





from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional

from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand


try:
      from fastapi import Body, FastAPI, HTTPException
      from fastapi.routing import APIRoute
      from pydantic import BaseModel
      from starlette.responses import JSONResponse
      from uvicorn import run

      SCREAMING_SNAKE_CASE_		     = True
except (ImportError, AttributeError):
      SCREAMING_SNAKE_CASE_		     = object



      def      __lowercase     (   *_SCREAMING_SNAKE_CASE				,		**_SCREAMING_SNAKE_CASE			)				->     Tuple:


            '''simple docstring'''


            pass



      SCREAMING_SNAKE_CASE_		     = False


SCREAMING_SNAKE_CASE_		     = logging.get_logger("""transformers-cli/serving""")



def      __lowercase     (   _SCREAMING_SNAKE_CASE			)				->     Optional[int]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE	=		pipeline(
          task=args.task				,		model=args.model if args.model else None				,		config=args.config				,		tokenizer=args.tokenizer				,		device=args.device				,		)
      return ServeCommand(_SCREAMING_SNAKE_CASE				,		args.host				,		args.port				,		args.workers			)

class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

     __snake_case					:			dict

class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

     __snake_case					:			List[str]
     __snake_case					:			Optional[List[int]]

class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

     __snake_case					:			str

class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

     __snake_case					:			Any

class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

     @staticmethod
     def        SCREAMING_SNAKE_CASE__						(							lowerCamelCase__		:					ArgumentParser )  ->	Optional[Any]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		parser.add_parser(
               """serve"""		,help="""CLI tool to run inference requests through REST and GraphQL endpoints.""" )
           serve_parser.add_argument(
               """--task"""		,type=lowerCamelCase__		,choices=get_supported_tasks()		,help="""The task to run the pipeline on"""		,)
           serve_parser.add_argument("""--host"""		,type=lowerCamelCase__		,default="""localhost"""		,help="""Interface the server will listen on.""" )
           serve_parser.add_argument("""--port"""		,type=lowerCamelCase__		,default=8888		,help="""Port the serving will listen to.""" )
           serve_parser.add_argument("""--workers"""		,type=lowerCamelCase__		,default=1		,help="""Number of http workers""" )
           serve_parser.add_argument("""--model"""		,type=lowerCamelCase__		,help="""Model's name or path to stored model.""" )
           serve_parser.add_argument("""--config"""		,type=lowerCamelCase__		,help="""Model's config name or path to stored model.""" )
           serve_parser.add_argument("""--tokenizer"""		,type=lowerCamelCase__		,help="""Tokenizer name to use.""" )
           serve_parser.add_argument(
               """--device"""		,type=lowerCamelCase__		,default=-1		,help="""Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)"""		,)
           serve_parser.set_defaults(func=lowerCamelCase__ )






     def __init__(							self		:					List[str]		,lowerCamelCase__		:					Pipeline		,lowerCamelCase__		:					str		,lowerCamelCase__		:					int		,lowerCamelCase__		:					int )  ->	str:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE	=		pipeline

           SCREAMING_SNAKE_CASE	=		host
           SCREAMING_SNAKE_CASE	=		port
           SCREAMING_SNAKE_CASE	=		workers

           if not _serve_dependencies_installed:
                 raise RuntimeError(
                     """Using serve command requires FastAPI and uvicorn. """
                     """Please install transformers with [serving]: pip install \"transformers[serving]\"."""
                     """Or install FastAPI and uvicorn separately.""" )
           else:
                 logger.info(F"""Serving model over {host}:{port}""" )
                 SCREAMING_SNAKE_CASE	=		FastAPI(
                     routes=[
                         APIRoute(
                             """/"""		,self.model_info		,response_model=lowerCamelCase__		,response_class=lowerCamelCase__		,methods=["""GET"""]		,),
                         APIRoute(
                             """/tokenize"""		,self.tokenize		,response_model=lowerCamelCase__		,response_class=lowerCamelCase__		,methods=["""POST"""]		,),
                         APIRoute(
                             """/detokenize"""		,self.detokenize		,response_model=lowerCamelCase__		,response_class=lowerCamelCase__		,methods=["""POST"""]		,),
                         APIRoute(
                             """/forward"""		,self.forward		,response_model=lowerCamelCase__		,response_class=lowerCamelCase__		,methods=["""POST"""]		,),
                     ]		,timeout=600		,)






     def        SCREAMING_SNAKE_CASE__						(							self		:					List[Any] )  ->	str:




