"""simple docstring"""






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

       __lowerCAmelCase       :			str   	=True
except (ImportError, AttributeError):
       __lowerCAmelCase       :			Any   	=object


       def      UpperCAmelCase__			(							*lowerCAmelCase__	:Union[str, Any]   ,						**lowerCAmelCase__	:int						)					->       Any:
             '''simple docstring'''


             pass






       __lowerCAmelCase       :			Dict   	=False


__lowerCAmelCase       :			Any   	=logging.get_logger("""transformers-cli/serving""")


def      UpperCAmelCase__			(							lowerCAmelCase__	:Namespace						)					->       str:
      '''simple docstring'''


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





class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  dict






class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  List[str]
      snake_case__     :  Optional[List[int]]






class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  str






class 					_A		(			lowerCAmelCase      ):
      snake_case__     :  Any






class 					_A		(			lowerCAmelCase      ):

      @staticmethod
      def 							A__			(		__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      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						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase						,			__lowerCAmelCase		):







            """simple docstring"""



            lowercase								=      pipeline

            lowercase								=      host
            lowercase								=      port
            lowercase								=      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}'		)
                  lowercase								=      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 							A__			(		self		):







            """simple docstring"""



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

      def 							A__			(		self		):







            """simple docstring"""



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

      def 							A__			(		self						,			__lowerCAmelCase = Body(__lowerCAmelCase						,			embed=__lowerCAmelCase		)						,			__lowerCAmelCase = Body(__lowerCAmelCase						,			embed=__lowerCAmelCase		)		):







            """simple docstring"""



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

                  if return_ids:
                        lowercase								=      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 							A__			(		self						,			__lowerCAmelCase = Body(__lowerCAmelCase						,			embed=__lowerCAmelCase		)						,			__lowerCAmelCase = Body(__lowerCAmelCase						,			embed=__lowerCAmelCase		)						,			__lowerCAmelCase = Body(__lowerCAmelCase						,			embed=__lowerCAmelCase		)						,			):







            """simple docstring"""



            try:
                  lowercase								=      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 							A__			(		self						,			__lowerCAmelCase=Body(__lowerCAmelCase						,			embed=__lowerCAmelCase		)		):







            """simple docstring"""



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

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




"""simple docstring"""






from __future__ import annotations


def      UpperCAmelCase__			(							lowerCAmelCase__	:dict   ,						lowerCAmelCase__	:str						)					->       set[str]:
      '''simple docstring'''


      lowercase				,				lowercase								=      set(lowerCAmelCase__						), [start]

      while stack:
            lowercase								=      stack.pop()
            explored.add(lowerCAmelCase__						)
            # Differences from BFS:
            # 1) pop last element instead of first one
            # 2) add adjacent elements to stack without exploring them
            for adj in reversed(graph[v]						):
                  if adj not in explored:
                        stack.append(lowerCAmelCase__						)
      return explored


__lowerCAmelCase       :			str   	={
    """A""": ["""B""", """C""", """D"""],
    """B""": ["""A""", """D""", """E"""],
    """C""": ["""A""", """F"""],
    """D""": ["""B""", """D"""],
    """E""": ["""B""", """F"""],
    """F""": ["""C""", """E""", """G"""],
    """G""": ["""F"""],
}

if __name__ == "__main__":
       import doctest

       doctest.testmod()
       print(depth_first_search(G, """A"""))



