



import os
import sys
from contextlib import contextmanager


# Windows only
if os.name == "nt":
							import ctypes
							import msvcrt  # noqa


							class      __lowerCAmelCase     (		ctypes.Structure      ):
												"""simple docstring"""






												A__				:		Dict			       =    [("size", ctypes.c_int), ("visible", ctypes.c_byte)]


def A						(       )						->      Dict:
			if os.name == "nt":
						A__       =    CursorInfo()
						A__       =    ctypes.windll.kernelaa.GetStdHandle(-11					)
						ctypes.windll.kernelaa.GetConsoleCursorInfo(__UpperCamelCase ,	ctypes.byref(__UpperCamelCase					)					)
						A__       =    False
						ctypes.windll.kernelaa.SetConsoleCursorInfo(__UpperCamelCase ,	ctypes.byref(__UpperCamelCase					)					)
			elif os.name == "posix":
						sys.stdout.write('\033[?25l'					)
						sys.stdout.flush()


def A						(       )						->      Optional[int]:
			if os.name == "nt":
						A__       =    CursorInfo()
						A__       =    ctypes.windll.kernelaa.GetStdHandle(-11					)
						ctypes.windll.kernelaa.GetConsoleCursorInfo(__UpperCamelCase ,	ctypes.byref(__UpperCamelCase					)					)
						A__       =    True
						ctypes.windll.kernelaa.SetConsoleCursorInfo(__UpperCamelCase ,	ctypes.byref(__UpperCamelCase					)					)
			elif os.name == "posix":
						sys.stdout.write('\033[?25h'					)
						sys.stdout.flush()






@contextmanager
def A						(       )						->      int:
			try:
						hide_cursor()
						yield
			finally:
						show_cursor()









from typing import Dict

from .base import GenericTensor, Pipeline


class      __lowerCAmelCase     (		UpperCAmelCase_      ):
					"""simple docstring"""






					def     _a							(     self					:       Any				,					_snake_case					:       str=None				,					_snake_case					:       Dict=None				,					_snake_case					:       Any=None				,					**_snake_case					:       str					):






								"""simple docstring"""


								if tokenize_kwargs is None:
											A__       =    {}

								if truncation is not None:
											if "truncation" in tokenize_kwargs:
														raise ValueError(
														    'truncation parameter defined twice (given as keyword argument as well as in tokenize_kwargs)'					)
											A__       =    truncation

								A__       =    tokenize_kwargs

								A__       =    {}
								if return_tensors is not None:
											A__       =    return_tensors

								return preprocess_params, {}, postprocess_params



					def     _a							(     self					:       Any				,					_snake_case					:       Dict				,					**_snake_case					:       Optional[Any]					):






								"""simple docstring"""


								A__       =    self.framework
								A__       =    self.tokenizer(_snake_case				,					return_tensors=_snake_case				,					**_snake_case					)
								return model_inputs



					def     _a							(     self					:       List[Any]				,					_snake_case					:       Dict					):






								"""simple docstring"""


								A__       =    self.model(**_snake_case					)
								return model_outputs



					def     _a							(     self					:       Optional[Any]				,					_snake_case					:       List[Any]				,					_snake_case					:       str=False					):






								"""simple docstring"""


								if return_tensors:
											return model_outputs[0]
								if self.framework == "pt":
											return model_outputs[0].tolist()
								elif self.framework == "tf":
											return model_outputs[0].numpy().tolist()



					def __call__(     self					:       Dict				,					*_snake_case					:       int				,					**_snake_case					:       List[str]					):






								"""simple docstring"""


								return super().__call__(*_snake_case				,					**_snake_case					)




