






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

 __a      :       int				  =   True
except (ImportError, AttributeError):
 __a      :       Optional[int]				  =   object



 def 			_SCREAMING_SNAKE_CASE						( *__lowercase   :			Tuple			,				**__lowercase   :			Optional[int]    )						->      List[str]:





     """simple docstring"""

     pass






 __a      :       str				  =   False


__a      :       str				  =   logging.get_logger("transformers-cli/serving")



def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Namespace    )						->      List[str]:





    """simple docstring"""

    __A         =	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      (	lowercase_  ):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE   						=				42


class       __lowercase      (	lowercase_  ):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE   						=				42
     SCREAMING_SNAKE_CASE   						=				42


class       __lowercase      (	lowercase_  ):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE   						=				42


class       __lowercase      (	lowercase_  ):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE   						=				42


class       __lowercase      (	lowercase_  ):







     '''simple docstring'''




     @staticmethod
     def 		lowerCAmelCase_     (				UpperCamelCase_       :			ArgumentParser				):


         """simple docstring"""



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




     def __init__(				self       :			Dict ,	UpperCamelCase_       :			Pipeline ,	UpperCamelCase_       :			str ,	UpperCamelCase_       :			int ,	UpperCamelCase_       :			int				):


         """simple docstring"""



         __A         =	pipeline

         __A         =	host
         __A         =	port
         __A         =	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         =	FastAPI(
                 routes=[
                     APIRoute(
                         """/""" ,	self.model_info ,	response_model=UpperCamelCase_ ,	response_class=UpperCamelCase_ ,	methods=["""GET"""] ,	),
                     APIRoute(
                         """/tokenize""" ,	self.tokenize ,	response_model=UpperCamelCase_ ,	response_class=UpperCamelCase_ ,	methods=["""POST"""] ,	),
                     APIRoute(
                         """/detokenize""" ,	self.detokenize ,	response_model=UpperCamelCase_ ,	response_class=UpperCamelCase_ ,	methods=["""POST"""] ,	),
                     APIRoute(
                         """/forward""" ,	self.forward ,	response_model=UpperCamelCase_ ,	response_class=UpperCamelCase_ ,	methods=["""POST"""] ,	),
                 ] ,	timeout=600 ,	)




     def 		lowerCAmelCase_     (				self       :			int				):


         """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       :			Dict ,	UpperCamelCase_       :			str = Body(UpperCamelCase_ ,	embed=UpperCamelCase_				) ,	UpperCamelCase_       :			bool = Body(UpperCamelCase_ ,	embed=UpperCamelCase_				)				):


         """simple docstring"""



         try:
             __A         =	self._pipeline.tokenizer.tokenize(UpperCamelCase_				)

             if return_ids:
                 __A         =	self._pipeline.tokenizer.convert_tokens_to_ids(UpperCamelCase_				)
                 return ServeTokenizeResult(tokens=UpperCamelCase_ ,	tokens_ids=UpperCamelCase_				)
             else:
                 return ServeTokenizeResult(tokens=UpperCamelCase_				)

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




     def 		lowerCAmelCase_     (				self       :			Optional[Any] ,	UpperCamelCase_       :			List[int] = Body(UpperCamelCase_ ,	embed=UpperCamelCase_				) ,	UpperCamelCase_       :			bool = Body(UpperCamelCase_ ,	embed=UpperCamelCase_				) ,	UpperCamelCase_       :			bool = Body(UpperCamelCase_ ,	embed=UpperCamelCase_				) ,	):


         """simple docstring"""



         try:
             __A         =	self._pipeline.tokenizer.decode(UpperCamelCase_ ,	UpperCamelCase_ ,	UpperCamelCase_				)
             return ServeDeTokenizeResult(model="""""" ,	text=UpperCamelCase_				)
         except Exception as e:
             raise HTTPException(status_code=500 ,	detail={"""model""": """""", """error""": str(UpperCamelCase_				)}				)





     async def 		lowerCAmelCase_     (				self       :			Any ,	UpperCamelCase_       :			List[Any]=Body(UpperCamelCase_ ,	embed=UpperCamelCase_				)				):


         """simple docstring"""



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

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












import os

import pytest

from datasets import (
    get_dataset_config_info,
    get_dataset_config_names,
    get_dataset_infos,
    get_dataset_split_names,
    inspect_dataset,
    inspect_metric,
)


