ORPOTrainer crashes due to pickling failure if dataloader_num_workers > 0

[kiratp]

Reproduction

 training_arguments = TrainingArguments(
        output_dir,
        overwrite_output_dir=False,
        per_device_train_batch_size=script_args.per_device_train_batch_size,
        gradient_accumulation_steps=script_args.gradient_accumulation_steps,
        optim=script_args.optim,
        save_steps=script_args.save_steps,
        logging_steps=script_args.logging_steps,
        learning_rate=script_args.learning_rate,
        fp16=script_args.fp16,
        bf16=script_args.bf16,
        max_steps=script_args.max_steps,
        warmup_ratio=script_args.warmup_ratio,
        group_by_length=script_args.group_by_length,
        lr_scheduler_type=script_args.lr_scheduler_type,
        gradient_checkpointing=script_args.gradient_checkpointing,
        ddp_find_unused_parameters=False,
        dataloader_num_workers=script_args.num_dataset_proc_workers,
        remove_unused_columns=False,
        num_train_epochs=script_args.num_train_epochs,
        eval_strategy=script_args.eval_strategy,
        eval_steps=script_args.eval_steps,
        eval_accumulation_steps=script_args.eval_accumulation_steps,
        resume_from_checkpoint=True,
        # half_precision_backend=half_precision_backend,
        dataloader_drop_last=True,
        **fsdp_training_args,
    )
// ...

grpo_config = GRPOConfig(
        max_prompt_length=script_args.max_prompt_length,
        num_generations=8,
        temperature=1.0,
        max_completion_length=script_args.max_seq_length,
        use_vllm=False,
        vllm_device="auto",
        vllm_gpu_memory_utilization=0.9,
        beta=0.04,
        **training_arguments.to_dict(),
    )

    # Doing this makes things work again
    # grpo_config.dataloader_num_workers = 0

    return GRPOTrainer(
        model,
        reward_funcs=grpo_reward_func_direct
        if script_args.mode == Mode.GRPO_DIRECT
        else grpo_reward_func_with_thinking,
        train_dataset=dataset["train"],
        eval_dataset=dataset["validation"],
        peft_config=peft_config,
        processing_class=tokenizer,
        args=grpo_config,
        # compute_metrics=compute_metrics,
    )

outputs:

tarting Training
  0%|                                                                                                                                                                                                                       | 0/1000 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/Users/kiratpandya/code/osmos/osmos/python/agents-trainer/train-trl.py", line 566, in <module>
    trainer.train()
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/site-packages/transformers/trainer.py", line 2171, in train
    return inner_training_loop(
           ^^^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/site-packages/transformers/trainer.py", line 2480, in _inner_training_loop
    batch_samples, num_items_in_batch = self.get_batch_samples(epoch_iterator, num_batches)
                                        ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/site-packages/transformers/trainer.py", line 5153, in get_batch_samples
    batch_samples += [next(epoch_iterator)]
                      ^^^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/site-packages/accelerate/data_loader.py", line 560, in __iter__
    dataloader_iter = self.base_dataloader.__iter__()
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/site-packages/torch/utils/data/dataloader.py", line 484, in __iter__
    return self._get_iterator()
           ^^^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/site-packages/torch/utils/data/dataloader.py", line 415, in _get_iterator
    return _MultiProcessingDataLoaderIter(self)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/site-packages/torch/utils/data/dataloader.py", line 1138, in __init__
    w.start()
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/multiprocessing/process.py", line 121, in start
    self._popen = self._Popen(self)
                  ^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/multiprocessing/context.py", line 224, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/multiprocessing/context.py", line 289, in _Popen
    return Popen(process_obj)
           ^^^^^^^^^^^^^^^^^^
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/multiprocessing/popen_spawn_posix.py", line 32, in __init__
    super().__init__(process_obj)
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/multiprocessing/popen_fork.py", line 19, in __init__
    self._launch(process_obj)
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/multiprocessing/popen_spawn_posix.py", line 47, in _launch
    reduction.dump(process_obj, fp)
  File "/Users/kiratpandya/miniconda3/envs/agents-trainer/lib/python3.12/multiprocessing/reduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
AttributeError: Can't get local object 'GRPOTrainer.__init__.<locals>.data_collator'
  0%|          | 0/1000 [00:00<?, ?it/s]```


### System Info

- Platform: macOS-14.6.1-arm64-arm-64bit
- Python version: 3.12.8
- PyTorch version: 2.6.0.dev20241112
- CUDA device(s): not available
- Transformers version: 4.48.2
- Accelerate version: 1.3.0
- Accelerate config:
  - compute_environment: LOCAL_MACHINE
  - distributed_type: NO
  - mixed_precision: no
  - use_cpu: False
  - debug: False
  - num_processes: 1
  - machine_rank: 0
  - num_machines: 1
  - rdzv_backend: static
  - same_network: True
  - main_training_function: main
  - enable_cpu_affinity: False
  - downcast_bf16: no
  - tpu_use_cluster: False
  - tpu_use_sudo: False
  - tpu_env: []
- Datasets version: 3.2.0
- HF Hub version: 0.28.1
- TRL version: 0.14.0.dev0
- bitsandbytes version: not installed
- DeepSpeed version: not installed
- Diffusers version: not installed
- Liger-Kernel version: not installed
- LLM-Blender version: not installed
- OpenAI version: not installed
- PEFT version: 0.14.0

### Checklist

- [x] I have checked that my issue isn't already filed (see [open issues](https://github.com/huggingface/trl/issues?q=is%3Aissue))
- [x] I have included my system information
- [x] Any code provided is minimal, complete, and reproducible ([more on MREs](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/creating-and-highlighting-code-blocks))
- [x] Any code provided is properly formatted in code blocks, (no screenshot, [more on code blocks](https://docs.github.com/en/get-started/writing-on-github/working-with-advanced-formatting/creating-and-highlighting-code-blocks))
- [x] Any traceback provided is complete