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# torch.take_along_dim

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

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

  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 (tensor) – the indices into `input`. Must have long dtype.

    - dim (int) – dimension to select along.

  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]])

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