class_docstr: A subclass of :class:`~ffcv.fields.Field` supporting
  multi-dimensional fixed size matrices of any torch type.
class_docstr_tok: ["A","subclass","of",":","class",":","`","~ffcv.fields.Field","`","supporting","multi-dimensional","fixed","size","matrices","of","any","torch","type","."]
code: def encode(self, destination, field, malloc):
      field = field.numpy()
      return super().encode(destination, field, malloc)
  
imports: from typing import Callable, TYPE_CHECKING, Tuple, Type
  import warnings
  import json
  from dataclasses import replace
  import numpy
  import torch
  from .base import Field, ARG_TYPE
  from ..pipeline.operation import Operation
  from ..pipeline.state import State
  from ..pipeline.compiler import Compiler
  from ..pipeline.allocation_query import AllocationQuery
  from ..libffcv import memcpy
label_desc: Use image node_id 2 for calling the TorchTensorField obj's underlying member method code with example usage: obj.encode(destination, field, malloc) and returns: super