

import functools
import operator

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


snake_case_			  = logging.get_logger(__name__)

snake_case_			  = {
    '''microsoft/unispeech-sat-base-100h-libri-ft''': (
        '''https://huggingface.co/microsoft/unispeech-sat-base-100h-libri-ft/resolve/main/config.json'''
    ),
    # See all UniSpeechSat models at https://huggingface.co/models?filter=unispeech_sat
}


class       SCREAMING_SNAKE_CASE__					(_snake_case     ):
    __lowerCamelCase						:       int														=     """unispeech-sat"""





    def __init__(      self						,   a=32						,   a=768						,   a=12						,   a=12						,   a=3072						,   a="gelu"						,   a=0.1						,   a=0.1						,   a=0.1						,   a=0.0						,   a=0.0						,   a=0.1						,   a=0.1						,   a=0.02						,   a=1e-5						,   a="group"						,   a="gelu"						,   a=(512, 512, 512, 512, 512, 512, 512)						,   a=(5, 2, 2, 2, 2, 2, 2)						,   a=(10, 3, 3, 3, 3, 2, 2)						,   a=False						,   a=128						,   a=16						,   a=False						,   a=True						,   a=0.05						,   a=10						,   a=2						,   a=0.0						,   a=10						,   a=0						,   a=320						,   a=2						,   a=0.1						,   a=100						,   a=256						,   a=256						,   a=0.1						,   a="mean"						,   a=False						,   a=False						,   a=256						,   a=(512, 512, 512, 512, 1500)						,   a=(5, 3, 3, 1, 1)						,   a=(1, 2, 3, 1, 1)						,   a=512						,   a=0						,   a=1						,   a=2						,   a=504						,   **a						,   ):
         super().__init__(**_lowerCamelCase						,   pad_token_id=_lowerCamelCase						,   bos_token_id=_lowerCamelCase						,   eos_token_id=_lowerCamelCase)
         lowercase__    :   List[Any]      =       hidden_size
         lowercase__    :   Dict      =       feat_extract_norm
         lowercase__    :   List[Any]      =       feat_extract_activation
         lowercase__    :   List[Any]      =       list(_lowerCamelCase)
         lowercase__    :   Optional[int]      =       list(_lowerCamelCase)
         lowercase__    :   List[str]      =       list(_lowerCamelCase)
         lowercase__    :   Optional[int]      =       conv_bias
         lowercase__    :   Any      =       num_conv_pos_embeddings
         lowercase__    :   Any      =       num_conv_pos_embedding_groups
         lowercase__    :   int      =       len(self.conv_dim)
         lowercase__    :   str      =       num_hidden_layers
         lowercase__    :   Dict      =       intermediate_size
         lowercase__    :   Optional[Any]      =       hidden_act
         lowercase__    :   List[str]      =       num_attention_heads
         lowercase__    :   Dict      =       hidden_dropout
         lowercase__    :   Union[str, Any]      =       attention_dropout
         lowercase__    :   List[Any]      =       activation_dropout
         lowercase__    :   str      =       feat_proj_dropout
         lowercase__    :   Union[str, Any]      =       final_dropout
         lowercase__    :   List[str]      =       layerdrop
         lowercase__    :   Dict      =       layer_norm_eps
         lowercase__    :   Any      =       initializer_range
         lowercase__    :   Optional[int]      =       vocab_size
         lowercase__    :   int      =       num_clusters
         lowercase__    :   List[str]      =       do_stable_layer_norm
         lowercase__    :   List[str]      =       use_weighted_layer_sum

         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
         lowercase__    :   List[Any]      =       apply_spec_augment
         lowercase__    :   Tuple      =       mask_time_prob
         lowercase__    :   List[Any]      =       mask_time_length
         lowercase__    :   Dict      =       mask_time_min_masks
         lowercase__    :   Optional[int]      =       mask_feature_prob
         lowercase__    :   List[Any]      =       mask_feature_length
         lowercase__    :   Any      =       mask_feature_min_masks

         # parameters for pretraining with codevector quantized representations
         lowercase__    :   int      =       num_codevectors_per_group
         lowercase__    :   int      =       num_codevector_groups
         lowercase__    :   Union[str, Any]      =       contrastive_logits_temperature
         lowercase__    :   Any      =       feat_quantizer_dropout
         lowercase__    :   Union[str, Any]      =       num_negatives
         lowercase__    :   Any      =       codevector_dim
         lowercase__    :   str      =       proj_codevector_dim
         lowercase__    :   Any      =       diversity_loss_weight

         # ctc loss
         lowercase__    :   Any      =       ctc_loss_reduction
         lowercase__    :   str      =       ctc_zero_infinity

         # SequenceClassification-specific parameter. Feel free to ignore for other classes.
         lowercase__    :   str      =       classifier_proj_size

         # XVector-specific parameters. Feel free to ignore for other classes.
         lowercase__    :   Optional[Any]      =       list(_lowerCamelCase)
         lowercase__    :   Dict      =       list(_lowerCamelCase)
         lowercase__    :   List[Any]      =       list(_lowerCamelCase)
         lowercase__    :   Optional[Any]      =       xvector_output_dim





    @property
    def       snake_case_				(      self):
         return functools.reduce(operator.mul						,   self.conv_stride						,   1)





def 				__lowerCamelCase						( UpperCAmelCase_						:		int = 100_0000						):




      """simple docstring"""





      a						:Any 							=       set(range(3 ,  UpperCAmelCase_ ,  2						)						)
      primes.add(2						)
      for p in range(3 ,  UpperCAmelCase_ ,  2						):
            if p not in primes:
                  continue
            primes.difference_update(set(range(p * p ,  UpperCAmelCase_ ,  UpperCAmelCase_						)						)						)

      a						:Union[str, Any] 							=       [float(UpperCAmelCase_						) for n in range(limit + 1						)]

      for p in primes:
            for n in range(UpperCAmelCase_ ,  limit + 1 ,  UpperCAmelCase_						):
                  phi[n] *= 1 - 1 / p

      return int(sum(phi[2:]						)						)


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





