class_docstr: A Stage represents schedule for one operation.
class_docstr_tok: ["A","Stage","represents","schedule","for","one","operation","."]
docstr: Prefetch the specified variable
  
  Parameters
  ----------
  tensor : Tensor
      The tensor to be prefetched
  var : IterVar
      The loop point at which the prefetching is applied
  offset : Expr
      The number of iterations to be prefetched before actual execution
code: def prefetch(self, tensor, var, offset):
      """Prefetch the specified variable
  
      Parameters
      ----------
      tensor : Tensor
          The tensor to be prefetched
      var : IterVar
          The loop point at which the prefetching is applied
      offset : Expr
          The number of iterations to be prefetched before actual execution
      """
      _ffi_api.StagePrefetch(self, tensor, var, offset)
  
imports: import collections
  import inspect
  from typing import Callable, List
  import tvm._ffi
  from tvm._ffi.base import string_types
  from tvm.ir import container
  from tvm.runtime import Object, convert
  from tvm.tir import Buffer, IndexMap, IterVar, Var
  from .None import _ffi_api
  from .None import tensor
label_desc: Use image node_id 17 for calling the Stage obj's underlying member method code with example usage: obj.prefetch(tensor, var, offset) without return types