class_docstr: CrypTensor class that uses plaintext PyTorch tensors as underlying backend.
  This class should be used for testing purposes.
code: def __init__(self, tensor, device=None, *args, **kwargs):
      # take required_grad from kwargs, input tensor, or set to False:
      default = (
          tensor.requires_grad if torch.is_tensor(tensor) else False
      )
      requires_grad = kwargs.pop("requires_grad", default)
  
      # call CrypTensor constructor:
      super().__init__(requires_grad=requires_grad)
  
      if device is None:
          device = torch.device("cpu")
      if not torch.is_tensor(tensor):
          tensor = torch.tensor(tensor, device=device)
      else:
          tensor = tensor.detach().to(device=device)
      tensor.requires_grad = False
      self._tensor = tensor
  
imports: import torch
  from crypten import CrypTensor, register_cryptensor
label_desc: Use image node_id 1 to create a new PyTorchTensor object from inherited base classes: CrypTensor with example: obj = PyTorchTensor(tensor, device)