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		(   UpperCamelCase_    ,     UpperCamelCase_    ,     UpperCamelCase_    ):
    @register_to_config
    def __init__(  self , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase = False , )       ->					Optional[Any]:
     super().__init__()

     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      nn.Embedding(lowerCAmelCase , lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      nn.Embedding(lowerCAmelCase , lowerCAmelCase   )
     SCREAMING_SNAKE_CASE__:   Tuple=      False

     SCREAMING_SNAKE_CASE__:   str=      nn.Dropout(p=lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   str=      TaConfig(
         vocab_size=lowerCAmelCase , d_model=lowerCAmelCase , num_heads=lowerCAmelCase , d_kv=lowerCAmelCase , d_ff=lowerCAmelCase , dropout_rate=lowerCAmelCase , feed_forward_proj=lowerCAmelCase , is_decoder=lowerCAmelCase , is_encoder_decoder=lowerCAmelCase , )

     SCREAMING_SNAKE_CASE__:   Any=      nn.ModuleList()
     for lyr_num in range(lowerCAmelCase   ):
      SCREAMING_SNAKE_CASE__:   Dict=      TaBlock(lowerCAmelCase   )
      self.encoders.append(lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   Optional[int]=      TaLayerNorm(lowerCAmelCase   )
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      nn.Dropout(p=lowerCAmelCase   )



    def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase   )       ->					int:
     SCREAMING_SNAKE_CASE__:   List[str]=      self.token_embedder(lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   str=      encoder_input_tokens.shape[1]
     SCREAMING_SNAKE_CASE__:   str=      torch.arange(lowerCAmelCase , device=encoder_input_tokens.device   )
     x += self.position_encoding(lowerCAmelCase   )

     SCREAMING_SNAKE_CASE__:   Any=      self.dropout_pre(lowerCAmelCase   )

     # inverted the attention mask
     SCREAMING_SNAKE_CASE__:   Dict=      encoder_input_tokens.size()
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      self.get_extended_attention_mask(lowerCAmelCase , lowerCAmelCase   )

     for lyr in self.encoders:
      SCREAMING_SNAKE_CASE__:   Tuple=      lyr(lowerCAmelCase , lowerCAmelCase   )[0]
     SCREAMING_SNAKE_CASE__:   Tuple=      self.layer_norm(lowerCAmelCase   )

     return self.dropout_post(lowerCAmelCase   ), encoder_inputs_mask


# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union


lowercase_     :   str 				=				re.compile(R'^(?P<major>\d+)' R'\.(?P<minor>\d+)' R'\.(?P<patch>\d+)$')






@total_ordering
@dataclass
class 		_lowerCamelCase		:
    __a  =      42
    __a  =      None
    __a  =      None
    __a  =      None
    __a  =      None
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__:   int=      _str_to_version_tuple(self.version_str   )
    def __repr__(  self   )       ->					Dict:
     return f'{self.tuple[0]}.{self.tuple[1]}.{self.tuple[2]}'
    @property
    def 						UpperCamelCase_				(  self   )       ->					List[str]:
     return self.major, self.minor, self.patch
    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					Dict:
     if isinstance(lowerCAmelCase , lowerCAmelCase   ):
      return Version(lowerCAmelCase   )
     elif isinstance(lowerCAmelCase , lowerCAmelCase   ):
      return other
     raise TypeError(f'{other} (type {type(lowerCAmelCase   )}) cannot be compared to version.'   )
    def __eq__(  self , lowerCAmelCase   )       ->					Optional[int]:
     try:
      SCREAMING_SNAKE_CASE__:   List[str]=      self._validate_operand(lowerCAmelCase   )
     except (TypeError, ValueError):
      return False
     else:
      return self.tuple == other.tuple
    def __lt__(  self , lowerCAmelCase   )       ->					List[str]:
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      self._validate_operand(lowerCAmelCase   )
     return self.tuple < other.tuple
    def __hash__(  self   )       ->					List[Any]:
     return hash(_version_tuple_to_str(self.tuple   )   )
    @classmethod
    def 						UpperCamelCase_				(  cls , lowerCAmelCase   )       ->					Tuple:
     SCREAMING_SNAKE_CASE__:   Dict=      {f.name for f in dataclasses.fields(cls   )}
     return cls(**{k: v for k, v in dic.items() if k in field_names}   )



    def 						UpperCamelCase_				(  self   )       ->					str:
     return self.version_str







def 			A__      (	snake_case_ :		int      ):
 SCREAMING_SNAKE_CASE__:   List[Any]=      _VERSION_REG.match(snake_case_      )
 if not res:
  raise ValueError(F'Invalid version \'{version_str}\'. Format should be x.y.z with {{x,y,z}} being digits.'      )
 return tuple(int(snake_case_      ) for v in [res.group('''major'''      ), res.group('''minor'''      ), res.group('''patch'''      )]      )







def 			A__      (	snake_case_ :		Union[str, Any]      ):
 return ".".join(str(snake_case_      ) for v in version_tuple      )

