



import math

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


a__   :					str 						=      logging.get_logger(__name__)

a__   :					Dict 						=      {
    "facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json",
    # See all Data2VecAudio models at https://huggingface.co/models?filter=data2vec-audio
}



class    UpperCAmelCase__(				lowerCamelCase						):

   '''simple docstring'''




   A     :	int												=     "data2vec-audio"


   def __init__(    self	:      List[str]      ,					lowerCAmelCase	:      Tuple=32      ,					lowerCAmelCase	:      Any=7_68      ,					lowerCAmelCase	:      Dict=12      ,					lowerCAmelCase	:      Dict=12      ,					lowerCAmelCase	:      Optional[int]=30_72      ,					lowerCAmelCase	:      Tuple="gelu"      ,					lowerCAmelCase	:      Any=0.1      ,					lowerCAmelCase	:      int=0.1      ,					lowerCAmelCase	:      Any=0.1      ,					lowerCAmelCase	:      Dict=0.0      ,					lowerCAmelCase	:      str=0.1      ,					lowerCAmelCase	:      Tuple=0.1      ,					lowerCAmelCase	:      Any=0.02      ,					lowerCAmelCase	:      Any=1E-5      ,					lowerCAmelCase	:      Any="gelu"      ,					lowerCAmelCase	:      Union[str, Any]=(5_12, 5_12, 5_12, 5_12, 5_12, 5_12, 5_12)      ,					lowerCAmelCase	:      Optional[int]=(5, 2, 2, 2, 2, 2, 2)      ,					lowerCAmelCase	:      Optional[int]=(10, 3, 3, 3, 3, 2, 2)      ,					lowerCAmelCase	:      int=False      ,					lowerCAmelCase	:      Tuple=16      ,					lowerCAmelCase	:      Any=19      ,					lowerCAmelCase	:      Optional[Any]=5      ,					lowerCAmelCase	:      List[Any]=0.05      ,					lowerCAmelCase	:      List[str]=10      ,					lowerCAmelCase	:      Optional[Any]=2      ,					lowerCAmelCase	:      Any=0.0      ,					lowerCAmelCase	:      Dict=10      ,					lowerCAmelCase	:      List[str]=0      ,					lowerCAmelCase	:      Union[str, Any]="sum"      ,					lowerCAmelCase	:      List[str]=False      ,					lowerCAmelCase	:      List[Any]=False      ,					lowerCAmelCase	:      List[Any]=2_56      ,					lowerCAmelCase	:      Optional[Any]=(5_12, 5_12, 5_12, 5_12, 15_00)      ,					lowerCAmelCase	:      Optional[int]=(5, 3, 3, 1, 1)      ,					lowerCAmelCase	:      List[str]=(1, 2, 3, 1, 1)      ,					lowerCAmelCase	:      int=5_12      ,					lowerCAmelCase	:      int=0      ,					lowerCAmelCase	:      List[str]=1      ,					lowerCAmelCase	:      Optional[int]=2      ,					lowerCAmelCase	:      Dict=False      ,					lowerCAmelCase	:      Tuple=3      ,					lowerCAmelCase	:      str=2      ,					lowerCAmelCase	:      List[Any]=3      ,					lowerCAmelCase	:      List[str]=None      ,					**lowerCAmelCase	:      Optional[int]      ,					)						->					str:




         """simple docstring"""

         super().__init__(**lowerCAmelCase      ,					pad_token_id=lowerCAmelCase      ,					bos_token_id=lowerCAmelCase      ,					eos_token_id=lowerCAmelCase)
         lowercase__  =	hidden_size
         lowercase__  =	feat_extract_activation
         lowercase__  =	list(lowerCAmelCase)
         lowercase__  =	list(lowerCAmelCase)
         lowercase__  =	list(lowerCAmelCase)
         lowercase__  =	conv_bias
         lowercase__  =	num_conv_pos_embeddings
         lowercase__  =	num_conv_pos_embedding_groups
         lowercase__  =	conv_pos_kernel_size
         lowercase__  =	len(self.conv_dim)
         lowercase__  =	num_hidden_layers
         lowercase__  =	intermediate_size
         lowercase__  =	hidden_act
         lowercase__  =	num_attention_heads
         lowercase__  =	hidden_dropout
         lowercase__  =	attention_dropout
         lowercase__  =	activation_dropout
         lowercase__  =	feat_proj_dropout
         lowercase__  =	final_dropout
         lowercase__  =	layerdrop
         lowercase__  =	layer_norm_eps
         lowercase__  =	initializer_range
         lowercase__  =	vocab_size
         lowercase__  =	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__  =	mask_time_prob
         lowercase__  =	mask_time_length
         lowercase__  =	mask_time_min_masks
         lowercase__  =	mask_feature_prob
         lowercase__  =	mask_feature_length
         lowercase__  =	mask_feature_min_masks

         # ctc loss
         lowercase__  =	ctc_loss_reduction
         lowercase__  =	ctc_zero_infinity

         # adapter
         lowercase__  =	add_adapter
         lowercase__  =	adapter_kernel_size
         lowercase__  =	adapter_stride
         lowercase__  =	num_adapter_layers
         lowercase__  =	output_hidden_size or hidden_size

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

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



   @property
   def       UpperCAmelCase		(    self	:      Tuple)						->					Any:




         """simple docstring"""

         return math.prod(self.conv_stride)





import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin



@require_jieba
class    UpperCAmelCase__(				lowerCamelCase  ,				unittest.TestCase						):

   '''simple docstring'''




   A     :	Optional[int]												=     CpmAntTokenizer
   A     :	Optional[int]												=     False


   def       UpperCAmelCase		(    self	:      List[str])						->					str:




         """simple docstring"""

         super().setUp()

         lowercase__  =	[
             '<d>',
             '</d>',
             '<s>',
             '</s>',
             '</_>',
             '<unk>',
             '<pad>',
             '</n>',
             '我',
             '是',
             'C',
             'P',
             'M',
             'A',
             'n',
             't',
         ]
         lowercase__  =	os.path.join(self.tmpdirname      ,					VOCAB_FILES_NAMES['vocab_file'])
         with open(self.vocab_file      ,					'w'      ,					encoding='utf-8') as vocab_writer:
               vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]))



   @tooslow
   def       UpperCAmelCase		(    self	:      str)						->					Optional[Any]:




         """simple docstring"""

         lowercase__  =	CpmAntTokenizer.from_pretrained('openbmb/cpm-ant-10b')
         lowercase__  =	'今天天气真好！'
         lowercase__  =	['今天', '天气', '真', '好', '！']
         lowercase__  =	tokenizer.tokenize(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase      ,					lowerCAmelCase)
         lowercase__  =	'今天天气真好！'
         lowercase__  =	[tokenizer.bos_token] + tokens

         lowercase__  =	[6, 98_02, 1_49_62, 20_82, 8_31, 2_44]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase)      ,					lowerCAmelCase)

         lowercase__  =	tokenizer.decode(lowerCAmelCase)
         self.assertEqual(lowerCAmelCase      ,					lowerCAmelCase)
