mindspore.ops.UnsortedSegmentMin
- class mindspore.ops.UnsortedSegmentMin[source]
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 (Union[int, Tensor]) - Set \(z\) as num_segments, it can be an int or 0-D Tensor.
- Outputs:
Tensor, the shape is \((z, x_{N+1}, ..., x_R)\).
- 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.]]