





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_snake_case  :   Union[str, Any]						   =  logging.get_logger(__name__)

_snake_case  :   Dict						   =  {
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}



class     _UpperCAmelCase   (   _UpperCamelCase   ):

  """simple docstring"""


  a_      =			"""roberta-prelayernorm"""






  def __init__(    self			:		Tuple ,  lowerCAmelCase_			:		Dict=5_0_2_6_5 ,  lowerCAmelCase_			:		int=7_6_8 ,  lowerCAmelCase_			:		Tuple=1_2 ,  lowerCAmelCase_			:		int=1_2 ,  lowerCAmelCase_			:		Union[str, Any]=3_0_7_2 ,  lowerCAmelCase_			:		str="gelu" ,  lowerCAmelCase_			:		int=0.1 ,  lowerCAmelCase_			:		Dict=0.1 ,  lowerCAmelCase_			:		List[str]=5_1_2 ,  lowerCAmelCase_			:		str=2 ,  lowerCAmelCase_			:		str=0.02 ,  lowerCAmelCase_			:		Optional[Any]=1e-12 ,  lowerCAmelCase_			:		str=1 ,  lowerCAmelCase_			:		List[Any]=0 ,  lowerCAmelCase_			:		int=2 ,  lowerCAmelCase_			:		Tuple="absolute" ,  lowerCAmelCase_			:		Optional[int]=True ,  lowerCAmelCase_			:		int=None ,  **lowerCAmelCase_			:		int ,  )							->						Tuple:
     super().__init__(pad_token_id=lowerCAmelCase_ ,  bos_token_id=lowerCAmelCase_ ,  eos_token_id=lowerCAmelCase_ ,  **lowerCAmelCase_					)

     __lowerCAmelCase							     =     vocab_size
     __lowerCAmelCase							     =     hidden_size
     __lowerCAmelCase							     =     num_hidden_layers
     __lowerCAmelCase							     =     num_attention_heads
     __lowerCAmelCase							     =     hidden_act
     __lowerCAmelCase							     =     intermediate_size
     __lowerCAmelCase							     =     hidden_dropout_prob
     __lowerCAmelCase							     =     attention_probs_dropout_prob
     __lowerCAmelCase							     =     max_position_embeddings
     __lowerCAmelCase							     =     type_vocab_size
     __lowerCAmelCase							     =     initializer_range
     __lowerCAmelCase							     =     layer_norm_eps
     __lowerCAmelCase							     =     position_embedding_type
     __lowerCAmelCase							     =     use_cache
     __lowerCAmelCase							     =     classifier_dropout





class     _UpperCAmelCase   (   _UpperCamelCase   ):

  """simple docstring"""


  @property
  def     lowercase		(    self			:		str					)							->						Mapping[str, Mapping[int, str]]:
     if self.task == "multiple-choice":
        __lowerCAmelCase							     =     {0: 'batch', 1: 'choice', 2: 'sequence'}
     else:
        __lowerCAmelCase							     =     {0: 'batch', 1: 'sequence'}
     return OrderedDict(
         [
             ('input_ids', dynamic_axis),
             ('attention_mask', dynamic_axis),
         ]					)








import unittest

import numpy as np
import torch

from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad



class     _UpperCAmelCase   (   unittest.TestCase   ):

  """simple docstring"""


  def     lowercase		(    self			:		Any					)							->						Optional[int]:
     __lowerCAmelCase							     =     1_0






  def     lowercase		(    self			:		int					)							->						Union[str, Any]:
     __lowerCAmelCase							     =     [1, 2, 3, 4]
     __lowerCAmelCase							     =     [1, 2, 3, 4, 0, 0, 0, 0, 0, 0]
     self.assertEqual(truncate_or_pad(lowerCAmelCase_ ,  self.block_size ,  0					) ,  lowerCAmelCase_					)






  def     lowercase		(    self			:		Optional[Any]					)							->						List[str]:
     __lowerCAmelCase							     =     [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
     __lowerCAmelCase							     =     [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
     self.assertEqual(truncate_or_pad(lowerCAmelCase_ ,  self.block_size ,  0					) ,  lowerCAmelCase_					)






