mindspore.ops.bincount

mindspore.ops.bincount(input, weights=None, minlength=0)[source]

Count the frequency of each value in the input tensor of non-negative ints.

If you don't specify minlength, the length of output tensor the length of the output tensor is max( input ) + 1.

If minlength is specified, the length of the output tensor is max([max( input ) + 1, minlength]).

If 'weights' is specified, the output results are weighted. If n is the value at position i, i.e out[n] += weight[i] instead of out[n] += 1.

Note

If input contains negative value, the result will be undefined.

Parameters

input (Tensor) – 1-D input tensor.
weights (Tensor, optional) – Weights. Default None .
minlength (int, optional) – A minimum number of bins for the output tensor. Default 0 .

Returns

Tensor, a tensor of shape [max(input)+1] if input is non-empty, otherwise, the shape is [0].

Supported Platforms:: Ascend GPU CPU

Examples

>>> import mindspore
>>> x = mindspore.tensor([2, 4, 1, 0, 0], dtype=mindspore.int64)
>>> print(mindspore.ops.bincount(x, minlength=7))
[2. 1. 1. 0. 1. 0. 0.]
>>> weights = mindspore.tensor([0, 0.25, 0.5, 0.75, 1], dtype=mindspore.float32)
>>> print(mindspore.ops.bincount(x, weights=weights))
[1.75 0.5  0.   0.   0.25]