



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

							__snake_case				:		Tuple										=True
except (ImportError, AttributeError):
							__snake_case				:		Any										=object






							def 	lowerCAmelCase__		(    *lowerCamelCase_		:		Optional[Any]       ,**lowerCamelCase_		:		int):





											'''simple docstring'''

											pass

							__snake_case				:		Any										=False


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






def 	lowerCAmelCase__		(    lowerCamelCase_		:		Namespace):





				'''simple docstring'''

				lowerCAmelCase__     :				Dict												=     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__			(							_UpperCamelCase):




		'''simple docstring'''



		snake_case_	=42



class        lowerCamelCase__			(							_UpperCamelCase):




		'''simple docstring'''



		snake_case_	=42
		snake_case_	=42



class        lowerCamelCase__			(							_UpperCamelCase):




		'''simple docstring'''



		snake_case_	=42



class        lowerCamelCase__			(							_UpperCamelCase):




		'''simple docstring'''



		snake_case_	=42



class        lowerCamelCase__			(							_UpperCamelCase):




		'''simple docstring'''



		@staticmethod
		def 		lowerCAmelCase__      (__lowerCamelCase )     ->			Tuple:

						"""simple docstring"""






						lowerCAmelCase__     :				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		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase		,__lowerCamelCase )     ->			Optional[int]:

						"""simple docstring"""






						lowerCAmelCase__     :				Tuple												=     pipeline

						lowerCAmelCase__     :				Tuple												=     host
						lowerCAmelCase__     :				Tuple												=     port
						lowerCAmelCase__     :				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}""" )
										lowerCAmelCase__     :				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 		lowerCAmelCase__      (self )     ->			Optional[Any]:

						"""simple docstring"""






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



		def 		lowerCAmelCase__      (self )     ->			List[str]:

						"""simple docstring"""






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



		def 		lowerCAmelCase__      (self		,__lowerCamelCase = Body(lowerCAmelCase_		,embed=lowerCAmelCase_ )		,__lowerCamelCase = Body(lowerCAmelCase_		,embed=lowerCAmelCase_ ) )     ->			Any:

						"""simple docstring"""






						try:
										lowerCAmelCase__     :				Dict												=     self._pipeline.tokenizer.tokenize(lowerCAmelCase_ )

										if return_ids:
														lowerCAmelCase__     :				List[Any]												=     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 		lowerCAmelCase__      (self		,__lowerCamelCase = Body(lowerCAmelCase_		,embed=lowerCAmelCase_ )		,__lowerCamelCase = Body(lowerCAmelCase_		,embed=lowerCAmelCase_ )		,__lowerCamelCase = Body(lowerCAmelCase_		,embed=lowerCAmelCase_ )		,)     ->			Optional[Any]:

						"""simple docstring"""






						try:
										lowerCAmelCase__     :				int												=     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 		lowerCAmelCase__      (self		,__lowerCamelCase=Body(lowerCAmelCase_		,embed=lowerCAmelCase_ ) )     ->			Optional[int]:

						"""simple docstring"""






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

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








import pytest

from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs

@pytest.mark.parametrize(
    'kwargs, expected',	[
        ({'num_shards': 0, 'max_num_jobs': 1}, []),
        ({'num_shards': 10, 'max_num_jobs': 1}, [range(10	)]),
        ({'num_shards': 10, 'max_num_jobs': 10}, [range(lowerCAmelCase_,	i + 1	) for i in range(10	)]),
        ({'num_shards': 1, 'max_num_jobs': 10}, [range(1	)]),
        ({'num_shards': 10, 'max_num_jobs': 3}, [range(0,	4	), range(4,	7	), range(7,	10	)]),
        ({'num_shards': 3, 'max_num_jobs': 10}, [range(0,	1	), range(1,	2	), range(2,	3	)]),
    ],	)
def   a_    ( lowerCAmelCase_      :			Optional[Any],	lowerCAmelCase_      :			Any	):
   __lowerCAmelCase								=	_distribute_shards(**lowerCAmelCase_	)
   assert out == expected

@pytest.mark.parametrize(
    'gen_kwargs, max_num_jobs, expected',	[
        ({'foo': 0}, 10, [{'foo': 0}]),
        ({'shards': [0, 1, 2, 3]}, 1, [{'shards': [0, 1, 2, 3]}]),
        ({'shards': [0, 1, 2, 3]}, 4, [{'shards': [0]}, {'shards': [1]}, {'shards': [2]}, {'shards': [3]}]),
        ({'shards': [0, 1]}, 4, [{'shards': [0]}, {'shards': [1]}]),
        ({'shards': [0, 1, 2, 3]}, 2, [{'shards': [0, 1]}, {'shards': [2, 3]}]),
    ],	)
def   a_    ( lowerCAmelCase_      :			Optional[Any],	lowerCAmelCase_      :			List[str],	lowerCAmelCase_      :			Optional[int]	):
   __lowerCAmelCase								=	_split_gen_kwargs(lowerCAmelCase_,	lowerCAmelCase_	)
   assert out == expected




@pytest.mark.parametrize(
    'gen_kwargs, expected',	[
        ({'foo': 0}, 1),
        ({'shards': [0]}, 1),
        ({'shards': [0, 1, 2, 3]}, 4),
        ({'shards': [0, 1, 2, 3], 'foo': 0}, 4),
        ({'shards': [0, 1, 2, 3], 'other': (0, 1)}, 4),
        ({'shards': [0, 1, 2, 3], 'shards2': [0, 1]}, RuntimeError),
    ],	)
def   a_    ( lowerCAmelCase_      :			int,	lowerCAmelCase_      :			Any	):
   if expected is RuntimeError:
      with pytest.raises(lowerCAmelCase_	):
         _number_of_shards_in_gen_kwargs(lowerCAmelCase_	)
   else:
      __lowerCAmelCase								=	_number_of_shards_in_gen_kwargs(lowerCAmelCase_	)
      assert out == expected

