code: def to_numpy(tensor):
      if torch.is_tensor(tensor):
          if tensor.requires_grad:
              tensor = tensor.detach()
          if tensor.cuda:
              tensor = tensor.cpu()
          return tensor.numpy()
      elif isinstance(tensor, np.ndarray):
          return tensor
      else:
          return np.asarray(tensor)
  
imports: from packaging.version import Version
  import numpy
  from .core import Backend, backend_types, backend_basic_math, backend_array
label_desc: Use image node_id 3 for calling the PyTorchBackend obj's underlying member method code with example usage: obj.to_numpy(tensor) and returns: tensor, tensor, np