mindspore.ops.Bincount

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class mindspore.ops.Bincount[source]

Counts the number of occurrences of each value in an integer array.

Warning

This is an experimental API that is subject to change or deletion.

Inputs:

  • array (Tensor) - A Tensor of type int32, whose value can not be less than zero.

  • size (Tensor) - A non-negative Tensor of type int32.

  • weights (Tensor) - A Tensor with the same shape as array, or a length-0 Tensor, in which case it acts as all weights equal to 1. Must be one of the following types: int32, int64, float32, float64.

Outputs:

A Tensor. Has the same type as weights.

Raises

  • TypeError – If dtype of array is not int32.

  • TypeError – If dtype of size is not int32.

  • ValueError – If size is negative.

  • ValueError – If weights are empty.

  • ValueError – If size of weights is not zero and the shape of weights is different with the shape of array.

  • TypeError – If dtype of weights is not in int32,int64,float32,float64

Supported Platforms:

Ascend GPU CPU

Examples

>>> import mindspore
>>> import numpy as np
>>> from mindspore import Tensor, ops
>>> array = Tensor(np.array([1, 2, 2, 3, 3, 3, 4, 4, 4, 4]), mindspore.int32)
>>> size = Tensor(5, mindspore.int32)
>>> weights = Tensor(np.array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1]), mindspore.float32)
>>> bincount = ops.Bincount()
>>> bins = bincount(array, size, weights)
>>> print(bins)
[0. 1. 2. 3. 4.]