




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   _SCREAMING_SNAKE_CASE       (							*lowercase_      ,			**lowercase_						)						->		List[str]:
       pass






      SCREAMING_SNAKE_CASE    =	False


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







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		Any:
 A__	=    pipeline(
     task=args.task      ,			model=args.model if args.model else None      ,			config=args.config      ,			tokenizer=args.tokenizer      ,			device=args.device      ,			)
 return ServeCommand(a__      ,			args.host      ,			args.port      ,			args.workers						)




class      UpperCAmelCase_  (						_a							):
    lowercase__						 =				42






class      UpperCAmelCase_  (						_a							):
    lowercase__						 =				42
    lowercase__						 =				42






class      UpperCAmelCase_  (						_a							):
    lowercase__						 =				42






class      UpperCAmelCase_  (						_a							):
    lowercase__						 =				42






class      UpperCAmelCase_  (						_a							):




    @staticmethod
    def 							__magic_name__							(   snake_case_						:	Optional[Any]				)				->							List[str]:




     '''simple docstring'''

     A__	=    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=8_888     ,			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[Any]     ,			snake_case_						:	int     ,			snake_case_						:	str     ,			snake_case_						:	List[Any]     ,			snake_case_						:	Dict				)				->							Dict:




     '''simple docstring'''

     A__	=    pipeline

     A__	=    host
     A__	=    port
     A__	=    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}"""				)
      A__	=    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 							__magic_name__							(   self						:	Any				)				->							Any:




     '''simple docstring'''

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




    def 							__magic_name__							(   self						:	List[str]				)				->							Tuple:




     '''simple docstring'''

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




    def 							__magic_name__							(   self						:	List[Any]     ,			snake_case_						:	str = Body(__lowerCAmelCase     ,			embed=__lowerCAmelCase				)     ,			snake_case_						:	Any = Body(__lowerCAmelCase     ,			embed=__lowerCAmelCase				)				)				->							Dict:




     '''simple docstring'''

     try:
      A__	=    self._pipeline.tokenizer.tokenize(__lowerCAmelCase				)

      if return_ids:
       A__	=    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 							__magic_name__							(   self						:	Optional[Any]     ,			snake_case_						:	Tuple = Body(__lowerCAmelCase     ,			embed=__lowerCAmelCase				)     ,			snake_case_						:	List[str] = Body(__lowerCAmelCase     ,			embed=__lowerCAmelCase				)     ,			snake_case_						:	Dict = Body(__lowerCAmelCase     ,			embed=__lowerCAmelCase				)     ,			)				->							Optional[int]:




     '''simple docstring'''

     try:
      A__	=    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 							__magic_name__							(   self						:	Tuple     ,			snake_case_						:	Optional[Any]=Body(__lowerCAmelCase     ,			embed=__lowerCAmelCase				)				)				->							int:




     '''simple docstring'''

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

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











"""simple docstring"""



from argparse import ArgumentParser

from .env import EnvironmentCommand







def   _SCREAMING_SNAKE_CASE       (							)						->		List[Any]:
 A__	=    ArgumentParser("Diffusers CLI tool"      ,			usage="diffusers-cli <command> [<args>]"						)
 A__	=    parser.add_subparsers(help="diffusers-cli command helpers"						)

 # Register commands
 EnvironmentCommand.register_subcommand(lowercase_						)

 # Let's go
 A__	=    parser.parse_args()

 if not hasattr(lowercase_      ,			"func"						):
  parser.print_help()
  exit(1						)

 # Run
 A__	=    args.func(lowercase_						)
 service.run()


if __name__ == "__main__":
      main()





