code: def from_payload(  # pylint: disable=arguments-differ
      cls,
      payload: Payload,
      plasma_db: "ext.PlasmaClient"
      | None = Provide[BentoMLContainer.plasma_db],
  ) -> torch.Tensor:
      if payload.meta.get("plasma"):
          import pyarrow.plasma as plasma
  
          assert plasma_db
          ret = plasma_db.get(plasma.ObjectID(payload.data))
  
      else:
          ret = pickle.loads(payload.data)
      return torch.from_numpy(ret).requires_grad_(False)
  
imports: from __future__ import annotations
  import functools
  import itertools
  import logging
  import pickle
  import typing
  from typing import TYPE_CHECKING
  from simple_di import Provide
  from simple_di import inject
  import bentoml
  from ....exceptions import MissingDependencyException
  from ...configuration.containers import BentoMLContainer
  from ...models.model import Model
  from ...runner.container import DataContainer
  from ...runner.container import DataContainerRegistry
  from ...runner.container import Payload
  from ...runner.utils import Params
  from ...types import LazyType
label_desc: Use image node_id 4 for calling the PyTorchTensorContainer obj's underlying member method code with example usage: obj.from_payload(cls, payload, plasma_db) and returns: torch