class_docstr: Introspective Rationale Explainer
      
class_docstr_tok: ["Introspective","Rationale","Explainer"]
docstr: Load a pretrained model in the explainer
  
  :param pretrained_model_path: a path to a saved torch state dictionary
  :type pretrained_model_path: string
  :return: the pretrained model
  :rtype: IntrospectiveRationaleModel
code: def load_pretrained_model(self, pretrained_model_path):
      """Load a pretrained model in the explainer
  
      :param pretrained_model_path: a path to a saved torch state dictionary
      :type pretrained_model_path: string
      :return: the pretrained model
      :rtype: IntrospectiveRationaleModel
      """
      if self.cuda:
          self.model.load_state_dict(torch.load(pretrained_model_path))
      else:
          self.model.load_state_dict(
              torch.load(pretrained_model_path, map_location="cpu")
          )
      self.model.eval()
      return self.model
  
imports: from typing import Iterable, Any, Optional, Union, Dict
  import numpy
  import pandas
  import torch
  from interpret_text.experimental.common.base_explainer import BaseTextExplainer, _validate_X
  from interpret_text.experimental.common.constants import BertTokens
  from interpret_text.experimental.common.model_config.introspective_rationale_model_config import IntrospectiveRationaleModelConfig
  from interpret_text.experimental.common.model_config.model_config_constants import get_bert_default_config, get_rnn_default_config, get_bert_rnn_default_config
  from interpret_text.experimental.common.preprocessor.bert_preprocessor import BertPreprocessor
  from interpret_text.experimental.common.preprocessor.glove_preprocessor import GlovePreprocessor
  from interpret_text.experimental.common.utils_classical import plot_local_imp
  from interpret_text.experimental.common.utils_introspective_rationale import generate_data
  from interpret_text.experimental.explanation import _create_local_explanation, LocalExplanation
  from interpret_text.experimental.introspective_rationale.components import ClassifierWrapper, ClassifierModule, IntrospectionGeneratorModule
  from interpret_text.experimental.introspective_rationale.model import IntrospectiveRationaleModel
  from transformers import BertForSequenceClassification
label_desc: Use image node_id 23 for calling the IntrospectiveRationaleExplainer obj's underlying member method code with example usage: obj.load_pretrained_model(pretrained_model_path) and returns: self