__a      :       List[str]				  =   pytest.mark.integration



@pytest.mark.parametrize("""path"""			,				["""paws""", """csv"""]    )
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			List[Any]			,				__lowercase   :			Optional[int]    )						->      Tuple:





    """simple docstring"""

    inspect_dataset(__lowercase			,				__lowercase    )
    __A         =	path + """.py"""
    assert script_name in os.listdir(__lowercase    )
    assert "__pycache__" not in os.listdir(__lowercase    )



@pytest.mark.filterwarnings("""ignore:inspect_metric is deprecated:FutureWarning"""    )
@pytest.mark.filterwarnings("""ignore:metric_module_factory is deprecated:FutureWarning"""    )
@pytest.mark.parametrize("""path"""			,				["""accuracy"""]    )
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Optional[int]			,				__lowercase   :			Tuple    )						->      Any:





    """simple docstring"""

    inspect_metric(__lowercase			,				__lowercase    )
    __A         =	path + """.py"""
    assert script_name in os.listdir(__lowercase    )
    assert "__pycache__" not in os.listdir(__lowercase    )



@pytest.mark.parametrize(
    """path, config_name, expected_splits"""			,				[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Dict			,				__lowercase   :			Optional[int]			,				__lowercase   :			List[Any]    )						->      Optional[Any]:





    """simple docstring"""

    __A         =	get_dataset_config_info(__lowercase			,				config_name=__lowercase    )
    assert info.config_name == config_name
    assert list(info.splits.keys()    ) == expected_splits



@pytest.mark.parametrize(
    """path, config_name, expected_exception"""			,				[
        ("""paws""", None, ValueError),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			List[Any]			,				__lowercase   :			int			,				__lowercase   :			List[str]    )						->      int:





    """simple docstring"""

    with pytest.raises(__lowercase    ):
        get_dataset_config_info(__lowercase			,				config_name=__lowercase    )



@pytest.mark.parametrize(
    """path, expected"""			,				[
        ("""squad""", """plain_text"""),
        ("""acronym_identification""", """default"""),
        ("""lhoestq/squad""", """plain_text"""),
        ("""lhoestq/test""", """default"""),
        ("""lhoestq/demo1""", """lhoestq--demo1"""),
        ("""dalle-mini/wit""", """dalle-mini--wit"""),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Tuple			,				__lowercase   :			Optional[Any]    )						->      Any:





    """simple docstring"""

    __A         =	get_dataset_config_names(__lowercase    )
    assert expected in config_names



@pytest.mark.parametrize(
    """path, expected_configs, expected_splits_in_first_config"""			,				[
        ("""squad""", ["""plain_text"""], ["""train""", """validation"""]),
        ("""dalle-mini/wit""", ["""dalle-mini--wit"""], ["""train"""]),
        ("""paws""", ["""labeled_final""", """labeled_swap""", """unlabeled_final"""], ["""train""", """test""", """validation"""]),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			int			,				__lowercase   :			Tuple			,				__lowercase   :			List[Any]    )						->      List[str]:





    """simple docstring"""

    __A         =	get_dataset_infos(__lowercase    )
    assert list(infos.keys()    ) == expected_configs
    __A         =	expected_configs[0]
    assert expected_config in infos
    __A         =	infos[expected_config]
    assert info.config_name == expected_config
    assert list(info.splits.keys()    ) == expected_splits_in_first_config



@pytest.mark.parametrize(
    """path, expected_config, expected_splits"""			,				[
        ("""squad""", """plain_text""", ["""train""", """validation"""]),
        ("""dalle-mini/wit""", """dalle-mini--wit""", ["""train"""]),
        ("""paws""", """labeled_final""", ["""train""", """test""", """validation"""]),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			Optional[int]			,				__lowercase   :			str			,				__lowercase   :			Union[str, Any]    )						->      Dict:





    """simple docstring"""

    __A         =	get_dataset_infos(__lowercase    )
    assert expected_config in infos
    __A         =	infos[expected_config]
    assert info.config_name == expected_config
    assert list(info.splits.keys()    ) == expected_splits






@pytest.mark.parametrize(
    """path, config_name, expected_exception"""			,				[
        ("""paws""", None, ValueError),
    ]			,				)
def 			_SCREAMING_SNAKE_CASE						( __lowercase   :			List[str]			,				__lowercase   :			Optional[int]			,				__lowercase   :			Tuple    )						->      Union[str, Any]:





    """simple docstring"""

    with pytest.raises(__lowercase    ):
        get_dataset_split_names(__lowercase			,				config_name=__lowercase    )




