


import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm

from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin


class 					lowerCAmelCase_ (       _a			,_a			,_a):




						@register_to_config
						def __init__(	self						:   Optional[int]   ,     __A						:   int   ,     __A						:   int   ,     __A						:   int   ,     __A						:   float   ,     __A						:   int   ,     __A						:   int   ,     __A						:   int   ,     __A						:   int   ,     __A						:   str   ,     __A						:   bool = False   ,     )      ->List[Any]:






									"""simple docstring"""






									super().__init__()

									a__ :Tuple						  =    nn.Embedding(__A   ,     __A						)

									a__ :Union[str, Any]						  =    nn.Embedding(__A   ,     __A						)
									a__ :str						  =    False

									a__ :int						  =    nn.Dropout(p=__A						)

									a__ :Union[str, Any]						  =    TaConfig(
									    vocab_size=__A   ,     d_model=__A   ,     num_heads=__A   ,     d_kv=__A   ,     d_ff=__A   ,     dropout_rate=__A   ,     feed_forward_proj=__A   ,     is_decoder=__A   ,     is_encoder_decoder=__A   ,     )

									a__ :Union[str, Any]						  =    nn.ModuleList()
									for lyr_num in range(__A						):
												a__ :int						  =    TaBlock(__A						)
												self.encoders.append(__A						)

									a__ :Optional[int]						  =    TaLayerNorm(__A						)
									a__ :int						  =    nn.Dropout(p=__A						)






						def  _snake_case					(	self						:   str   ,     __A						:   Optional[Any]   ,     __A						:   int						)      ->Dict:






									"""simple docstring"""






									a__ :int						  =    self.token_embedder(__A						)

									a__ :List[Any]						  =    encoder_input_tokens.shape[1]
									a__ :Union[str, Any]						  =    torch.arange(__A   ,     device=encoder_input_tokens.device						)
									x += self.position_encoding(__A						)

									a__ :Dict						  =    self.dropout_pre(__A						)

									# inverted the attention mask
									a__ :Optional[Any]						  =    encoder_input_tokens.size()
									a__ :int						  =    self.get_extended_attention_mask(__A   ,     __A						)

									for lyr in self.encoders:
												a__ :List[str]						  =    lyr(__A   ,     __A						)[0]
									a__ :int						  =    self.layer_norm(__A						)

									return self.dropout_post(__A						), encoder_inputs_mask






def 				lowerCamelCase__	(      a	:   int = 1_000_000				)    ->	int:





			"""simple docstring"""
			a__ :int						  =    [i - 1 for i in range(limit + 1				)]

			for i in range(2	,  limit + 1				):
						if phi[i] == i - 1:
									for j in range(2 * i	,  limit + 1	,  a				):
												phi[j] -= phi[j] // i

			return sum(phi[2 : limit + 1]				)


if __name__ == "__main__":
		print(solution())


