


'''simple docstring'''

import math

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


lowerCAmelCase				:str        =      logging.get_logger(__name__)

lowerCAmelCase				:Union[str, Any]        =      {
    '''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json''',
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}
class _lowerCamelCase	(						__snake_case							):



		'''simple docstring'''







		A_     :      List[Any]				   =    """data2vec-audio"""







		def __init__( self		:						Any  ,					_A		:						Tuple=32  ,					_A		:						Dict=768  ,					_A		:						Union[str, Any]=12  ,					_A		:						Any=12  ,					_A		:						str=3072  ,					_A		:						Union[str, Any]="gelu"  ,					_A		:						List[Any]=0.1  ,					_A		:						Tuple=0.1  ,					_A		:						List[str]=0.1  ,					_A		:						Tuple=0.0  ,					_A		:						Any=0.1  ,					_A		:						int=0.1  ,					_A		:						Dict=0.02  ,					_A		:						Any=1E-5  ,					_A		:						List[str]="gelu"  ,					_A		:						List[str]=(512, 512, 512, 512, 512, 512, 512)  ,					_A		:						str=(5, 2, 2, 2, 2, 2, 2)  ,					_A		:						Union[str, Any]=(10, 3, 3, 3, 3, 2, 2)  ,					_A		:						str=False  ,					_A		:						Union[str, Any]=16  ,					_A		:						Optional[int]=19  ,					_A		:						Dict=5  ,					_A		:						List[Any]=0.05  ,					_A		:						int=10  ,					_A		:						Optional[Any]=2  ,					_A		:						Dict=0.0  ,					_A		:						Optional[Any]=10  ,					_A		:						Dict=0  ,					_A		:						int="sum"  ,					_A		:						Dict=False  ,					_A		:						Any=False  ,					_A		:						Optional[int]=256  ,					_A		:						Any=(512, 512, 512, 512, 1500)  ,					_A		:						List[Any]=(5, 3, 3, 1, 1)  ,					_A		:						List[str]=(1, 2, 3, 1, 1)  ,					_A		:						Tuple=512  ,					_A		:						int=0  ,					_A		:						List[str]=1  ,					_A		:						Optional[int]=2  ,					_A		:						Optional[Any]=False  ,					_A		:						Dict=3  ,					_A		:						Optional[Any]=2  ,					_A		:						Union[str, Any]=3  ,					_A		:						int=None  ,					**_A		:						List[Any]  ,					)  ->			Dict:
			super().__init__(**UpperCamelCase__  ,					pad_token_id=UpperCamelCase__  ,					bos_token_id=UpperCamelCase__  ,					eos_token_id=UpperCamelCase__      )
			__magic_name__	:   str					     =					hidden_size
			__magic_name__	:   Union[str, Any]					     =					feat_extract_activation
			__magic_name__	:   Any					     =					list(UpperCamelCase__      )
			__magic_name__	:   List[str]					     =					list(UpperCamelCase__      )
			__magic_name__	:   Optional[int]					     =					list(UpperCamelCase__      )
			__magic_name__	:   Dict					     =					conv_bias
			__magic_name__	:   str					     =					num_conv_pos_embeddings
			__magic_name__	:   Dict					     =					num_conv_pos_embedding_groups
			__magic_name__	:   int					     =					conv_pos_kernel_size
			__magic_name__	:   Dict					     =					len(self.conv_dim      )
			__magic_name__	:   Dict					     =					num_hidden_layers
			__magic_name__	:   Dict					     =					intermediate_size
			__magic_name__	:   int					     =					hidden_act
			__magic_name__	:   Any					     =					num_attention_heads
			__magic_name__	:   List[Any]					     =					hidden_dropout
			__magic_name__	:   Optional[Any]					     =					attention_dropout
			__magic_name__	:   Optional[Any]					     =					activation_dropout
			__magic_name__	:   Optional[Any]					     =					feat_proj_dropout
			__magic_name__	:   Any					     =					final_dropout
			__magic_name__	:   Optional[int]					     =					layerdrop
			__magic_name__	:   Optional[Any]					     =					layer_norm_eps
			__magic_name__	:   Dict					     =					initializer_range
			__magic_name__	:   Any					     =					vocab_size
			__magic_name__	:   Optional[int]					     =					use_weighted_layer_sum

			if (
			    (len(self.conv_stride      ) != self.num_feat_extract_layers)
			    or (len(self.conv_kernel      ) != self.num_feat_extract_layers)
			    or (len(self.conv_dim      ) != self.num_feat_extract_layers)
			):
				raise ValueError(
				    'Configuration for convolutional layers is incorrect. It is required that `len(config.conv_dim)` =='
				    ' `len(config.conv_stride)` == `len(config.conv_kernel)`, but is `len(config.conv_dim) ='
				    F' {len(self.conv_dim      )}`, `len(config.conv_stride) = {len(self.conv_stride      )}`,'
				    F' `len(config.conv_kernel) = {len(self.conv_kernel      )}`.'      )

			# fine-tuning config parameters for SpecAugment: https://arxiv.org/abs/1904.08779
			__magic_name__	:   Optional[Any]					     =					mask_time_prob
			__magic_name__	:   Union[str, Any]					     =					mask_time_length
			__magic_name__	:   List[Any]					     =					mask_time_min_masks
			__magic_name__	:   List[Any]					     =					mask_feature_prob
			__magic_name__	:   List[str]					     =					mask_feature_length
			__magic_name__	:   int					     =					mask_feature_min_masks

			# ctc loss
			__magic_name__	:   int					     =					ctc_loss_reduction
			__magic_name__	:   Any					     =					ctc_zero_infinity

			# adapter
			__magic_name__	:   Dict					     =					add_adapter
			__magic_name__	:   str					     =					adapter_kernel_size
			__magic_name__	:   Optional[Any]					     =					adapter_stride
			__magic_name__	:   Tuple					     =					num_adapter_layers
			__magic_name__	:   List[str]					     =					output_hidden_size or hidden_size

			# SequenceClassification-specific parameter. Feel free to ignore for other classes.
			__magic_name__	:   Optional[int]					     =					classifier_proj_size

			# XVector-specific parameters. Feel free to ignore for other classes.
			__magic_name__	:   Any					     =					list(UpperCamelCase__      )
			__magic_name__	:   Optional[int]					     =					list(UpperCamelCase__      )
			__magic_name__	:   List[Any]					     =					list(UpperCamelCase__      )
			__magic_name__	:   Dict					     =					xvector_output_dim







		@property
		def        __lowerCAmelCase		( self		:						Optional[Any]      )  ->			Optional[int]:
			return math.prod(self.conv_stride      )







'''simple docstring'''

import socket





def lowerCamelCase      (      ):





	"""simple docstring"""







	__magic_name__	:   List[str]					     =					socket.socket(socket.AF_INET		,		socket.SOCK_STREAM		)
	__magic_name__	:   Union[str, Any]					     =					socket.gethostname()
	__magic_name__	:   int					     =					1_2312

	sock.connect((host, port)		)
	sock.send(b'Hello server!'		)

	with open('Received_file'		,		'wb'		) as out_file:
		print('File opened'		)
		print('Receiving data...'		)
		while True:
			__magic_name__	:   Optional[int]					     =					sock.recv(1024		)
			if not data:
				break
			out_file.write(lowerCAmelCase		)

	print('Successfully received the file'		)
	sock.close()
	print('Connection closed'		)


if __name__ == "__main__":
							main()