

'''simple docstring'''







import functools
import operator

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


__lowerCamelCase		       =    logging.get_logger(__name__)

__lowerCamelCase		       =    {
    'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json',
    # See all WavLM models at https://huggingface.co/models?filter=wavlm
}


class 					A__      (      lowerCamelCase__			):
    lowercase						=		"wavlm"



    def __init__(					self		,				UpperCamelCase__=32		,				UpperCamelCase__=768		,				UpperCamelCase__=12		,				UpperCamelCase__=12		,				UpperCamelCase__=3072		,				UpperCamelCase__="gelu"		,				UpperCamelCase__=0.1		,				UpperCamelCase__=0.1		,				UpperCamelCase__=0.1		,				UpperCamelCase__=0.0		,				UpperCamelCase__=0.1		,				UpperCamelCase__=0.1		,				UpperCamelCase__=0.02		,				UpperCamelCase__=1e-5		,				UpperCamelCase__="group"		,				UpperCamelCase__="gelu"		,				UpperCamelCase__=(512, 512, 512, 512, 512, 512, 512)		,				UpperCamelCase__=(5, 2, 2, 2, 2, 2, 2)		,				UpperCamelCase__=(10, 3, 3, 3, 3, 2, 2)		,				UpperCamelCase__=False		,				UpperCamelCase__=128		,				UpperCamelCase__=16		,				UpperCamelCase__=320		,				UpperCamelCase__=800		,				UpperCamelCase__=False		,				UpperCamelCase__=True		,				UpperCamelCase__=0.05		,				UpperCamelCase__=10		,				UpperCamelCase__=2		,				UpperCamelCase__=0.0		,				UpperCamelCase__=10		,				UpperCamelCase__=320		,				UpperCamelCase__=2		,				UpperCamelCase__=0.1		,				UpperCamelCase__=100		,				UpperCamelCase__=256		,				UpperCamelCase__=256		,				UpperCamelCase__=0.1		,				UpperCamelCase__="mean"		,				UpperCamelCase__=False		,				UpperCamelCase__=False		,				UpperCamelCase__=256		,				UpperCamelCase__=(512, 512, 512, 512, 1500)		,				UpperCamelCase__=(5, 3, 3, 1, 1)		,				UpperCamelCase__=(1, 2, 3, 1, 1)		,				UpperCamelCase__=512		,				UpperCamelCase__=80		,				UpperCamelCase__=0		,				UpperCamelCase__=1		,				UpperCamelCase__=2		,				UpperCamelCase__=False		,				UpperCamelCase__=3		,				UpperCamelCase__=2		,				UpperCamelCase__=3		,				UpperCamelCase__=None		,				**UpperCamelCase__		,				)						->      Tuple:





           '''simple docstring'''
           super().__init__(**__lowerCamelCase		,				pad_token_id=__lowerCamelCase		,				bos_token_id=__lowerCamelCase		,				eos_token_id=__lowerCamelCase       )
           A_						=      hidden_size
           A_						=      feat_extract_norm
           A_						=      feat_extract_activation
           A_						=      list(__lowerCamelCase       )
           A_						=      list(__lowerCamelCase       )
           A_						=      list(__lowerCamelCase       )
           A_						=      conv_bias
           A_						=      num_buckets
           A_						=      max_bucket_distance
           A_						=      num_conv_pos_embeddings
           A_						=      num_conv_pos_embedding_groups
           A_						=      len(self.conv_dim       )
           A_						=      num_hidden_layers
           A_						=      intermediate_size
           A_						=      hidden_act
           A_						=      num_attention_heads
           A_						=      hidden_dropout
           A_						=      attention_dropout
           A_						=      activation_dropout
           A_						=      feat_proj_dropout
           A_						=      final_dropout
           A_						=      layerdrop
           A_						=      layer_norm_eps
           A_						=      initializer_range
           A_						=      num_ctc_classes
           A_						=      vocab_size
           A_						=      do_stable_layer_norm
           A_						=      use_weighted_layer_sum
           A_						=      classifier_proj_size

           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
           A_						=      apply_spec_augment
           A_						=      mask_time_prob
           A_						=      mask_time_length
           A_						=      mask_time_min_masks
           A_						=      mask_feature_prob
           A_						=      mask_feature_length

           # parameters for pretraining with codevector quantized representations
           A_						=      num_codevectors_per_group
           A_						=      num_codevector_groups
           A_						=      contrastive_logits_temperature
           A_						=      num_negatives
           A_						=      codevector_dim
           A_						=      proj_codevector_dim
           A_						=      diversity_loss_weight

           # ctc loss
           A_						=      ctc_loss_reduction
           A_						=      ctc_zero_infinity

           # adapter
           A_						=      add_adapter
           A_						=      adapter_kernel_size
           A_						=      adapter_stride
           A_						=      num_adapter_layers
           A_						=      output_hidden_size or hidden_size

           # SequenceClassification-specific parameter. Feel free to ignore for other classes.
           A_						=      classifier_proj_size

           # XVector-specific parameters. Feel free to ignore for other classes.
           A_						=      list(__lowerCamelCase       )
           A_						=      list(__lowerCamelCase       )
           A_						=      list(__lowerCamelCase       )
           A_						=      xvector_output_dim







    @property
    def 					snake_case_			(					self       )						->      List[str]:





           '''simple docstring'''
           return functools.reduce(operator.mul		,				self.conv_stride		,				1       )



'''simple docstring'''







import os

__lowerCamelCase		       =    {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def       UpperCAmelCase__    (      UpperCAmelCase__				)			->			int:
       A_						=      0

       A_						=      0
       while index < len(UpperCAmelCase__				) - 1:
              A_						=      SYMBOLS[numerals[index]]
              A_						=      SYMBOLS[numerals[index + 1]]
              if current_value < next_value:
                     total_value -= current_value
              else:
                     total_value += current_value
              index += 1
       total_value += SYMBOLS[numerals[index]]

       return total_value
def       UpperCAmelCase__    (      UpperCAmelCase__				)			->			str:
       A_						=      """"""

       A_						=      num // 10_00
       numerals += m_count * "M"
       num %= 10_00

       A_						=      num // 1_00
       if c_count == 9:
              numerals += "CM"
              c_count -= 9
       elif c_count == 4:
              numerals += "CD"
              c_count -= 4
       if c_count >= 5:
              numerals += "D"
              c_count -= 5
       numerals += c_count * "C"
       num %= 1_00

       A_						=      num // 10
       if x_count == 9:
              numerals += "XC"
              x_count -= 9
       elif x_count == 4:
              numerals += "XL"
              x_count -= 4
       if x_count >= 5:
              numerals += "L"
              x_count -= 5
       numerals += x_count * "X"
       num %= 10

       if num == 9:
              numerals += "IX"
              num -= 9
       elif num == 4:
              numerals += "IV"
              num -= 4
       if num >= 5:
              numerals += "V"
              num -= 5
       numerals += num * "I"

       return numerals
def       UpperCAmelCase__    (      UpperCAmelCase__ = "/p089_roman.txt"				)			->			int:
       A_						=      0

       with open(os.path.dirname(UpperCAmelCase__				) + roman_numerals_filename				) as filea:
              A_						=      filea.readlines()

       for line in lines:
              A_						=      line.strip()
              A_						=      parse_roman_numerals(UpperCAmelCase__				)
              A_						=      generate_roman_numerals(UpperCAmelCase__				)
              savings += len(UpperCAmelCase__				) - len(UpperCAmelCase__				)

       return savings


if __name__ == "__main__":
      print(f"""{solution() = }""")
