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# torch.cat

torch.cat(tensors, dim=0, *, out=None) → Tensor

  Concatenates the given sequence of `seq` tensors in the given dimension. All tensors must either have the same shape (except in the concatenating dimension) or be empty.

  `torch.cat()` can be seen as an inverse operation for `torch.split()` and `torch.chunk()`.

  `torch.cat()` can be best understood via examples.

  See also

  `torch.stack()` concatenates the given sequence along a new dimension.

  Parameters:

    - tensors (sequence of Tensors) – any python sequence of tensors of the same type. Non-empty tensors provided must have the same shape, except in the cat dimension.

    - dim (int, optional) – the dimension over which the tensors are concatenated

  Keyword Arguments:

    out (Tensor, optional) – the output tensor.

  Example:

      >>> x = torch.randn(2, 3)
      >>> x
      tensor([[ 0.6580, -1.0969, -0.4614],
              [-0.1034, -0.5790,  0.1497]])
      >>> torch.cat((x, x, x), 0)
      tensor([[ 0.6580, -1.0969, -0.4614],
              [-0.1034, -0.5790,  0.1497],
              [ 0.6580, -1.0969, -0.4614],
              [-0.1034, -0.5790,  0.1497],
              [ 0.6580, -1.0969, -0.4614],
              [-0.1034, -0.5790,  0.1497]])
      >>> torch.cat((x, x, x), 1)
      tensor([[ 0.6580, -1.0969, -0.4614,  0.6580, -1.0969, -0.4614,  0.6580,
               -1.0969, -0.4614],
              [-0.1034, -0.5790,  0.1497, -0.1034, -0.5790,  0.1497, -0.1034,
               -0.5790,  0.1497]])

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