






from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase								=						logging.get_logger(__name__)

__UpperCAmelCase								=						{
    'facebook/s2t-wav2vec2-large-en-de': (
        'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'
    ),
    # See all Speech2Text models at https://huggingface.co/models?filter=speech2text2
}



class   lowerCamelCase      (_snake_case			):







		'''simple docstring'''



		_snake_case    :    str       						=  '''speech_to_text_2'''
		_snake_case    :    Optional[int]       						=  ['''past_key_values''']
		_snake_case    :    str       						=  {'''num_attention_heads''': '''decoder_attention_heads''', '''hidden_size''': '''d_model'''}



		def __init__(							self				,		_UpperCamelCase=1_0_0_0_0				,		_UpperCamelCase=6				,		_UpperCamelCase=2_0_4_8				,		_UpperCamelCase=4				,		_UpperCamelCase=0.0				,		_UpperCamelCase=True				,		_UpperCamelCase="relu"				,		_UpperCamelCase=2_5_6				,		_UpperCamelCase=0.1				,		_UpperCamelCase=0.0				,		_UpperCamelCase=0.0				,		_UpperCamelCase=0.02				,		_UpperCamelCase=2				,		_UpperCamelCase=True				,		_UpperCamelCase=1				,		_UpperCamelCase=0				,		_UpperCamelCase=2				,		_UpperCamelCase=1_0_2_4				,		**_UpperCamelCase				,		)	->							Optional[Any]:
							UpperCAmelCase_    :      Tuple            =						vocab_size
							UpperCAmelCase_    :      Optional[int]            =						d_model
							UpperCAmelCase_    :      Dict            =						decoder_ffn_dim
							UpperCAmelCase_    :      int            =						decoder_layers
							UpperCAmelCase_    :      Tuple            =						decoder_attention_heads
							UpperCAmelCase_    :      str            =						dropout
							UpperCAmelCase_    :      Union[str, Any]            =						attention_dropout
							UpperCAmelCase_    :      List[str]            =						activation_dropout
							UpperCAmelCase_    :      Any            =						activation_function
							UpperCAmelCase_    :      List[Any]            =						init_std
							UpperCAmelCase_    :      Optional[Any]            =						decoder_layerdrop
							UpperCAmelCase_    :      List[str]            =						use_cache
							UpperCAmelCase_    :      Dict            =						decoder_layers
							UpperCAmelCase_    :      List[str]            =						scale_embedding  # scale factor will be sqrt(d_model) if True
							UpperCAmelCase_    :      Optional[int]            =						max_target_positions

							super().__init__(
							    pad_token_id=_UpperCamelCase				,		bos_token_id=_UpperCamelCase				,		eos_token_id=_UpperCamelCase				,		decoder_start_token_id=_UpperCamelCase				,		**_UpperCamelCase				,		)














from __future__ import annotations




def      lowercase__      (     __snake_case    :							tuple[int, int]     ,       __snake_case    :							int  ):


					'''simple docstring'''


					UpperCAmelCase_       ,  UpperCAmelCase_    :      Tuple            =						position
					UpperCAmelCase_    :      str            =						[
					    (y + 1, x + 2),
					    (y - 1, x + 2),
					    (y + 1, x - 2),
					    (y - 1, x - 2),
					    (y + 2, x + 1),
					    (y + 2, x - 1),
					    (y - 2, x + 1),
					    (y - 2, x - 1),
					]
					UpperCAmelCase_    :      Optional[Any]            =						[]

					for position in positions:
										UpperCAmelCase_       ,  UpperCAmelCase_    :      Tuple            =						position
										if 0 <= y_test < n and 0 <= x_test < n:
															permissible_positions.append(__snake_case  )

					return permissible_positions




def      lowercase__      (     __snake_case    :							list[list[int]]  ):


					'''simple docstring'''


					return not any(elem == 0 for row in board for elem in row  )




def      lowercase__      (     __snake_case    :							list[list[int]]     ,       __snake_case    :							tuple[int, int]     ,       __snake_case    :							int  ):


					'''simple docstring'''


					if is_complete(__snake_case  ):
										return True

					for position in get_valid_pos(__snake_case     ,       len(__snake_case  )  ):
										UpperCAmelCase_       ,  UpperCAmelCase_    :      Any            =						position

										if board[y][x] == 0:
															UpperCAmelCase_    :      Optional[Any]            =						curr + 1
															if open_knight_tour_helper(__snake_case     ,       __snake_case     ,       curr + 1  ):
																				return True
															UpperCAmelCase_    :      List[Any]            =						0

					return False




def      lowercase__      (     __snake_case    :							int  ):


					'''simple docstring'''


					UpperCAmelCase_    :      str            =						[[0 for i in range(__snake_case  )] for j in range(__snake_case  )]

					for i in range(__snake_case  ):
										for j in range(__snake_case  ):
															UpperCAmelCase_    :      Optional[Any]            =						1
															if open_knight_tour_helper(__snake_case     ,       (i, j)     ,       1  ):
																				return board
															UpperCAmelCase_    :      List[Any]            =						0

					UpperCAmelCase_    :      List[str]            =						F"Open Kight Tour cannot be performed on a board of size {n}"
					raise ValueError(__snake_case  )


if __name__ == "__main__":
		import doctest

		doctest.testmod()






