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import inspect
from copy import deepcopy
from functools import update_wrapper
from types import MethodType
from .peft_model import PeftModel
def update_forward_signature(model: PeftModel) -> None:
"""
Args:
Updates the forward signature of the PeftModel to include parents class signature
model (`PeftModel`): Peft model to update the forward signature
Example:
```python
>>> from transformers import WhisperForConditionalGeneration
>>> from peft import get_peft_model, LoraConfig, update_forward_signature
>>> model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-tiny.en")
>>> peft_config = LoraConfig(r=8, lora_alpha=32, lora_dropout=0.1, target_modules=["q_proj", "v_proj"])
>>> peft_model = get_peft_model(model, peft_config)
>>> update_forward_signature(peft_model)
```
"""
# Only update signature when the current forward signature only has *args and **kwargs
current_signature = inspect.signature(model.forward)
if (
len(current_signature.parameters) == 2
and "args" in current_signature.parameters
and "kwargs" in current_signature.parameters
):
forward = deepcopy(model.forward.__func__)
update_wrapper(
forward, type(model.get_base_model()).forward, assigned=("__doc__", "__name__", "__annotations__")
)
model.forward = MethodType(forward, model)
def update_generate_signature(model: PeftModel) -> None:
"""
Args:
Updates the generate signature of a PeftModel with overriding generate to include parents class signature
model (`PeftModel`): Peft model to update the generate signature
Example:
```python
>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
>>> from peft import get_peft_model, LoraConfig, TaskType, update_generate_signature
>>> model_name_or_path = "bigscience/mt0-large"
>>> tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
>>> model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
>>> peft_config = LoraConfig(
... task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1
... )
>>> peft_model = get_peft_model(model, peft_config)
>>> update_generate_signature(peft_model)
>>> help(peft_model.generate)
```
"""
if not hasattr(model, "generate"):
return
current_signature = inspect.signature(model.generate)
if (
len(current_signature.parameters) == 2
and "args" in current_signature.parameters
and "kwargs" in current_signature.parameters
) or (len(current_signature.parameters) == 1 and "kwargs" in current_signature.parameters):
generate = deepcopy(model.generate.__func__)
update_wrapper(
generate,
type(model.get_base_model()).generate,
assigned=("__doc__", "__name__", "__annotations__"),
)
model.generate = MethodType(generate, model)
def update_signature(model: PeftModel, method: str = "all") -> None:
"""
Args:
Updates the signature of a PeftModel include parents class signature for forward or generate method
model (`PeftModel`): Peft model to update generate or forward signature method (`str`): method to update
signature choose one of "forward", "generate", "all"
Example:
```python
>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
>>> from peft import get_peft_model, LoraConfig, TaskType, update_signature
>>> model_name_or_path = "bigscience/mt0-large"
>>> tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
>>> model = AutoModelForSeq2SeqLM.from_pretrained(model_name_or_path)
>>> peft_config = LoraConfig(
... task_type=TaskType.SEQ_2_SEQ_LM, inference_mode=False, r=8, lora_alpha=32, lora_dropout=0.1
... )
>>> peft_model = get_peft_model(model, peft_config)
>>> update_signature(peft_model)
>>> help(peft_model.generate)
```
"""
if method == "forward":
update_forward_signature(model)
elif method == "generate":
update_generate_signature(model)
elif method == "all":
update_forward_signature(model)
update_generate_signature(model)
else:
raise ValueError(f"method {method} is not supported please choose one of ['forward', 'generate', 'all']")
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