





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__     =	True
except (ImportError, AttributeError):
					UpperCamelCase__     =	object





					def       _UpperCamelCase       (*a__				:int				,     **a__				:int    ):






												"""simple docstring"""





												pass
					UpperCamelCase__     =	False


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





def       _UpperCamelCase       (a__				:Namespace    ):






							"""simple docstring"""





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

class     __SCREAMING_SNAKE_CASE   (       _a    ):
							snake_case       : dict






class     __SCREAMING_SNAKE_CASE   (       _a    ):
							snake_case       : List[str]
							snake_case       : Optional[List[int]]






class     __SCREAMING_SNAKE_CASE   (       _a    ):
							snake_case       : str






class     __SCREAMING_SNAKE_CASE   (       _a    ):
							snake_case       : Any






class     __SCREAMING_SNAKE_CASE   (       _a    ):






							@staticmethod
							def 			_lowerCamelCase						(  __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 			_lowerCamelCase						(  self					):
														run(self._app					,	host=self.host					,	port=self.port					,	workers=self.workers					)






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






							def 			_lowerCamelCase						(  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 			_lowerCamelCase						(  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 			_lowerCamelCase						(  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					)}					)









def       _UpperCamelCase       (a__				:str    ):






							"""simple docstring"""





							UpperCamelCase__			       =     0

							# if input_string is "aba" than new_input_string become "a|b|a"
							UpperCamelCase__			       =     """"""
							UpperCamelCase__			       =     """"""

							# append each character + "|" in new_string for range(0, length-1)
							for i in input_string[: len(a__    ) - 1]:
														new_input_string += i + "|"
							# append last character
							new_input_string += input_string[-1]

							# we will store the starting and ending of previous furthest ending palindromic
							# substring
							UpperCamelCase__       ,       UpperCamelCase__			       =     0, 0

							# length[i] shows the length of palindromic substring with center i
							UpperCamelCase__			       =     [1 for i in range(len(a__    )    )]

							# for each character in new_string find corresponding palindromic string
							UpperCamelCase__			       =     0
							for j in range(len(a__    )    ):
														UpperCamelCase__			       =     1 if j > r else min(length[l + r - j] // 2				,     r - j + 1    )
														while (
														    j - k >= 0
														    and j + k < len(a__    )
														    and new_input_string[k + j] == new_input_string[j - k]
														):
																					k += 1

														UpperCamelCase__			       =     2 * k - 1

														# does this string is ending after the previously explored end (that is r) ?
														# if yes the update the new r to the last index of this
														if j + k - 1 > r:
																					UpperCamelCase__			       =     j - k + 1  # noqa: E741
																					UpperCamelCase__			       =     j + k - 1

														# update max_length and start position
														if max_length < length[j]:
																					UpperCamelCase__			       =     length[j]
																					UpperCamelCase__			       =     j

    # create that string
							UpperCamelCase__			       =     new_input_string[start - max_length // 2 : start + max_length // 2 + 1]
							for i in s:
														if i != "|":
																					output_string += i

							return output_string


if __name__ == "__main__":
					import doctest

					doctest.testmod()




