code: def fixture_cfg():
      return DictDefault(
          {
              "base_model": "TinyLlama/TinyLlama-1.1B-Chat-v0.6",
              "model_type": "AutoModelForCausalLM",
              "tokenizer_type": "LlamaTokenizer",
              "micro_batch_size": 1,
              "gradient_accumulation_steps": 1,
              "learning_rate": 0.00005,
              "save_steps": 100,
              "output_dir": "./model-out",
              "warmup_steps": 10,
              "gradient_checkpointing": False,
              "optimizer": "adamw_torch",
              "sequence_len": 2048,
              "rl": True,
              "adam_beta1": 0.998,
              "adam_beta2": 0.9,
              "adam_epsilon": 0.00001,
              "dataloader_num_workers": 1,
              "dataloader_pin_memory": True,
              "model_config_type": "llama",
          }
      )
  
file_path: axolotl/tests/core/test_trainer_builder.py
imports: import pytest
  from axolotl.core.trainer_builder import HFDPOTrainerBuilder
  from axolotl.utils.dict import DictDefault
  from axolotl.utils.models import load_model, load_tokenizer
label_desc: Use image node_id 1 for calling a global function with example usage: fixture_cfg() and returns: DictDefault