           '''simple docstring'''


           run(self._app		,host=self.host		,port=self.port		,workers=self.workers )






     def        SCREAMING_SNAKE_CASE__						(							self		:					Optional[Any] )  ->	List[str]:




           '''simple docstring'''


           return ServeModelInfoResult(infos=vars(self._pipeline.model.config ) )






     def        SCREAMING_SNAKE_CASE__						(							self		:					Dict		,lowerCamelCase__		:					str = Body(lowerCamelCase__		,embed=lowerCamelCase__ )		,lowerCamelCase__		:					bool = Body(lowerCamelCase__		,embed=lowerCamelCase__ ) )  ->	Any:




           '''simple docstring'''


           try:
                 SCREAMING_SNAKE_CASE	=		self._pipeline.tokenizer.tokenize(lowerCamelCase__ )

                 if return_ids:
                       SCREAMING_SNAKE_CASE	=		self._pipeline.tokenizer.convert_tokens_to_ids(lowerCamelCase__ )
                       return ServeTokenizeResult(tokens=lowerCamelCase__		,tokens_ids=lowerCamelCase__ )
                 else:
                       return ServeTokenizeResult(tokens=lowerCamelCase__ )

           except Exception as e:
                 raise HTTPException(status_code=500		,detail={"""model""": """""", """error""": str(lowerCamelCase__ )} )






     def        SCREAMING_SNAKE_CASE__						(							self		:					List[Any]		,lowerCamelCase__		:					List[int] = Body(lowerCamelCase__		,embed=lowerCamelCase__ )		,lowerCamelCase__		:					bool = Body(lowerCamelCase__		,embed=lowerCamelCase__ )		,lowerCamelCase__		:					bool = Body(lowerCamelCase__		,embed=lowerCamelCase__ )		,)  ->	int:




           '''simple docstring'''


           try:
                 SCREAMING_SNAKE_CASE	=		self._pipeline.tokenizer.decode(lowerCamelCase__		,lowerCamelCase__		,lowerCamelCase__ )
                 return ServeDeTokenizeResult(model=""""""		,text=lowerCamelCase__ )
           except Exception as e:
                 raise HTTPException(status_code=500		,detail={"""model""": """""", """error""": str(lowerCamelCase__ )} )






     async def        SCREAMING_SNAKE_CASE__						(							self		:					int		,lowerCamelCase__		:					str=Body(lowerCamelCase__		,embed=lowerCamelCase__ ) )  ->	Optional[Any]:




           '''simple docstring'''


           if len(lowerCamelCase__ ) == 0:
                 return ServeForwardResult(output=[]		,attention=[] )

           try:
                 # Forward through the model
                 SCREAMING_SNAKE_CASE	=		self._pipeline(lowerCamelCase__ )
                 return ServeForwardResult(output=lowerCamelCase__ )
           except Exception as e:
                 raise HTTPException(500		,{"""error""": str(lowerCamelCase__ )} )









import warnings

from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor


SCREAMING_SNAKE_CASE_		     = logging.get_logger(__name__)

class 	UpperCamelCase__				(   lowerCAmelCase_     ):



     '''simple docstring'''

     def __init__(							self		:					int		,*lowerCamelCase__		:					int		,**lowerCamelCase__		:					List[Any] )  ->	None:




           '''simple docstring'''


           warnings.warn(
               """The class DeformableDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
               """ Please use DeformableDetrImageProcessor instead."""		,lowerCamelCase__		,)
           super().__init__(*lowerCamelCase__		,**lowerCamelCase__ )


