



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 snake_case__  (			*__SCREAMING_SNAKE_CASE			,     **__SCREAMING_SNAKE_CASE )		->							Dict:
					pass

			SCREAMING_SNAKE_CASE     				=						False


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







def snake_case__  (			__SCREAMING_SNAKE_CASE )		->							Tuple:
		UpperCAmelCase_						=				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 	lowerCamelCase      (						lowercase__  ):







					'''simple docstring'''







					lowerCAmelCase_				:    dict





class 	lowerCamelCase      (						lowercase__  ):







					'''simple docstring'''







					lowerCAmelCase_				:    List[str]
					lowerCAmelCase_				:    Optional[List[int]]





class 	lowerCamelCase      (						lowercase__  ):







					'''simple docstring'''







					lowerCAmelCase_				:    str





class 	lowerCamelCase      (						lowercase__  ):







					'''simple docstring'''







					lowerCAmelCase_				:    Any





class 	lowerCamelCase      (						lowercase__  ):







					'''simple docstring'''







					@staticmethod
					def    A__		(			lowerCAmelCase     ):
							UpperCAmelCase_						=				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     ):
							UpperCAmelCase_						=				pipeline

							UpperCAmelCase_						=				host
							UpperCAmelCase_						=				port
							UpperCAmelCase_						=				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}'''     )
									UpperCAmelCase_						=				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     ):
							run(self._app    ,	host=self.host    ,	port=self.port    ,	workers=self.workers     )



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



					def    A__		(			self    ,	lowerCAmelCase = Body(lowerCAmelCase    ,	embed=lowerCAmelCase     )    ,	lowerCAmelCase = Body(lowerCAmelCase    ,	embed=lowerCAmelCase     )     ):
							try:
									UpperCAmelCase_						=				self._pipeline.tokenizer.tokenize(lowerCAmelCase     )

									if return_ids:
											UpperCAmelCase_						=				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     )    ,	):
							try:
									UpperCAmelCase_						=				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     )     ):

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

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






import heapq as hq
import math
from collections.abc import Iterator



class 	lowerCamelCase      :







					'''simple docstring'''







					def __init__(			self    ,	lowerCAmelCase     ):
							UpperCAmelCase_						=				str(id_     )
							UpperCAmelCase_						=				None
							UpperCAmelCase_						=				None
							UpperCAmelCase_						=				[]
							UpperCAmelCase_						=				{}  # {vertex:distance}



					def __lt__(			self    ,	lowerCAmelCase     ):
							return self.key < other.key



					def __repr__(			self     ):
							return self.id



					def    A__		(			self    ,	lowerCAmelCase     ):
							self.neighbors.append(lowerCAmelCase     )



					def    A__		(			self    ,	lowerCAmelCase    ,	lowerCAmelCase     ):
							UpperCAmelCase_						=				weight







def snake_case__  (			__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )		->							Optional[int]:
		# add the neighbors:
		graph[a - 1].add_neighbor(graph[b - 1] )
		graph[b - 1].add_neighbor(graph[a - 1] )
		# add the edges:
		graph[a - 1].add_edge(graph[b - 1]			,     __SCREAMING_SNAKE_CASE )
		graph[b - 1].add_edge(graph[a - 1]			,     __SCREAMING_SNAKE_CASE )







def snake_case__  (			__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )		->							list:
		UpperCAmelCase_						=				[]
		for u in graph:
				UpperCAmelCase_						=				math.inf
				UpperCAmelCase_						=				None
		UpperCAmelCase_						=				0
		UpperCAmelCase_						=				graph[:]
		while q:
				UpperCAmelCase_						=				min(__SCREAMING_SNAKE_CASE )
				q.remove(__SCREAMING_SNAKE_CASE )
				for v in u.neighbors:
						if (v in q) and (u.edges[v.id] < v.key):
								UpperCAmelCase_						=				u
								UpperCAmelCase_						=				u.edges[v.id]
		for i in range(1			,     len(__SCREAMING_SNAKE_CASE ) ):
				a.append((int(graph[i].id ) + 1, int(graph[i].pi.id ) + 1) )
		return a







def snake_case__  (			__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )		->							Iterator[tuple]:
		for u in graph:
				UpperCAmelCase_						=				math.inf
				UpperCAmelCase_						=				None
		UpperCAmelCase_						=				0

		UpperCAmelCase_						=				list(__SCREAMING_SNAKE_CASE )
		hq.heapify(__SCREAMING_SNAKE_CASE )

		while h:
				UpperCAmelCase_						=				hq.heappop(__SCREAMING_SNAKE_CASE )
				for v in u.neighbors:
						if (v in h) and (u.edges[v.id] < v.key):
								UpperCAmelCase_						=				u
								UpperCAmelCase_						=				u.edges[v.id]
								hq.heapify(__SCREAMING_SNAKE_CASE )

		for i in range(1			,     len(__SCREAMING_SNAKE_CASE ) ):
				yield (int(graph[i].id ) + 1, int(graph[i].pi.id ) + 1)







def snake_case__  (			)		->							None:
		pass


if __name__ == "__main__":
			import doctest

			doctest.testmod()

