class_docstr: Model from "Engaging Image Chat: Modeling Personality in Grounded Dialogue".
  
  See paper for more details: (https://arxiv.org/abs/1811.00945)
  
  An extension of the model from https://arxiv.org/abs/1810.10665; given
  an image, personality, and dialogue history, predicts the next utterance
  in a dialogue.
class_docstr_tok: ["Model","from","``","Engaging","Image","Chat",":","Modeling","Personality","in","Grounded","Dialogue","''",".","See","paper","for","more","details",":","(","https",":","\/\/arxiv.org\/abs\/1811.00945",")","An","extension","of","the","model","from","https",":","\/\/arxiv.org\/abs\/1810.10665",";","given","an","image",",","personality",",","and","dialogue","history",",","predicts","the","next","utterance","in","a","dialogue","."]
docstr: Model train step.
  
  :param valid_obs:
      list of valid observations
  
  :param image_feats:
      list of image features, one per example
  
  :param personalities:
      list of personalities, one per example
  
  :param dialogue_histories:
      list of dialogue histories, one per example
  
  :return:
      the total loss and the number of correct examples
docstr_tok: ["Model","train","step",".",":","param","valid_obs",":","list","of","valid","observations",":","param","image_feats",":","list","of","image","features",",","one","per","example",":","param","personalities",":","list","of","personalities",",","one","per","example",":","param","dialogue_histories",":","list","of","dialogue","histories",",","one","per","example",":","return",":","the","total","loss","and","the","number","of","correct","examples"]
code: def train_step(
      self, valid_obs, image_feats, personalities, dialogue_histories
  ):
      """
      Model train step.
  
      :param valid_obs:
          list of valid observations
  
      :param image_feats:
          list of image features, one per example
  
      :param personalities:
          list of personalities, one per example
  
      :param dialogue_histories:
          list of dialogue histories, one per example
  
      :return:
          the total loss and the number of correct examples
      """
      self.model.train()
      labels = [random.choice(v["labels"]) for v in valid_obs]
      loss, num_correct, _ = self.model(
          image_feats,
          personalities,
          dialogue_histories,
          labels,
          batchsize=len(valid_obs),
      )
      return loss, num_correct
  
imports: from typing import Optional
  from parlai.core.params import ParlaiParser
  from parlai.core.opt import Opt
  from parlai.utils.misc import round_sigfigs
  from parlai.core.message import Message
  from .modules import TransresnetMultimodalModel
  from projects.personality_captions.transresnet.transresnet import TransresnetAgent
  from parlai.utils.io import PathManager
  import parlai.utils.torch
  import torch
  from torch import optim
  import random
  import numpy
  import tqdm
  from collections import deque
label_desc: Use image node_id 7 for calling the TransresnetMultimodalAgent obj's underlying member method code with example usage: obj.train_step(valid_obs, image_feats, personalities, dialogue_histories) and returns: loss,  num_correct