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Showing content from https://docs.pytorch.org/docs/stable/generated/torch.mode.html below:

torch.mode — PyTorch 2.7 documentation

torch.mode(input, dim=-1, keepdim=False, *, out=None)¶

Returns a namedtuple (values, indices) where values is the mode value of each row of the input tensor in the given dimension dim, i.e. a value which appears most often in that row, and indices is the index location of each mode value found.

By default, dim is the last dimension of the input tensor.

If keepdim is True, the output tensors are of the same size as input except in the dimension dim where they are of size 1. Otherwise, dim is squeezed (see torch.squeeze()), resulting in the output tensors having 1 fewer dimension than input.

Note

This function is not defined for torch.cuda.Tensor yet.

Parameters

• input (Tensor) – the input tensor.

• dim (int) – the dimension to reduce.

• keepdim (bool) – whether the output tensor has dim retained or not.

Keyword Arguments

out (tuple, optional) – the result tuple of two output tensors (values, indices)

Example:

>>> b = torch.tensor([[0, 0, 0, 2, 0, 0, 2],
...                   [0, 3, 0, 0, 2, 0, 1],
...                   [2, 2, 2, 0, 0, 0, 3],
...                   [2, 2, 3, 0, 1, 1, 0],
...                   [1, 1, 0, 0, 2, 0, 2]])
>>> torch.mode(b, 0)
torch.return_types.mode(
values=tensor([0, 2, 0, 0, 0, 0, 2]),
indices=tensor([1, 3, 4, 4, 2, 4, 4]))

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