qfeval_functions.functions.bincount

bincount(x, minlength=0, dim=-1)[source]

Count number of occurrences of each value in a tensor.

This function computes the frequency of each non-negative integer value in the input tensor along the specified dimension. The output tensor’s size along the counted dimension is the maximum of minlength and the largest value in the input plus one. Each position in the output contains the count of that index value in the input.

Parameters:

  • x (Tensor) – The input tensor containing non-negative integer values.

  • minlength (int) – Minimum length of the output tensor along the counted dimension. If the maximum value in x is less than minlength - 1, the output is padded with zeros. Default is 0.

  • dim (int) – The dimension along which to count values. Default is -1 (the last dimension).

Returns:

A tensor where the value at index i along the specified dimension contains the count of occurrences of value i in the corresponding slice of the input tensor.

Return type:

Tensor

Example

>>> x = torch.tensor([1, 2, 2, 3, 3, 1])
>>> QF.bincount(x)
tensor([0, 2, 2, 2])

>>> x = torch.tensor([[1, 2, 2], [3, 3, 1]])
>>> QF.bincount(x, dim=1)
tensor([[0, 1, 2, 0],
        [0, 1, 0, 2]])

>>> x = torch.tensor([1, 2])
>>> QF.bincount(x, minlength=5)
tensor([0, 1, 1, 0, 0])