mindspore.Tensor.unsorted_segment_max
- Tensor.unsorted_segment_max(segment_ids, num_segments)[source]
Computes the maximum along segments of a tensor.
Note
If the segment_id i is absent in the segment_ids, then output[i] will be filled with the minimum value of the type of self.
The segment_ids must be non-negative tensor.
- Parameters
- Returns
Tensor, set the number of num_segments as N, the shape is \((N, x_2, ..., x_R)\).
- Raises
TypeError – If num_segments is not an int.
ValueError – If length of shape of segment_ids is not equal to 1.
- Supported Platforms:
Ascend
GPU
CPU
Examples
>>> from mindspore import Tensor >>> 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 >>> output = x.unsorted_segment_max(segment_ids, num_segments) >>> print(output) [[1. 2. 3.] [4. 5. 6.]]