,x_R)$.

Supported Platforms:

Ascend GPU CPU

Examples

>>> from mindspore import Tensor
>>> from mindspore import ops
>>> import numpy as np
>>> input_x = Tensor(np.array([[1, 2, 3], [4, 5, 6], [4, 2, 1]]).astype(np.float32))
>>> segment_ids = Tensor(np.array([0, 1, 1]).astype(np.int32))
>>> num_segments = 2
>>> unsorted_segment_min = ops.UnsortedSegmentMin()
>>> output = unsorted_segment_min(input_x, segment_ids, num_segments)
>>> print(output)
[[1. 2. 3.]
 [4. 2. 1.]]