  def     lowercase		(    self			:		Any					)							->						Optional[Any]:
     __lowerCAmelCase							     =     [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0, 1_1, 1_2, 1_3]
     __lowerCAmelCase							     =     [1, 2, 3, 4, 5, 6, 7, 8, 9, 1_0]
     self.assertEqual(truncate_or_pad(lowerCAmelCase_ ,  self.block_size ,  0					) ,  lowerCAmelCase_					)






  def     lowercase		(    self			:		List[str]					)							->						Any:
     __lowerCAmelCase							     =     'It was the year of Our Lord one thousand seven hundred and\n        seventy-five.\n\nSpiritual revelations were conceded to England at that\n        favoured period, as at this.'
     __lowerCAmelCase     ,     __lowerCAmelCase							     =     process_story(lowerCAmelCase_					)
     self.assertEqual(lowerCAmelCase_ ,  []					)






  def     lowercase		(    self			:		Any					)							->						str:
     __lowerCAmelCase							     =     ''
     __lowerCAmelCase     ,     __lowerCAmelCase							     =     process_story(lowerCAmelCase_					)
     self.assertEqual(lowerCAmelCase_ ,  []					)
     self.assertEqual(lowerCAmelCase_ ,  []					)






  def     lowercase		(    self			:		int					)							->						int:
     __lowerCAmelCase							     =     (
         'It was the year of Our Lord one thousand seven hundred and '
         'seventy-five\n\nSpiritual revelations were conceded to England '
         'at that favoured period, as at this.\n@highlight\n\nIt was the best of times'
     )
     __lowerCAmelCase     ,     __lowerCAmelCase							     =     process_story(lowerCAmelCase_					)

     __lowerCAmelCase							     =     [
         'It was the year of Our Lord one thousand seven hundred and seventy-five.',
         'Spiritual revelations were conceded to England at that favoured period, as at this.',
     ]
     self.assertEqual(lowerCAmelCase_ ,  lowerCAmelCase_					)

     __lowerCAmelCase							     =     ['It was the best of times.']
     self.assertEqual(lowerCAmelCase_ ,  lowerCAmelCase_					)






  def     lowercase		(    self			:		Dict					)							->						Any:
     __lowerCAmelCase							     =     torch.tensor([1, 2, 3, 4]					)
     __lowerCAmelCase							     =     torch.tensor([1, 1, 1, 1]					)
     np.testing.assert_array_equal(build_mask(lowerCAmelCase_ ,  0					).numpy() ,  expected.numpy()					)






  def     lowercase		(    self			:		List[Any]					)							->						Optional[int]:
     __lowerCAmelCase							     =     torch.tensor([1, 2, 3, 4, 2_3, 2_3, 2_3]					)
     __lowerCAmelCase							     =     torch.tensor([1, 1, 1, 1, 0, 0, 0]					)
     np.testing.assert_array_equal(build_mask(lowerCAmelCase_ ,  2_3					).numpy() ,  expected.numpy()					)






  def     lowercase		(    self			:		str					)							->						List[Any]:
     __lowerCAmelCase							     =     torch.tensor([8, 2, 3, 4, 1, 1, 1]					)
     __lowerCAmelCase							     =     torch.tensor([1, 1, 1, 1, 0, 0, 0]					)
     np.testing.assert_array_equal(build_mask(lowerCAmelCase_ ,  1					).numpy() ,  expected.numpy()					)






  def     lowercase		(    self			:		Optional[Any]					)							->						Optional[int]:
     __lowerCAmelCase							     =     1_0_1
     __lowerCAmelCase							     =     torch.tensor([[1, 2, 3, 4, 5, 6], [1, 2, 3, 1_0_1, 5, 6], [1, 1_0_1, 3, 4, 1_0_1, 6]]					)
     __lowerCAmelCase							     =     torch.tensor([[1, 1, 1, 1, 1, 1], [1, 1, 1, 0, 0, 0], [1, 0, 0, 0, 1, 1]]					)

     __lowerCAmelCase							     =     compute_token_type_ids(lowerCAmelCase_ ,  lowerCAmelCase_					)
     np.testing.assert_array_equal(lowerCAmelCase_ ,  lowerCAmelCase_					)

