'''simple docstring'''
import functools
import operator

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


_A		:      Optional[Any]						   =logging.get_logger(__name__)

_A		:      Any						   ={
    """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			(	UpperCAmelCase__					):
      UpperCAmelCase_	:						List[str]	 =       """hubert"""







      def __init__(  self  ,    lowercase=32  ,    lowercase=768  ,    lowercase=12  ,    lowercase=12  ,    lowercase=3072  ,    lowercase="gelu"  ,    lowercase=0.1  ,    lowercase=0.1  ,    lowercase=0.1  ,    lowercase=True  ,    lowercase=0.0  ,    lowercase=0.1  ,    lowercase=0.1  ,    lowercase=0.02  ,    lowercase=1e-5  ,    lowercase="group"  ,    lowercase="gelu"  ,    lowercase=(512, 512, 512, 512, 512, 512, 512)  ,    lowercase=(5, 2, 2, 2, 2, 2, 2)  ,    lowercase=(10, 3, 3, 3, 3, 2, 2)  ,    lowercase=False  ,    lowercase=128  ,    lowercase=16  ,    lowercase=False  ,    lowercase=True  ,    lowercase=0.05  ,    lowercase=10  ,    lowercase=2  ,    lowercase=0.0  ,    lowercase=10  ,    lowercase=0  ,    lowercase="sum"  ,    lowercase=False  ,    lowercase=False  ,    lowercase=256  ,    lowercase=0  ,    lowercase=1  ,    lowercase=2  ,    **lowercase  ,    ):
        super().__init__(**__lowercase  ,    pad_token_id=__lowercase  ,    bos_token_id=__lowercase  ,    eos_token_id=__lowercase     )
        lowercase				:							str									=   hidden_size
        lowercase				:							Union[str, Any]									=   feat_extract_norm
        lowercase				:							str									=   feat_extract_activation
        lowercase				:							List[Any]									=   list(__lowercase     )
        lowercase				:							List[str]									=   list(__lowercase     )
        lowercase				:							List[str]									=   list(__lowercase     )
        lowercase				:							str									=   conv_bias
        lowercase				:							Optional[Any]									=   num_conv_pos_embeddings
        lowercase				:							Dict									=   num_conv_pos_embedding_groups
        lowercase				:							Dict									=   len(self.conv_dim     )
        lowercase				:							Any									=   num_hidden_layers
        lowercase				:							Tuple									=   intermediate_size
        lowercase				:							List[Any]									=   hidden_act
        lowercase				:							Tuple									=   num_attention_heads
        lowercase				:							Optional[Any]									=   hidden_dropout
        lowercase				:							List[str]									=   attention_dropout
        lowercase				:							str									=   activation_dropout
        lowercase				:							Dict									=   feat_proj_layer_norm
        lowercase				:							Any									=   feat_proj_dropout
        lowercase				:							Optional[int]									=   final_dropout
        lowercase				:							Optional[int]									=   layerdrop
        lowercase				:							Optional[Any]									=   layer_norm_eps
        lowercase				:							List[Any]									=   initializer_range
        lowercase				:							List[str]									=   vocab_size
        lowercase				:							Optional[Any]									=   do_stable_layer_norm
        lowercase				:							Dict									=   use_weighted_layer_sum
        lowercase				:							Optional[Any]									=   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
        lowercase				:							List[Any]									=   apply_spec_augment
        lowercase				:							List[Any]									=   mask_time_prob
        lowercase				:							Optional[Any]									=   mask_time_length
        lowercase				:							Dict									=   mask_time_min_masks
        lowercase				:							int									=   mask_feature_prob
        lowercase				:							Union[str, Any]									=   mask_feature_length
        lowercase				:							int									=   mask_feature_min_masks

        # ctc loss
        lowercase				:							Any									=   ctc_loss_reduction
        lowercase				:							Tuple									=   ctc_zero_infinity







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



import doctest

import projectq
from projectq.ops import H, Measure



def       lowerCAmelCase			(		lowerCAmelCase_			)->			int:
				lowerCAmelCase_			:   List[Any]     					=					quantum_engine.allocate_qubit()
				H | qubit
				Measure | qubit
				return int(lowerCAmelCase_			)


if __name__ == "__main__":
						doctest.testmod()

						# initialises a new quantum backend
						_UpperCAmelCase      :	str  =projectq.MainEngine()

						# Generate a list of 10 random numbers
						_UpperCAmelCase      :	Optional[int]  =[get_random_number(quantum_engine) for _ in range(10)]

						# Flushes the quantum engine from memory
						quantum_engine.flush()

						print("""Random numbers""", random_numbers_list)