torch.cat#

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

Concatenates the given sequence of tensors intensors in the given dimension.All tensors must either have the same shape (except in the concatenatingdimension) or be a 1-D empty tensor with size(0,).

torch.cat() can be seen as an inverse operation fortorch.split()andtorch.chunk().

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

See also

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

Parameters

• tensors (sequence ofTensors) – 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)>>>xtensor([[ 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]])