code: def test_text_environment_generate(self):
      generation_kwargs = {
          "do_sample": False,
          "max_new_tokens": 4,
          "pad_token_id": self.gpt2_tokenizer.eos_token_id,
      }
      env = TextEnvironment(
          self.gpt2_model,
          self.gpt2_tokenizer,
          tools=[DummyTool()],
          reward_fn=lambda x: torch.tensor(1),
          prompt="I am a prompt!\n",
          generation_kwargs=generation_kwargs,
      )
  
      input_texts = ["this is a test", "this is another, longer test"]
  
      model_inputs = [
          self.gpt2_tokenizer(
              txt, return_tensors="pt"
          ).input_ids.squeeze()
          for txt in input_texts
      ]
  
      generations_batched = env._generate_batched(
          model_inputs, batch_size=2
      )
      generations_batched = self.gpt2_tokenizer.batch_decode(
          generations_batched
      )
  
      generations_single = [
          env._generate_batched([inputs], batch_size=1)[0]
          for inputs in model_inputs
      ]
      generations_single = self.gpt2_tokenizer.batch_decode(
          generations_single
      )
  
      self.assertEqual(generations_single, generations_batched)
  
imports: import unittest
  from unittest.mock import patch
  import torch
  from transformers import AutoTokenizer
  from trl import AutoModelForCausalLMWithValueHead, TextEnvironment, TextHistory
label_desc: Use image node_id 3 for calling the TextEnvironmentTester obj's underlying member method code with example usage: obj.test_text_environment_generate() without return types