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						:   int         =			True
except (ImportError, AttributeError):
				__SCREAMING_SNAKE_CASE						:   List[str]         =			object
				def  snake_case						(*__lowercase ,      **__lowercase						)	->	Tuple:

										'''simple docstring'''



										pass

				__SCREAMING_SNAKE_CASE						:   Optional[int]         =			False


__SCREAMING_SNAKE_CASE						:   Any         =			logging.get_logger('transformers-cli/serving')
def  snake_case						(__lowercase						)	->	List[Any]:

						'''simple docstring'''



						_snake_case						:					List[Any]    =   pipeline(
						    task=args.task ,      model=args.model if args.model else None ,      config=args.config ,      tokenizer=args.tokenizer ,      device=args.device ,      )
						return ServeCommand(__lowercase ,      args.host ,      args.port ,      args.workers						)



class        lowercase_   (					__snake_case		):
							_lowerCamelCase						=		42




class        lowercase_   (					__snake_case		):
							_lowerCamelCase						=		42
							_lowerCamelCase						=		42




class        lowercase_   (					__snake_case		):
							_lowerCamelCase						=		42




class        lowercase_   (					__snake_case		):
							_lowerCamelCase						=		42




class        lowercase_   (					__snake_case		):



							@staticmethod
							def 	UpperCamelCase	(						lowercase_    ):
													_snake_case						:					Any    =   parser.add_parser(
													    "serve"				,    help="CLI tool to run inference requests through REST and GraphQL endpoints."    )
													serve_parser.add_argument(
													    "--task"				,    type=lowercase_				,    choices=get_supported_tasks()				,    help="The task to run the pipeline on"				,    )
													serve_parser.add_argument("--host"				,    type=lowercase_				,    default="localhost"				,    help="Interface the server will listen on."    )
													serve_parser.add_argument("--port"				,    type=lowercase_				,    default=8_888				,    help="Port the serving will listen to."    )
													serve_parser.add_argument("--workers"				,    type=lowercase_				,    default=1				,    help="Number of http workers"    )
													serve_parser.add_argument("--model"				,    type=lowercase_				,    help="Model's name or path to stored model."    )
													serve_parser.add_argument("--config"				,    type=lowercase_				,    help="Model's config name or path to stored model."    )
													serve_parser.add_argument("--tokenizer"				,    type=lowercase_				,    help="Tokenizer name to use."    )
													serve_parser.add_argument(
													    "--device"				,    type=lowercase_				,    default=-1				,    help="Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)"				,    )
													serve_parser.set_defaults(func=lowercase_    )



							def __init__(						self				,    lowercase_				,    lowercase_				,    lowercase_				,    lowercase_    ):
													_snake_case						:					Dict    =   pipeline

													_snake_case						:					Any    =   host
													_snake_case						:					List[Any]    =   port
													_snake_case						:					Optional[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}"""    )
																			_snake_case						:					List[str]    =   FastAPI(
																			    routes=[
																			        APIRoute(
																			            "/"				,    self.model_info				,    response_model=lowercase_				,    response_class=lowercase_				,    methods=["GET"]				,    ),
																			        APIRoute(
																			            "/tokenize"				,    self.tokenize				,    response_model=lowercase_				,    response_class=lowercase_				,    methods=["POST"]				,    ),
																			        APIRoute(
																			            "/detokenize"				,    self.detokenize				,    response_model=lowercase_				,    response_class=lowercase_				,    methods=["POST"]				,    ),
																			        APIRoute(
																			            "/forward"				,    self.forward				,    response_model=lowercase_				,    response_class=lowercase_				,    methods=["POST"]				,    ),
																			    ]				,    timeout=600				,    )



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



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



							def 	UpperCamelCase	(						self				,    lowercase_ = Body(lowercase_				,    embed=lowercase_    )				,    lowercase_ = Body(lowercase_				,    embed=lowercase_    )    ):
													try:
																			_snake_case						:					Any    =   self._pipeline.tokenizer.tokenize(lowercase_    )

																			if return_ids:
																									_snake_case						:					int    =   self._pipeline.tokenizer.convert_tokens_to_ids(lowercase_    )
																									return ServeTokenizeResult(tokens=lowercase_				,    tokens_ids=lowercase_    )
																			else:
																									return ServeTokenizeResult(tokens=lowercase_    )

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



							def 	UpperCamelCase	(						self				,    lowercase_ = Body(lowercase_				,    embed=lowercase_    )				,    lowercase_ = Body(lowercase_				,    embed=lowercase_    )				,    lowercase_ = Body(lowercase_				,    embed=lowercase_    )				,    ):
													try:
																			_snake_case						:					List[Any]    =   self._pipeline.tokenizer.decode(lowercase_				,    lowercase_				,    lowercase_    )
																			return ServeDeTokenizeResult(model=""				,    text=lowercase_    )
													except Exception as e:
																			raise HTTPException(status_code=500				,    detail={"model": "", "error": str(lowercase_    )}    )



							async def 	UpperCamelCase	(						self				,    lowercase_=Body(lowercase_				,    embed=lowercase_    )    ):

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

													try:
																			# Forward through the model
																			_snake_case						:					str    =   self._pipeline(lowercase_    )
																			return ServeForwardResult(output=lowercase_    )
													except Exception as e:
																			raise HTTPException(500				,    {"error": str(lowercase_    )}    )
from __future__ import annotations

from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass



@dataclass
class        lowercase_   :
							_lowerCamelCase						=		42
							_lowerCamelCase						=		42




class        lowercase_   :



							def __init__(						self				,    lowercase_    ):
													_snake_case						:					list[list[Edge]]    =   [[] for _ in range(lowercase_    )]
													_snake_case						:					Union[str, Any]    =   size



							def __getitem__(						self				,    lowercase_    ):
													return iter(self._graph[vertex]    )



							@property
							def 	UpperCamelCase	(						self    ):
													return self._size



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_				,    lowercase_    ):
													if weight not in (0, 1):
																			raise ValueError("Edge weight must be either 0 or 1."    )

													if to_vertex < 0 or to_vertex >= self.size:
																			raise ValueError("Vertex indexes must be in [0; size)."    )

													self._graph[from_vertex].append(Edge(lowercase_				,    lowercase_    )    )



							def 	UpperCamelCase	(						self				,    lowercase_				,    lowercase_    ):
													_snake_case						:					Optional[int]    =   deque([start_vertex]    )
													_snake_case						:					list[int | None]    =   [None] * self.size
													_snake_case						:					Tuple    =   0

													while queue:
																			_snake_case						:					List[Any]    =   queue.popleft()
																			_snake_case						:					Tuple    =   distances[current_vertex]
																			if current_distance is None:
																									continue

																			for edge in self[current_vertex]:
																									_snake_case						:					Dict    =   current_distance + edge.weight
																									_snake_case						:					str    =   distances[edge.destination_vertex]
																									if (
																									    isinstance(lowercase_				,    lowercase_    )
																									    and new_distance >= dest_vertex_distance
																									):
																															continue
																									_snake_case						:					List[Any]    =   new_distance
																									if edge.weight == 0:
																															queue.appendleft(edge.destination_vertex    )
																									else:
																															queue.append(edge.destination_vertex    )

													if distances[finish_vertex] is None:
																			raise ValueError("No path from start_vertex to finish_vertex."    )

													return distances[finish_vertex]


if __name__ == "__main__":
				import doctest

				doctest.testmod()