class_docstr: Testing suite for v-head models.
docstr: Test if we instantiate a model by adding `summary_drop_prob` to the config
  it will be added to the v_head
docstr_tok: ["Test","if","we","instantiate","a","model","by","adding","`","summary_drop_prob","`","to","the","config","it","will","be","added","to","the","v_head"]
code: def test_dropout_kwargs(self):
      r"""
      Test if we instantiate a model by adding `summary_drop_prob` to the config
      it will be added to the v_head
      """
      for model_name in self.all_model_names:
          v_head_kwargs = {"summary_dropout_prob": 0.5}
  
          model = self.trl_model_class.from_pretrained(
              model_name, **v_head_kwargs
          )
  
          # Check if v head of the model has the same dropout as the config
          self.assertEqual(model.v_head.dropout.p, 0.5)
  
          model = self.trl_model_class.from_pretrained(
              model_name, summary_dropout_prob=0.5
          )
  
          # Check if v head of the model has the same dropout as the config
          self.assertEqual(model.v_head.dropout.p, 0.5)
  
imports: import gc
  import tempfile
  import unittest
  import torch
  from transformers import AutoModel, AutoModelForCausalLM, AutoModelForSeq2SeqLM
  from trl import AutoModelForCausalLMWithValueHead, AutoModelForSeq2SeqLMWithValueHead, create_reference_model
label_desc: Use image node_id 4 for calling the Seq2SeqValueHeadModelTester obj's underlying member method code with example usage: obj.test_dropout_kwargs() without return types