torch.take_along_dim

torch.take_along_dim(input, indices, dim=None, *, out=None) → Tensor

Selects values from input at the 1-dimensional indices from indices along the given dim.

If dim is None, the input array is treated as if it has been flattened to 1d.

Functions that return indices along a dimension, like torch.argmax() and torch.argsort(), are designed to work with this function. See the examples below.

Note

This function is similar to NumPy’s take_along_axis. See also torch.gather().

Parameters

• input (Tensor) – the input tensor.

• indices (LongTensor) – the indices into input. Must have long dtype.

• dim (int, optional) – dimension to select along. Default: 0

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> t = torch.tensor([[10, 30, 20], [60, 40, 50]])
>>> max_idx = torch.argmax(t)
>>> torch.take_along_dim(t, max_idx)
tensor([60])
>>> sorted_idx = torch.argsort(t, dim=1)
>>> torch.take_along_dim(t, sorted_idx, dim=1)
tensor([[10, 20, 30],
        [40, 50, 60]])