class_docstr: Model described in (https://arxiv.org/abs/1811.00945).
  
  A model for producing engaging captions about an image. Given an image and
  this model will attempt to predict an appropriate
  next utterance in the dialog, in the context of a given personality.
  
  See the paper linked above for more information.
class_docstr_tok: ["Model","described","in","(","https",":","\/\/arxiv.org\/abs\/1811.00945",")",".","A","model","for","producing","engaging","captions","about","an","image",".","Given","an","image","and","this","model","will","attempt","to","predict","an","appropriate","next","utterance","in","the","dialog",",","in","the","context","of","a","given","personality",".","See","the","paper","linked","above","for","more","information","."]
docstr: Load a model.
  
  :param path:
      path from which to load model
docstr_tok: ["Load","a","model",".",":","param","path",":","path","from","which","to","load","model"]
code: def load(self, path):
      """
      Load a model.
  
      :param path:
          path from which to load model
      """
      with PathManager.open(path, "rb") as f:
          states = torch.load(f, map_location=lambda cpu, _: cpu)
      if "model" in states:
          self.model.load_state_dict(states["model"])
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.core.agents import Agent
  from parlai.core.dict import DictionaryAgent
  from parlai.utils.misc import round_sigfigs
  from .modules import TransresnetModel
  from parlai.tasks.personality_captions.build import build
  from parlai.utils.io import PathManager
  import parlai.utils.torch
  import os
  import random
  import json
  import numpy
  import torch
  import tqdm
label_desc: Use image node_id 22 for calling the TransresnetAgent obj's underlying member method code with example usage: obj.load(path) without return types