

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_ (			_lowerCAmelCase	,				_lowerCAmelCase	,				_lowerCAmelCase):




 @register_to_config
 def __init__(			self  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase  ,  _UpperCAmelCase = False  ,  ):
   super().__init__()

   __UpperCAmelCase	:  List[str]		=     nn.Linear(_UpperCAmelCase  ,  _UpperCAmelCase  ,  bias=_UpperCAmelCase							)

   __UpperCAmelCase	:  int		=     nn.Embedding(_UpperCAmelCase  ,  _UpperCAmelCase							)
   __UpperCAmelCase	:  Optional[int]		=     False

   __UpperCAmelCase	:  Optional[Any]		=     nn.Dropout(p=_UpperCAmelCase							)

   __UpperCAmelCase	:  List[Any]		=     TaConfig(
       d_model=_UpperCAmelCase  ,  num_heads=_UpperCAmelCase  ,  d_kv=_UpperCAmelCase  ,  d_ff=_UpperCAmelCase  ,  feed_forward_proj=_UpperCAmelCase  ,  dropout_rate=_UpperCAmelCase  ,  is_decoder=_UpperCAmelCase  ,  is_encoder_decoder=_UpperCAmelCase  ,  )
   __UpperCAmelCase	:  str		=     nn.ModuleList()
   for lyr_num in range(_UpperCAmelCase							):
     __UpperCAmelCase	:  Tuple		=     TaBlock(_UpperCAmelCase							)
     self.encoders.append(_UpperCAmelCase							)

   __UpperCAmelCase	:  str		=     TaLayerNorm(_UpperCAmelCase							)
   __UpperCAmelCase	:  str		=     nn.Dropout(p=_UpperCAmelCase							)




 def     a       (			self  ,  _UpperCAmelCase  ,  _UpperCAmelCase							):
   __UpperCAmelCase	:  Tuple		=     self.input_proj(_UpperCAmelCase							)

   # terminal relative positional encodings
   __UpperCAmelCase	:  int		=     encoder_inputs.shape[1]
   __UpperCAmelCase	:  Dict		=     torch.arange(_UpperCAmelCase  ,  device=encoder_inputs.device							)

   __UpperCAmelCase	:  Union[str, Any]		=     encoder_inputs_mask.sum(-1							)
   __UpperCAmelCase	:  Optional[Any]		=     torch.roll(input_positions.unsqueeze(0							)  ,  tuple(seq_lens.tolist()							)  ,  dims=0							)
   x += self.position_encoding(_UpperCAmelCase							)

   __UpperCAmelCase	:  str		=     self.dropout_pre(_UpperCAmelCase							)

   # inverted the attention mask
   __UpperCAmelCase	:  List[Any]		=     encoder_inputs.size()
   __UpperCAmelCase	:  List[str]		=     self.get_extended_attention_mask(_UpperCAmelCase  ,  _UpperCAmelCase							)

   for lyr in self.encoders:
     __UpperCAmelCase	:  Optional[int]		=     lyr(_UpperCAmelCase  ,  _UpperCAmelCase							)[0]
   __UpperCAmelCase	:  Union[str, Any]		=     self.layer_norm(_UpperCAmelCase							)

   return self.dropout_post(_UpperCAmelCase							), encoder_inputs_mask






# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run

import sys
import warnings
from os.path import abspath, dirname, join


# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
snake_case__						      =			abspath(join(dirname(dirname(dirname(__file__))), 'src'))
sys.path.insert(1, git_repo_path)


# silence FutureWarning warnings in tests since often we can't act on them until
# they become normal warnings - i.e. the tests still need to test the current functionality
warnings.simplefilter(action='ignore', category=FutureWarning)
def    __magic_name__(	__UpperCAmelCase		)    ->     int:



      '''simple docstring'''

      from transformers.testing_utils import pytest_addoption_shared

      pytest_addoption_shared(__UpperCAmelCase		)




def    __magic_name__(	__UpperCAmelCase		)    ->     List[str]:



      '''simple docstring'''

      from transformers.testing_utils import pytest_terminal_summary_main

      _lowerCamelCase           =					terminalreporter.config.getoption('''--make-reports'''		)
      if make_reports:
            pytest_terminal_summary_main(__UpperCAmelCase			,    id=__UpperCAmelCase		)