






# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel  # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline  # noqa: F401


deprecate(
    '''stable diffusion controlnet''',
    '''0.22.0''',
    '''Importing `StableDiffusionControlNetPipeline` or `MultiControlNetModel` from diffusers.pipelines.stable_diffusion.pipeline_stable_diffusion_controlnet is deprecated. Please import `from diffusers import StableDiffusionControlNetPipeline` instead.''',
    standard_warn=False,
    stacklevel=3,
)







import os
import sys

__a:     Union[str, Any]   					=					os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)


from transformers import (
    AutoConfig,
    AutoModel,
    AutoModelForCausalLM,
    AutoModelForMaskedLM,
    AutoModelForQuestionAnswering,
    AutoModelForSequenceClassification,
    AutoTokenizer,
    add_start_docstrings,
)


__a:     Union[str, Any]   					=					[
    '''torch''',
    '''numpy''',
    '''tokenizers''',
    '''filelock''',
    '''requests''',
    '''tqdm''',
    '''regex''',
    '''sentencepiece''',
    '''sacremoses''',
    '''importlib_metadata''',
    '''huggingface_hub''',
]




@add_start_docstrings(AutoConfig.__doc__ )
def       _SCREAMING_SNAKE_CASE (							*__snake_case   ,      **__snake_case )				->						Union[str, Any]:
       return AutoConfig.from_pretrained(*__snake_case   ,      **__snake_case )




@add_start_docstrings(AutoTokenizer.__doc__ )
def       _SCREAMING_SNAKE_CASE (							*__snake_case   ,      **__snake_case )				->						Any:
       return AutoTokenizer.from_pretrained(*__snake_case   ,      **__snake_case )




@add_start_docstrings(AutoModel.__doc__ )
def       _SCREAMING_SNAKE_CASE (							*__snake_case   ,      **__snake_case )				->						Tuple:
       return AutoModel.from_pretrained(*__snake_case   ,      **__snake_case )




@add_start_docstrings(AutoModelForCausalLM.__doc__ )
def       _SCREAMING_SNAKE_CASE (							*__snake_case   ,      **__snake_case )				->						Tuple:
       return AutoModelForCausalLM.from_pretrained(*__snake_case   ,      **__snake_case )




@add_start_docstrings(AutoModelForMaskedLM.__doc__ )
def       _SCREAMING_SNAKE_CASE (							*__snake_case   ,      **__snake_case )				->						Optional[Any]:
       return AutoModelForMaskedLM.from_pretrained(*__snake_case   ,      **__snake_case )




@add_start_docstrings(AutoModelForSequenceClassification.__doc__ )
def       _SCREAMING_SNAKE_CASE (							*__snake_case   ,      **__snake_case )				->						List[str]:
       return AutoModelForSequenceClassification.from_pretrained(*__snake_case   ,      **__snake_case )





@add_start_docstrings(AutoModelForQuestionAnswering.__doc__ )
def       _SCREAMING_SNAKE_CASE (							*__snake_case   ,      **__snake_case )				->						List[Any]:
       return AutoModelForQuestionAnswering.from_pretrained(*__snake_case   ,      **__snake_case )