



import functools
import operator

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


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

__snake_case    :		str  ={
    '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 	lowerCamelCase__      (							lowerCamelCase__):




		'''simple docstring'''



		snake_case_     ="""unispeech-sat"""



		def __init__(self		,__lowerCamelCase=32		,__lowerCamelCase=7_68		,__lowerCamelCase=12		,__lowerCamelCase=12		,__lowerCamelCase=30_72		,__lowerCamelCase="gelu"		,__lowerCamelCase=0.1		,__lowerCamelCase=0.1		,__lowerCamelCase=0.1		,__lowerCamelCase=0.0		,__lowerCamelCase=0.0		,__lowerCamelCase=0.1		,__lowerCamelCase=0.1		,__lowerCamelCase=0.02		,__lowerCamelCase=1e-5		,__lowerCamelCase="group"		,__lowerCamelCase="gelu"		,__lowerCamelCase=(5_12, 5_12, 5_12, 5_12, 5_12, 5_12, 5_12)		,__lowerCamelCase=(5, 2, 2, 2, 2, 2, 2)		,__lowerCamelCase=(10, 3, 3, 3, 3, 2, 2)		,__lowerCamelCase=False		,__lowerCamelCase=1_28		,__lowerCamelCase=16		,__lowerCamelCase=False		,__lowerCamelCase=True		,__lowerCamelCase=0.05		,__lowerCamelCase=10		,__lowerCamelCase=2		,__lowerCamelCase=0.0		,__lowerCamelCase=10		,__lowerCamelCase=0		,__lowerCamelCase=3_20		,__lowerCamelCase=2		,__lowerCamelCase=0.1		,__lowerCamelCase=1_00		,__lowerCamelCase=2_56		,__lowerCamelCase=2_56		,__lowerCamelCase=0.1		,__lowerCamelCase="mean"		,__lowerCamelCase=False		,__lowerCamelCase=False		,__lowerCamelCase=2_56		,__lowerCamelCase=(5_12, 5_12, 5_12, 5_12, 15_00)		,__lowerCamelCase=(5, 3, 3, 1, 1)		,__lowerCamelCase=(1, 2, 3, 1, 1)		,__lowerCamelCase=5_12		,__lowerCamelCase=0		,__lowerCamelCase=1		,__lowerCamelCase=2		,__lowerCamelCase=5_04		,**__lowerCamelCase		,)					->      Optional[Any]:

						"""simple docstring"""






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

						# parameters for pretraining with codevector quantized representations
						lowerCAmelCase__					:    List[str]												=					num_codevectors_per_group
						lowerCAmelCase__					:    str												=					num_codevector_groups
						lowerCAmelCase__					:    Any												=					contrastive_logits_temperature
						lowerCAmelCase__					:    int												=					feat_quantizer_dropout
						lowerCAmelCase__					:    Tuple												=					num_negatives
						lowerCAmelCase__					:    List[str]												=					codevector_dim
						lowerCAmelCase__					:    Optional[Any]												=					proj_codevector_dim
						lowerCAmelCase__					:    int												=					diversity_loss_weight

						# ctc loss
						lowerCAmelCase__					:    List[Any]												=					ctc_loss_reduction
						lowerCAmelCase__					:    Tuple												=					ctc_zero_infinity

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

						# XVector-specific parameters. Feel free to ignore for other classes.
						lowerCAmelCase__					:    Dict												=					list(__lowerCamelCase			)
						lowerCAmelCase__					:    Any												=					list(__lowerCamelCase			)
						lowerCAmelCase__					:    Optional[int]												=					list(__lowerCamelCase			)
						lowerCAmelCase__					:    Tuple												=					xvector_output_dim



		@property
		def 		lowerCAmelCase__				(self			)					->      Any:

						"""simple docstring"""






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






def      lowerCAmelCase__		(   lowerCamelCase_		:		int = 1000000):





				'''simple docstring'''

				lowerCAmelCase__					:    int												=					set(range(3	,lowerCamelCase_	,2))
				primes.add(2)
				for p in range(3	,lowerCamelCase_	,2):
								if p not in primes:
												continue
								primes.difference_update(set(range(p * p	,lowerCamelCase_	,lowerCamelCase_)))

				lowerCAmelCase__					:    int												=					[float(lowerCamelCase_) for n in range(limit + 1)]

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

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


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

