



"""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

			A		=						True
except (ImportError, AttributeError):
			A		=						object

			def  __SCREAMING_SNAKE_CASE		(			*lowerCamelCase_:							int     ,		**lowerCamelCase_:							Any ):
									"""simple docstring"""






									pass
			A		=						False


A		=						logging.get_logger('transformers-cli/serving')

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							Namespace ):
						"""simple docstring"""






						snake_case   :			List[Any]						    = 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       _a  ( SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     42



class       _a  ( SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     42
			__magic_name__     					=     42



class       _a  ( SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     42



class       _a  ( SCREAMING_SNAKE_CASE__):
			__magic_name__     					=     42



class       _a  ( SCREAMING_SNAKE_CASE__):



			@staticmethod
			def 				__lowercase					(			_lowercase							:				ArgumentParser		)							->					str:
									snake_case   :			Optional[int]						    = parser.add_parser(
									    "serve"   ,	help="CLI tool to run inference requests through REST and GraphQL endpoints."		)
									serve_parser.add_argument(
									    "--task"   ,	type=_lowercase   ,	choices=get_supported_tasks()   ,	help="The task to run the pipeline on"   ,	)
									serve_parser.add_argument("--host"   ,	type=_lowercase   ,	default="localhost"   ,	help="Interface the server will listen on."		)
									serve_parser.add_argument("--port"   ,	type=_lowercase   ,	default=8888   ,	help="Port the serving will listen to."		)
									serve_parser.add_argument("--workers"   ,	type=_lowercase   ,	default=1   ,	help="Number of http workers"		)
									serve_parser.add_argument("--model"   ,	type=_lowercase   ,	help="Model's name or path to stored model."		)
									serve_parser.add_argument("--config"   ,	type=_lowercase   ,	help="Model's config name or path to stored model."		)
									serve_parser.add_argument("--tokenizer"   ,	type=_lowercase   ,	help="Tokenizer name to use."		)
									serve_parser.add_argument(
									    "--device"   ,	type=_lowercase   ,	default=-1   ,	help="Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)"   ,	)
									serve_parser.set_defaults(func=_lowercase		)



			def __init__(			self							:				List[Any]   ,	_lowercase							:				Pipeline   ,	_lowercase							:				str   ,	_lowercase							:				int   ,	_lowercase							:				int		)							->					Dict:
									snake_case   :			str						    = pipeline

									snake_case   :			List[Any]						    = host
									snake_case   :			Optional[int]						    = port
									snake_case   :			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}'''		)
															snake_case   :			Dict						    = FastAPI(
															    routes=[
															        APIRoute(
															            "/"   ,	self.model_info   ,	response_model=_lowercase   ,	response_class=_lowercase   ,	methods=["GET"]   ,	),
															        APIRoute(
															            "/tokenize"   ,	self.tokenize   ,	response_model=_lowercase   ,	response_class=_lowercase   ,	methods=["POST"]   ,	),
															        APIRoute(
															            "/detokenize"   ,	self.detokenize   ,	response_model=_lowercase   ,	response_class=_lowercase   ,	methods=["POST"]   ,	),
															        APIRoute(
															            "/forward"   ,	self.forward   ,	response_model=_lowercase   ,	response_class=_lowercase   ,	methods=["POST"]   ,	),
															    ]   ,	timeout=600   ,	)



			def 				__lowercase					(			self							:				List[Any]		)							->					Any:
									run(self._app   ,	host=self.host   ,	port=self.port   ,	workers=self.workers		)



			def 				__lowercase					(			self							:				List[str]		)							->					Optional[Any]:
									return ServeModelInfoResult(infos=vars(self._pipeline.model.config		)		)



			def 				__lowercase					(			self							:				Dict   ,	_lowercase							:				str = Body(_lowercase   ,	embed=_lowercase		)   ,	_lowercase							:				bool = Body(_lowercase   ,	embed=_lowercase		)		)							->					List[str]:
									try:
															snake_case   :			Dict						    = self._pipeline.tokenizer.tokenize(_lowercase		)

															if return_ids:
																					snake_case   :			Any						    = self._pipeline.tokenizer.convert_tokens_to_ids(_lowercase		)
																					return ServeTokenizeResult(tokens=_lowercase   ,	tokens_ids=_lowercase		)
															else:
																					return ServeTokenizeResult(tokens=_lowercase		)

