class pypose.identity_like(liegroup, **kwargs)[source]

Returns identity LieTensor with the same lsize and ltype as the given LieTensor.

  • liegroup (LieTensor) – the size of liegroup will determine the size of the output tensor.

  • requires_grad (bool, optional) – If autograd should record operations on the returned tensor. Default: False.

  • generator (torch.Generator, optional) – a pseudorandom number generator for sampling

  • dtype (torch.dtype, optional) – the desired data type of returned tensor. Default: if None, uses a global default (see torch.set_default_tensor_type()).

  • layout (torch.layout, optional) – the desired layout of returned Tensor. Default: torch.strided.

  • device (torch.device, optional) – the desired device of returned tensor. Default: if None, uses the current device for the default tensor type (see torch.set_default_tensor_type()). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types.


>>> x = pp.randn_SO3(3, device="cuda:0", dtype=torch.double, requires_grad=True)
>>> pp.identity_like(x, device="cpu")
SO3Type LieTensor:
tensor([[0., 0., 0., 1.],
        [0., 0., 0., 1.],
        [0., 0., 0., 1.]])


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