Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Re-training PEFT model fails after loading with Linear4bit error #3833

Closed
thelinuxkid opened this issue Dec 15, 2023 · 0 comments
Closed

Re-training PEFT model fails after loading with Linear4bit error #3833

thelinuxkid opened this issue Dec 15, 2023 · 0 comments
Assignees
Labels
llm Large Language Model related

Comments

@thelinuxkid
Copy link
Contributor

Describe the bug
When attempting to train on top of an already trained model (with new data), loading the model with Python throws the error:

Already found a `peft_config` attribute in the model. This will lead to having multiple adapters in the model. Make sure to know what you are doing!                  [3311/13921]
Traceback (most recent call last):
  File "train_enric_actions.py", line 115, in <module>
    train(config_path, base_model, dataset, model_name, output_directory)
  File "train_enric_actions.py", line 100, in train
    model.train(
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/ludwig/api.py", line 619, in train
    with self.backend.create_trainer(
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/ludwig/backend/base.py", line 293, in create_trainer
    return trainer_cls(config=config, model=model, **kwargs)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/ludwig/trainers/trainer_llm.py", line 418, in __init__
    super().__init__(
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/ludwig/trainers/trainer.py", line 179, in __init__
    self.model.prepare_for_training()
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/ludwig/models/llm.py", line 259, in prepare_for_training
    self.initialize_adapter()
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/ludwig/models/llm.py", line 247, in initialize_adapter
    self.model = get_peft_model(self.model, peft_config)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/mapping.py", line 133, in get_peft_model
    return MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type](model, peft_config, adapter_name=adapter_name)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/peft_model.py", line 1041, in __init__
    super().__init__(model, peft_config, adapter_name)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/peft_model.py", line 123, in __init__
    self.base_model = cls(model, {adapter_name: peft_config}, adapter_name)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/tuners/lora/model.py", line 119, in __init__
    super().__init__(model, config, adapter_name)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/tuners/tuners_utils.py", line 95, in __init__
    self.inject_adapter(self.model, adapter_name)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/tuners/tuners_utils.py", line 252, in inject_adapter
    self._create_and_replace(peft_config, adapter_name, target, target_name, parent, **optional_kwargs)
  File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/tuners/lora/model.py", line 200, in _create_and_replace
    new_module = self._create_new_module(lora_config, adapter_name, target, **kwargs)                                                                                               File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/peft/tuners/lora/model.py", line 286, in _create_new_module
    "compute_dtype": target.compute_dtype,                                                                                                                                          File "/home/ubuntu/.local/share/virtualenvs/ludwig-JgQxVRRw/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1695, in __getattr__
    raise AttributeError(f"'{type(self).__name__}' object has no attribute '{name}'")
AttributeError: 'Linear4bit' object has no attribute 'compute_dtype'

after attempting to load the model as so:

ludwig_model = LudwigModel(config)
ludwig_model.model = LudwigModel.create_model(config)
ludwig.model.load_weights("results/experiment_run_0/model")

To Reproduce
Steps to reproduce the behavior:

  1. Train a single PEFT model
  2. Attempt to retrain again but now loading the already trained model as above
  3. See error

Config:

{
  "model_type": "llm",
  "base_model": "{{base_model}}",
  "generation": {"temperature": 0.1},
  "quantization": {"bits": 4},
  "adapter": {"type": "lora"},
  "prompt": {
    "template": "blas blash"
  },

  "input_features": [
    {
      "name": "context_and_intent",
      "type": "text"
    }
  ],

  "output_features": [
    {
      "name": "action",
      "type": "text",
      "preprocessing":  {
        "fallback_label": "unsure"
      },
      "decoder": {
        "type": "text_extractor",
        "match": {
          "unsure": {
            "type": "contains",
            "value": "unsure"
          },
          "cat1": {
            "type": "contains",
            "value": "cat1"
          }
        }
      }
    }
  ],

  "preprocessing": {
    "split": {
      "type": "random",
      "probabilities": [
        0.95,
        0,
        0.05
      ]
    }
  },

  "trainer": {
    "type": "finetune",
    "epochs": 13,
    "early_stop": -1,
    "optimizer": {
      "type": "paged_adam"
    },
    "weight_decay": 0.1,
    "batch_size": 1,
    "learning_rate": 0.0002,
    "eval_batch_size": 2,
    "learning_rate_scheduler": {
      "decay": "cosine",
      "warmup_fraction": 0.03
    },
    "gradient_accumulation_steps": 16,
    "enable_gradient_checkpointing": true
  }
}

Expected behavior
The training should resume without failure. Thanks to @geoffreyangus for helping me find a workaround by adding the previous training's weights to adapter.pretrained_adapter_weights in the config file.

Environment (please complete the following information):

  • OS: Ubuntu 20.04
  • Version: Cuda 12.1
  • Python version: 3.8.10
  • bitsandbytes 0.40.2
  • ludwig 0.8.6
  • peft 0.7.0
  • transformers 4.35.2
@alexsherstinsky alexsherstinsky added the llm Large Language Model related label Jul 26, 2024
@mhabedank mhabedank closed this as not planned Won't fix, can't repro, duplicate, stale Oct 20, 2024
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
llm Large Language Model related
Projects
None yet
Development

Successfully merging a pull request may close this issue.

3 participants