code: def profile_method(target: "Target") -> Callable:
      """
      Wrap a `call_method` node
      record the memory cost and FLOPs of the execution.
  
      Warnings:
          This is not fully implemented and you may follow the error message to debug.
      """
  
      def f(
          *args: Tuple[Argument, ...], **kwargs: Dict[str, Any]
      ) -> Any:
          # args[0] is the `self` object for this method call
          self_obj, *args_tail = args
  
          # execute the method and return the result
          assert isinstance(
              target, str
          ), f"{target} instance is not str."
  
          out = getattr(self_obj, target)(*args_tail, **kwargs)
          assert (
              target in INPLACE_METHOD + NON_INPLACE_METHOD
          ), CALL_METHOD_MSG.format(
              target, INPLACE_METHOD, NON_INPLACE_METHOD
          )
          # call_method has no parameters and are MOSTLY(?) inplace, and has no FLOPs or MACs.
          fwd_tmp = (
              0 if target in INPLACE_METHOD else activation_size(out)
          )
          fwd_out = (
              0
              if target not in INPLACE_METHOD
              else activation_size(out)
          )
          return out, GraphInfo(
              0, 0, fwd_tmp, fwd_out, fwd_tmp + fwd_out, 0
          )
  
      return f
  
file_path: colossalai/colossalai/fx/profiler/experimental/profiler.py
imports: from dataclasses import dataclass
  from typing import Any, Callable, Dict, Tuple
  import torch
  from torch.fx.node import Argument, Target
  from ..._compatibility import compatibility
  from ..memory_utils import activation_size
  from .constants import INPLACE_METHOD, INPLACE_OPS, NON_INPLACE_METHOD
  from .registry import meta_profiler_function, meta_profiler_module
label_desc: Use image node_id 2 for calling a global function with example usage: profile_method(target) and returns: f, out,  GraphInfo