# Copyright (c) Alibaba, Inc. and its affiliates.
# Part of the implementation is borrowed from huggingface/transformers.

import inspect
from types import FunctionType, MethodType
from typing import List, Union

from torch.nn import Module
from transformers.trainer_callback import TrainerCallback
from transformers.trainer_utils import (EvaluationStrategy, FSDPOption, HPSearchBackend, HubStrategy, IntervalStrategy,
                                        SchedulerType)

from swift.utils import get_logger

try:
    # https://github.com/huggingface/transformers/pull/25702
    from transformers.trainer_utils import ShardedDDPOption
except ImportError:
    ShardedDDPOption = None

logger = get_logger()


def can_return_loss(model: Module) -> bool:
    """Check if a given model can return loss."""
    signature = inspect.signature(model.forward)
    for p in signature.parameters:
        if p == 'return_loss' and signature.parameters[p].default is True:
            return True
    return False


def find_labels(model: Module) -> List[str]:
    """Find the labels used by a given model."""
    model_name = model.__class__.__name__
    signature = inspect.signature(model.forward)
    if 'QuestionAnswering' in model_name:
        return [p for p in signature.parameters if 'label' in p or p in ('start_positions', 'end_positions')]
    else:
        return [p for p in signature.parameters if 'label' in p]


def get_function(method_or_function: Union[MethodType, FunctionType]) -> FunctionType:
    if isinstance(method_or_function, MethodType):
        method_or_function = method_or_function.__func__
    return method_or_function


def is_instance_of_ms_model(model: Module) -> bool:
    """avoid import modelscope: circular dependency problem"""
    for m_cls in model.__class__.__mro__:
        cls_name = m_cls.__name__
        cls_module = m_cls.__module__
        if cls_name == 'Model' and cls_module.startswith('modelscope'):
            return True
    return False
