'''simple docstring'''

import functools
import operator

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


_lowerCamelCase :				Optional[int]														= logging.get_logger(__name__)

_lowerCamelCase :				int														= {
    """facebook/hubert-base-ls960""": """https://huggingface.co/facebook/hubert-base-ls960/resolve/main/config.json""",
    # See all Hubert models at https://huggingface.co/models?filter=hubert
}




class    lowerCamelCase__  (   __snake_case     ):
   __UpperCAmelCase           =						"""hubert"""



   def __init__(    self					,      lowerCAmelCase__=32					,      lowerCAmelCase__=768					,      lowerCAmelCase__=12					,      lowerCAmelCase__=12					,      lowerCAmelCase__=3_072					,      lowerCAmelCase__="gelu"					,      lowerCAmelCase__=0.1					,      lowerCAmelCase__=0.1					,      lowerCAmelCase__=0.1					,      lowerCAmelCase__=True					,      lowerCAmelCase__=0.0					,      lowerCAmelCase__=0.1					,      lowerCAmelCase__=0.1					,      lowerCAmelCase__=0.02					,      lowerCAmelCase__=1e-5					,      lowerCAmelCase__="group"					,      lowerCAmelCase__="gelu"					,      lowerCAmelCase__=(512, 512, 512, 512, 512, 512, 512)					,      lowerCAmelCase__=(5, 2, 2, 2, 2, 2, 2)					,      lowerCAmelCase__=(10, 3, 3, 3, 3, 2, 2)					,      lowerCAmelCase__=False					,      lowerCAmelCase__=128					,      lowerCAmelCase__=16					,      lowerCAmelCase__=False					,      lowerCAmelCase__=True					,      lowerCAmelCase__=0.05					,      lowerCAmelCase__=10					,      lowerCAmelCase__=2					,      lowerCAmelCase__=0.0					,      lowerCAmelCase__=10					,      lowerCAmelCase__=0					,      lowerCAmelCase__="sum"					,      lowerCAmelCase__=False					,      lowerCAmelCase__=False					,      lowerCAmelCase__=256					,      lowerCAmelCase__=0					,      lowerCAmelCase__=1					,      lowerCAmelCase__=2					,      **lowerCAmelCase__					,      )				->     Dict:
        """simple docstring"""





        super().__init__(**lowerCAmelCase__					,      pad_token_id=lowerCAmelCase__					,      bos_token_id=lowerCAmelCase__					,      eos_token_id=lowerCAmelCase__     )
        _UpperCamelCase  :Optional[Any]       =hidden_size
        _UpperCamelCase  :Union[str, Any]       =feat_extract_norm
        _UpperCamelCase  :Union[str, Any]       =feat_extract_activation
        _UpperCamelCase  :int       =list(lowerCAmelCase__     )
        _UpperCamelCase  :Dict       =list(lowerCAmelCase__     )
        _UpperCamelCase  :Dict       =list(lowerCAmelCase__     )
        _UpperCamelCase  :Optional[int]       =conv_bias
        _UpperCamelCase  :Union[str, Any]       =num_conv_pos_embeddings
        _UpperCamelCase  :int       =num_conv_pos_embedding_groups
        _UpperCamelCase  :Dict       =len(self.conv_dim     )
        _UpperCamelCase  :Dict       =num_hidden_layers
        _UpperCamelCase  :Tuple       =intermediate_size
        _UpperCamelCase  :Optional[Any]       =hidden_act
        _UpperCamelCase  :Dict       =num_attention_heads
        _UpperCamelCase  :Optional[int]       =hidden_dropout
        _UpperCamelCase  :int       =attention_dropout
        _UpperCamelCase  :Optional[Any]       =activation_dropout
        _UpperCamelCase  :List[Any]       =feat_proj_layer_norm
        _UpperCamelCase  :Union[str, Any]       =feat_proj_dropout
        _UpperCamelCase  :Optional[int]       =final_dropout
        _UpperCamelCase  :Optional[int]       =layerdrop
        _UpperCamelCase  :Union[str, Any]       =layer_norm_eps
        _UpperCamelCase  :str       =initializer_range
        _UpperCamelCase  :List[str]       =vocab_size
        _UpperCamelCase  :int       =do_stable_layer_norm
        _UpperCamelCase  :int       =use_weighted_layer_sum
        _UpperCamelCase  :Optional[int]       =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
        _UpperCamelCase  :Union[str, Any]       =apply_spec_augment
        _UpperCamelCase  :Tuple       =mask_time_prob
        _UpperCamelCase  :Union[str, Any]       =mask_time_length
        _UpperCamelCase  :Optional[int]       =mask_time_min_masks
        _UpperCamelCase  :Any       =mask_feature_prob
        _UpperCamelCase  :Any       =mask_feature_length
        _UpperCamelCase  :List[Any]       =mask_feature_min_masks

        # ctc loss
        _UpperCamelCase  :Optional[int]       =ctc_loss_reduction
        _UpperCamelCase  :List[str]       =ctc_zero_infinity




   @property
   def  _UpperCamelCase		(    self     )				->     Optional[Any]:
        """simple docstring"""





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






def  A_(      A = 1000 ):
	UpperCAmelCase_		    =  0
	for i in range(A ):
		if i % 3 == 0 or i % 5 == 0:
			result += i
	return result


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


