





'''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 : int											=			True
except (ImportError, AttributeError):
			__lowerCamelCase : Union[str, Any]											=			object







			def 							UpperCAmelCase_    (	*lowerCAmelCase_		,							**lowerCAmelCase_							):

							"""simple docstring"""






							pass


			__lowerCamelCase : List[str]											=			False


__lowerCamelCase : List[Any]											=			logging.get_logger("transformers-cli/serving")







def 							UpperCAmelCase_    (	lowerCAmelCase_							):

				"""simple docstring"""






				lowercase         = 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       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	dict




class       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	List[str]
		UpperCAmelCase					:	Optional[List[int]]




class       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	str




class       UpperCAmelCase (						_lowercase  ):
		UpperCAmelCase					:	Any




class       UpperCAmelCase (						_lowercase  ):




		@staticmethod
		def 				UpperCAmelCase__   (A__      :	ArgumentParser				)					-> str:
						lowercase         = parser.add_parser(
						    "serve"							,			help="CLI tool to run inference requests through REST and GraphQL endpoints."				)
						serve_parser.add_argument(
						    "--task"							,			type=A__							,			choices=get_supported_tasks()							,			help="The task to run the pipeline on"							,			)
						serve_parser.add_argument("--host"							,			type=A__							,			default="localhost"							,			help="Interface the server will listen on."				)
						serve_parser.add_argument("--port"							,			type=A__							,			default=8_8_8_8							,			help="Port the serving will listen to."				)
						serve_parser.add_argument("--workers"							,			type=A__							,			default=1							,			help="Number of http workers"				)
						serve_parser.add_argument("--model"							,			type=A__							,			help="Model's name or path to stored model."				)
						serve_parser.add_argument("--config"							,			type=A__							,			help="Model's config name or path to stored model."				)
						serve_parser.add_argument("--tokenizer"							,			type=A__							,			help="Tokenizer name to use."				)
						serve_parser.add_argument(
						    "--device"							,			type=A__							,			default=-1							,			help="Indicate the device to run onto, -1 indicates CPU, >= 0 indicates GPU (default: -1)"							,			)
						serve_parser.set_defaults(func=A__				)




		def __init__(self      :	Any							,			A__      :	Pipeline							,			A__      :	str							,			A__      :	int							,			A__      :	int				)					-> Optional[int]:
						lowercase         = pipeline

						lowercase         = host
						lowercase         = port
						lowercase         = 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}'				)
										lowercase         = FastAPI(
										    routes=[
										        APIRoute(
										            "/"							,			self.model_info							,			response_model=A__							,			response_class=A__							,			methods=["GET"]							,			),
										        APIRoute(
										            "/tokenize"							,			self.tokenize							,			response_model=A__							,			response_class=A__							,			methods=["POST"]							,			),
										        APIRoute(
										            "/detokenize"							,			self.detokenize							,			response_model=A__							,			response_class=A__							,			methods=["POST"]							,			),
										        APIRoute(
										            "/forward"							,			self.forward							,			response_model=A__							,			response_class=A__							,			methods=["POST"]							,			),
										    ]							,			timeout=6_0_0							,			)




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




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




		def 				UpperCAmelCase__   (self      :	Optional[Any]							,			A__      :	str = Body(A__							,			embed=A__				)							,			A__      :	bool = Body(A__							,			embed=A__				)				)					-> int:
						try:
										lowercase         = self._pipeline.tokenizer.tokenize(A__				)

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

						except Exception as e:
										raise HTTPException(status_code=5_0_0							,			detail={"model": "", "error": str(A__				)}				)




		def 				UpperCAmelCase__   (self      :	Tuple							,			A__      :	List[int] = Body(A__							,			embed=A__				)							,			A__      :	bool = Body(A__							,			embed=A__				)							,			A__      :	bool = Body(A__							,			embed=A__				)							,			)					-> Optional[int]:
						try:
										lowercase         = self._pipeline.tokenizer.decode(A__							,			A__							,			A__				)
										return ServeDeTokenizeResult(model=""							,			text=A__				)
						except Exception as e:
										raise HTTPException(status_code=5_0_0							,			detail={"model": "", "error": str(A__				)}				)





		async def 				UpperCAmelCase__   (self      :	Tuple							,			A__      :	Optional[int]=Body(A__							,			embed=A__				)				)					-> Dict:

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

						try:
										# Forward through the model
										lowercase         = self._pipeline(A__				)
										return ServeForwardResult(output=A__				)
						except Exception as e:
										raise HTTPException(5_0_0							,			{"error": str(A__				)}				)











'''simple docstring'''

# This is the module that test_patching.py uses to test patch_submodule()

import os  # noqa: this is just for tests
import os as renamed_os  # noqa: this is just for tests
from os import path  # noqa: this is just for tests
from os import path as renamed_path  # noqa: this is just for tests
from os.path import join  # noqa: this is just for tests
from os.path import join as renamed_join  # noqa: this is just for tests


__lowerCamelCase : Any											=			open  # noqa: we just need to have a builtin inside this module to test it properly




