




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

     _UpperCAmelCase		:  Any	=   True
except (ImportError, AttributeError):
     _UpperCAmelCase		:  Any	=   object



     def 					UpperCAmelCase__     (   *lowerCamelCase,	**lowerCamelCase      ):
       pass







     _UpperCAmelCase		:  Any	=   False


_UpperCAmelCase		:  Dict	=   logging.get_logger("transformers-cli/serving")



def 					UpperCAmelCase__     (   lowerCamelCase      ):
  lowercase			:Optional[int]							=  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       __lowerCAmelCase				(							lowerCAmelCase):
       _a           =  42







class       __lowerCAmelCase				(							lowerCAmelCase):
       _a           =  42
       _a           =  42







class       __lowerCAmelCase				(							lowerCAmelCase):
       _a           =  42







class       __lowerCAmelCase				(							lowerCAmelCase):
       _a           =  42







class       __lowerCAmelCase				(							lowerCAmelCase):






       @staticmethod
       def     SCREAMING_SNAKE_CASE			(      _lowerCAmelCase:    ArgumentParser ):
         lowercase			:Optional[int]							=  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=88_88				,    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:    Any				,    _lowerCAmelCase:    Pipeline				,    _lowerCAmelCase:    str				,    _lowerCAmelCase:    int				,    _lowerCAmelCase:    int ):
         lowercase			:Any							=  pipeline

         lowercase			:Optional[Any]							=  host
         lowercase			:Dict							=  port
         lowercase			:List[Any]							=  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			:List[str]							=  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=6_00				,    )






       def     SCREAMING_SNAKE_CASE			(      self:    Any ):
         run(self._app				,    host=self.host				,    port=self.port				,    workers=self.workers )






       def     SCREAMING_SNAKE_CASE			(      self:    Union[str, Any] ):
         return ServeModelInfoResult(infos=vars(self._pipeline.model.config ) )






       def     SCREAMING_SNAKE_CASE			(      self:    List[str]				,    _lowerCAmelCase:    str = Body(_lowerCAmelCase				,    embed=_lowerCAmelCase )				,    _lowerCAmelCase:    bool = Body(_lowerCAmelCase				,    embed=_lowerCAmelCase ) ):
         try:
           lowercase			:Optional[int]							=  self._pipeline.tokenizer.tokenize(_lowerCAmelCase )

           if return_ids:
             lowercase			:int							=  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=5_00				,    detail={"model": "", "error": str(_lowerCAmelCase )} )






       def     SCREAMING_SNAKE_CASE			(      self:    str				,    _lowerCAmelCase:    List[int] = Body(_lowerCAmelCase				,    embed=_lowerCAmelCase )				,    _lowerCAmelCase:    bool = Body(_lowerCAmelCase				,    embed=_lowerCAmelCase )				,    _lowerCAmelCase:    bool = Body(_lowerCAmelCase				,    embed=_lowerCAmelCase )				,    ):
         try:
           lowercase			:Optional[Any]							=  self._pipeline.tokenizer.decode(_lowerCAmelCase				,    _lowerCAmelCase				,    _lowerCAmelCase )
           return ServeDeTokenizeResult(model=""				,    text=_lowerCAmelCase )
         except Exception as e:
           raise HTTPException(status_code=5_00				,    detail={"model": "", "error": str(_lowerCAmelCase )} )






       async def     SCREAMING_SNAKE_CASE			(      self:    Any				,    _lowerCAmelCase:    Union[str, Any]=Body(_lowerCAmelCase				,    embed=_lowerCAmelCase ) ):

         # Check we don't have empty string
         if len(_lowerCAmelCase ) == 0:
           return ServeForwardResult(output=[]				,    attention=[] )

         try:
           # Forward through the model
           lowercase			:Optional[int]							=  self._pipeline(_lowerCAmelCase )
           return ServeForwardResult(output=_lowerCAmelCase )
         except Exception as e:
           raise HTTPException(5_00				,    {"error": str(_lowerCAmelCase )} )









def 					UpperCAmelCase__     (   lowerCamelCase,	lowerCamelCase,	lowerCamelCase,	lowerCamelCase      ):
  # Return True if there is node that has not iterated.
  lowercase			:Union[str, Any]							=  [False] * len(lowerCamelCase      )
  lowercase			:Union[str, Any]							=  []
  queue.append(lowerCamelCase      )
  lowercase			:Optional[Any]							=  True

  while queue:
    lowercase			:Optional[Any]							=  queue.pop(0      )
    for ind in range(len(graph[u]      )      ):
      if visited[ind] is False and graph[u][ind] > 0:
        queue.append(lowerCamelCase      )
        lowercase			:Dict							=  True
        lowercase			:Dict							=  u

  return visited[t]



def 					UpperCAmelCase__     (   lowerCamelCase,	lowerCamelCase,	lowerCamelCase      ):
  # This array is filled by BFS and to store path
  lowercase			:Optional[int]							=  [-1] * (len(lowerCamelCase      ))
  lowercase			:int							=  0
  while bfs(lowerCamelCase,	lowerCamelCase,	lowerCamelCase,	lowerCamelCase      ):
    lowercase			:int							=  float("Inf"      )
    lowercase			:Any							=  sink

    while s != source:
      # Find the minimum value in select path
      lowercase			:Any							=  min(lowerCamelCase,	graph[parent[s]][s]      )
      lowercase			:Dict							=  parent[s]

    max_flow += path_flow
    lowercase			:Union[str, Any]							=  sink

    while v != source:
      lowercase			:List[Any]							=  parent[v]
      graph[u][v] -= path_flow
      graph[v][u] += path_flow
      lowercase			:Any							=  parent[v]
  return max_flow


_UpperCAmelCase		:  Optional[Any]	=   [
    [0, 16, 13, 0, 0, 0],
    [0, 0, 10, 12, 0, 0],
    [0, 4, 0, 0, 14, 0],
    [0, 0, 9, 0, 0, 20],
    [0, 0, 0, 7, 0, 4],
    [0, 0, 0, 0, 0, 0],
]

_UpperCAmelCase	,	_UpperCAmelCase		:  Any	=   0, 5







print(ford_fulkerson(graph, source, sink))



