"dtype". If "dtype" is "None" it is inferred to be
         "self.dtype". When "non_blocking", tries to convert
         asynchronously with respect to the host if possible, e.g.,
         converting a CPU Tensor with pinned memory to a CUDA Tensor.
         When "copy" is set, a new Tensor is created even when the
         Tensor already matches the desired conversion.
     Args:
        memory_format ("torch.memory_format", optional): the
        desired memory format of returned Tensor. Default:
        "torch.preserve_format".

torch.to(other, non_blocking=False, copy=False) -> Tensor
     Returns a Tensor with same "torch.dtype" and "torch.device"
     as the Tensor "other". When "non_blocking", tries to convert
     asynchronously with respect to the host if possible, e.g.,
     converting a CPU Tensor with pinned memory to a CUDA Tensor.
     When "copy" is set, a new Tensor is created even when the