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



			def 				__lowercase					(			self							:				Dict   ,	_lowercase							:				List[int] = Body(_lowercase   ,	embed=_lowercase		)   ,	_lowercase							:				bool = Body(_lowercase   ,	embed=_lowercase		)   ,	_lowercase							:				bool = Body(_lowercase   ,	embed=_lowercase		)   ,	)							->					Dict:
									try:
															snake_case   :			List[Any]						    = self._pipeline.tokenizer.decode(_lowercase   ,	_lowercase   ,	_lowercase		)
															return ServeDeTokenizeResult(model=""   ,	text=_lowercase		)
									except Exception as e:
															raise HTTPException(status_code=500   ,	detail={"model": "", "error": str(_lowercase		)}		)



			async def 				__lowercase					(			self							:				Optional[Any]   ,	_lowercase							:				str=Body(_lowercase   ,	embed=_lowercase		)		)							->					int:

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

									try:
															# Forward through the model
															snake_case   :			Optional[Any]						    = self._pipeline(_lowercase		)
															return ServeForwardResult(output=_lowercase		)
									except Exception as e:
															raise HTTPException(500   ,	{"error": str(_lowercase		)}		)








"""simple docstring"""







import importlib
import shutil
import threading
import warnings
from typing import List

import fsspec
import fsspec.asyn

from . import compression
from .hffilesystem import HfFileSystem


A		=						importlib.util.find_spec('s3fs') is not None

if _has_safs:
			from .safilesystem import SaFileSystem  # noqa: F401

A		=						[
    compression.BzaFileSystem,
    compression.GzipFileSystem,
    compression.LzaFileSystem,
    compression.XzFileSystem,
    compression.ZstdFileSystem,
]

# Register custom filesystems
for fs_class in COMPRESSION_FILESYSTEMS + [HfFileSystem]:
			if fs_class.protocol in fsspec.registry and fsspec.registry[fs_class.protocol] is not fs_class:
						warnings.warn(F'''A filesystem protocol was already set for {fs_class.protocol} and will be overwritten.''')
			fsspec.register_implementation(fs_class.protocol, fs_class, clobber=True)

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							str ):
						"""simple docstring"""






						if "://" in dataset_path:
												snake_case   :			List[str]						    = dataset_path.split("://" )[1]
						return dataset_path

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							fsspec.AbstractFileSystem ):
						"""simple docstring"""






						if fs is not None and fs.protocol != "file":
												return True
						else:
												return False

def  __SCREAMING_SNAKE_CASE		(			lowerCamelCase_:							fsspec.AbstractFileSystem     ,		lowerCamelCase_:							str     ,		lowerCamelCase_:							str ):
						"""simple docstring"""






						snake_case   :			int						    = not is_remote_filesystem(lowerCamelCase_ )
						if is_local:
												# LocalFileSystem.mv does copy + rm, it is more efficient to simply move a local directory
												shutil.move(fs._strip_protocol(lowerCamelCase_ )     ,		fs._strip_protocol(lowerCamelCase_ ) )
						else:
												fs.mv(lowerCamelCase_     ,		lowerCamelCase_     ,		recursive=lowerCamelCase_ )

def  __SCREAMING_SNAKE_CASE		(			):
						"""simple docstring"""






						if hasattr(fsspec.asyn     ,		"reset_lock" ):
												# for future fsspec>2022.05.0
												fsspec.asyn.reset_lock()
						else:
												snake_case   :			Union[str, Any]						    = None
												snake_case   :			Optional[int]						    = None
												snake_case   :			List[str]						    = threading.Lock()



