code: def context(tensor):
      return {
          "dtype": tensor.dtype,
          "device": tensor.device,
          "requires_grad": tensor.requires_grad,
      }
  
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 1 for calling the PyTorchBackend obj's underlying member method code with example usage: obj.context(tensor) and returns: dict