
import functools
import operator

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


_A   =			logging.get_logger(__name__)

_A   =			{
    "facebook/wav2vec2-base-960h": "https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json",
    # See all Wav2Vec2 models at https://huggingface.co/models?filter=wav2vec2
}







class 					lowerCamelCase		(  A_  ):
     UpperCAmelCase__    :							Dict									=		"wav2vec2"





     def __init__(self				:   List[Any]    ,   _A				:   List[str]=3_2    ,   _A				:   Dict=7_6_8    ,   _A				:   Optional[int]=1_2    ,   _A				:   Any=1_2    ,   _A				:   Tuple=3_0_7_2    ,   _A				:   Tuple="gelu"    ,   _A				:   Union[str, Any]=0.1    ,   _A				:   int=0.1    ,   _A				:   Any=0.1    ,   _A				:   Any=0.0    ,   _A				:   List[Any]=0.0    ,   _A				:   Optional[int]=0.1    ,   _A				:   Optional[Any]=0.1    ,   _A				:   Optional[Any]=0.02    ,   _A				:   Tuple=1E-5    ,   _A				:   Optional[Any]="group"    ,   _A				:   int="gelu"    ,   _A				:   List[Any]=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2, 5_1_2)    ,   _A				:   List[Any]=(5, 2, 2, 2, 2, 2, 2)    ,   _A				:   str=(1_0, 3, 3, 3, 3, 2, 2)    ,   _A				:   Optional[Any]=False    ,   _A				:   Optional[Any]=1_2_8    ,   _A				:   Any=1_6    ,   _A				:   List[Any]=False    ,   _A				:   List[Any]=True    ,   _A				:   List[str]=0.05    ,   _A				:   List[str]=1_0    ,   _A				:   Optional[Any]=2    ,   _A				:   int=0.0    ,   _A				:   Dict=1_0    ,   _A				:   Dict=0    ,   _A				:   int=3_2_0    ,   _A				:   List[Any]=2    ,   _A				:   List[Any]=0.1    ,   _A				:   Any=1_0_0    ,   _A				:   Any=2_5_6    ,   _A				:   Dict=2_5_6    ,   _A				:   Tuple=0.1    ,   _A				:   str="sum"    ,   _A				:   List[Any]=False    ,   _A				:   List[Any]=False    ,   _A				:   Any=2_5_6    ,   _A				:   Any=(5_1_2, 5_1_2, 5_1_2, 5_1_2, 1_5_0_0)    ,   _A				:   List[Any]=(5, 3, 3, 1, 1)    ,   _A				:   Tuple=(1, 2, 3, 1, 1)    ,   _A				:   int=5_1_2    ,   _A				:   Dict=0    ,   _A				:   str=1    ,   _A				:   Optional[Any]=2    ,   _A				:   List[Any]=False    ,   _A				:   List[str]=3    ,   _A				:   str=2    ,   _A				:   Optional[int]=3    ,   _A				:   Union[str, Any]=None    ,   _A				:   Dict=None    ,   **_A				:   Optional[int]    ,   )						->						int:
         super().__init__(**_A    ,   pad_token_id=_A    ,   bos_token_id=_A    ,   eos_token_id=_A       )
         snake_case								= hidden_size
         snake_case								= feat_extract_norm
         snake_case								= feat_extract_activation
         snake_case								= list(_A       )
         snake_case								= list(_A       )
         snake_case								= list(_A       )
         snake_case								= conv_bias
         snake_case								= num_conv_pos_embeddings
         snake_case								= num_conv_pos_embedding_groups
         snake_case								= len(self.conv_dim       )
         snake_case								= num_hidden_layers
         snake_case								= intermediate_size
         snake_case								= hidden_act
         snake_case								= num_attention_heads
         snake_case								= hidden_dropout
         snake_case								= attention_dropout
         snake_case								= activation_dropout
         snake_case								= feat_proj_dropout
         snake_case								= final_dropout
         snake_case								= layerdrop
         snake_case								= layer_norm_eps
         snake_case								= initializer_range
         snake_case								= vocab_size
         snake_case								= do_stable_layer_norm
         snake_case								= 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
         snake_case								= apply_spec_augment
         snake_case								= mask_time_prob
         snake_case								= mask_time_length
         snake_case								= mask_time_min_masks
         snake_case								= mask_feature_prob
         snake_case								= mask_feature_length
         snake_case								= mask_feature_min_masks

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

         # ctc loss
         snake_case								= ctc_loss_reduction
         snake_case								= ctc_zero_infinity

         # adapter
         snake_case								= add_adapter
         snake_case								= adapter_kernel_size
         snake_case								= adapter_stride
         snake_case								= num_adapter_layers
         snake_case								= output_hidden_size or hidden_size
         snake_case								= adapter_attn_dim

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

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





     @property
     def 		UpperCAmelCase(self				:   Union[str, Any]       )						->						str:
         return functools.reduce(operator.mul    ,   self.conv_stride    ,   1       )



class 					lowerCamelCase		:





     def __init__(self				:   List[Any]    ,   _A				:   str       )						->						Any:
         # we need a list not a string, so do something to change the type
         snake_case								= arr.split(","       )





     def 		UpperCAmelCase(self				:   str       )						->						str:
         snake_case								= [int(self.array[0]       )] * len(self.array       )
         snake_case								= [int(self.array[0]       )] * len(self.array       )
         for i in range(1    ,   len(self.array       )       ):
             snake_case								= max(
                 int(self.array[i]       ) + sum_value[i - 1]    ,   int(self.array[i]       )       )
             snake_case								= max(sum_value[i]    ,   rear[i - 1]       )
         return rear[len(self.array       ) - 1]


if __name__ == "__main__":
   _A   =			input("please input some numbers:")
   _A   =			SubArray(whole_array)
   _A   =			array.solve_sub_array()
   print(("the results is:", re))

