





"""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  :			List[str]        =       True
except (ImportError, AttributeError):
		_lowerCamelCase  :			int        =       object

		def 		lowercase_      (		*_UpperCAmelCase  ,      **_UpperCAmelCase	):




			"""simple docstring"""






			pass
		_lowerCamelCase  :			Optional[int]        =       False


_lowerCamelCase  :			Optional[Any]        =       logging.get_logger('transformers-cli/serving')

def 		lowercase_      (		_UpperCAmelCase	):




	"""simple docstring"""






	A_  :				int	   =		pipeline(
	    task=args.task  ,      model=args.model if args.model else None  ,      config=args.config  ,      tokenizer=args.tokenizer  ,      device=args.device  ,      )
	return ServeCommand(_UpperCAmelCase  ,      args.host  ,      args.port  ,      args.workers	)

class        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    dict

class        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    List[str]
				__lowerCAmelCase    :    Optional[List[int]]

class        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    str

class        lowercase      (    __UpperCAmelCase):
				__lowerCAmelCase    :    Any

class        lowercase      (    __UpperCAmelCase):







				@staticmethod
				def 					a_  (							_lowerCamelCase   :					ArgumentParser       ):



					"""simple docstring"""

					A_  :				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   :					Optional[Any]      ,     _lowerCamelCase   :					Pipeline      ,     _lowerCamelCase   :					str      ,     _lowerCamelCase   :					int      ,     _lowerCamelCase   :					int       ):



					"""simple docstring"""

					A_  :				Optional[int]	   =		pipeline

					A_  :				Optional[Any]	   =		host
					A_  :				List[Any]	   =		port
					A_  :				List[str]	   =		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_  :				List[Any]	   =		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 					a_  (							self   :					Union[str, Any]       ):



					"""simple docstring"""

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







				def 					a_  (							self   :					Any       ):



					"""simple docstring"""

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







				def 					a_  (							self   :					Union[str, Any]      ,     _lowerCamelCase   :					str = Body(_lowerCamelCase      ,     embed=_lowerCamelCase       )      ,     _lowerCamelCase   :					bool = Body(_lowerCamelCase      ,     embed=_lowerCamelCase       )       ):



					"""simple docstring"""

					try:
						A_  :				Optional[int]	   =		self._pipeline.tokenizer.tokenize(_lowerCamelCase       )

						if return_ids:
							A_  :				str	   =		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 					a_  (							self   :					Any      ,     _lowerCamelCase   :					List[int] = Body(_lowerCamelCase      ,     embed=_lowerCamelCase       )      ,     _lowerCamelCase   :					bool = Body(_lowerCamelCase      ,     embed=_lowerCamelCase       )      ,     _lowerCamelCase   :					bool = Body(_lowerCamelCase      ,     embed=_lowerCamelCase       )      ,     ):



					"""simple docstring"""

					try:
						A_  :				List[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 					a_  (							self   :					str      ,     _lowerCamelCase   :					Optional[int]=Body(_lowerCamelCase      ,     embed=_lowerCamelCase       )       ):



					"""simple docstring"""

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

					try:
						# Forward through the model
						A_  :				Dict	   =		self._pipeline(_lowerCamelCase       )
						return ServeForwardResult(output=_lowerCamelCase       )
					except Exception as e:
						raise HTTPException(5_00      ,     {'''error''': str(_lowerCamelCase       )}       )











"""simple docstring"""

from __future__ import annotations

from collections import namedtuple

def 		lowercase_      (		_UpperCAmelCase  ,      _UpperCAmelCase  ,      _UpperCAmelCase	):




	"""simple docstring"""






	A_  :				int	   =		namedtuple('''result'''  ,      '''name value'''	)
	if (voltage, current, power).count(0	) != 1:
		raise ValueError('''Only one argument must be 0'''	)
	elif power < 0:
		raise ValueError(
		    '''Power cannot be negative in any electrical/electronics system'''	)
	elif voltage == 0:
		return result('''voltage'''  ,      power / current	)
	elif current == 0:
		return result('''current'''  ,      power / voltage	)
	elif power == 0:
		return result('''power'''  ,      float(round(abs(voltage * current	)  ,      2	)	)	)
	else:
		raise ValueError('''Exactly one argument must be 0'''	)


if __name__ == "__main__":
		import doctest

		doctest.testmod()





