'''simple docstring'''

import math
from typing import Optional

import numpy as np

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


__a:			int	       =       logging.get_logger(__name__)

__a:			List[str]	       =       {
    """facebook/encodec_24khz""": """https://huggingface.co/facebook/encodec_24khz/resolve/main/config.json""",
    """facebook/encodec_48khz""": """https://huggingface.co/facebook/encodec_48khz/resolve/main/config.json""",
}



class       UpperCAmelCase  (						a__ ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   "encodec"

       def __init__(						self     ,       __lowerCAmelCase=[1.5, 3.0, 6.0, 1_2.0, 2_4.0]     ,       __lowerCAmelCase=24000     ,       __lowerCAmelCase=1     ,       __lowerCAmelCase=False     ,       __lowerCAmelCase=None     ,       __lowerCAmelCase=None     ,       __lowerCAmelCase=128     ,       __lowerCAmelCase=32     ,       __lowerCAmelCase=1     ,       __lowerCAmelCase=[8, 5, 4, 2]     ,       __lowerCAmelCase="weight_norm"     ,       __lowerCAmelCase=7     ,       __lowerCAmelCase=7     ,       __lowerCAmelCase=3     ,       __lowerCAmelCase=2     ,       __lowerCAmelCase=True     ,       __lowerCAmelCase="reflect"     ,       __lowerCAmelCase=2     ,       __lowerCAmelCase=2     ,       __lowerCAmelCase=1.0     ,       __lowerCAmelCase=1024     ,       __lowerCAmelCase=None     ,       __lowerCAmelCase=True     ,       **__lowerCAmelCase     ,       )  ->  Optional[int]:
        lowercase__    :   str						= target_bandwidths
        lowercase__    :   str						= sampling_rate
        lowercase__    :   Optional[Any]						= audio_channels
        lowercase__    :   Tuple						= normalize
        lowercase__    :   int						= chunk_length_s
        lowercase__    :   str						= overlap
        lowercase__    :   Tuple						= hidden_size
        lowercase__    :   Dict						= num_filters
        lowercase__    :   Tuple						= num_residual_layers
        lowercase__    :   Union[str, Any]						= upsampling_ratios
        lowercase__    :   List[str]						= norm_type
        lowercase__    :   Dict						= kernel_size
        lowercase__    :   Tuple						= last_kernel_size
        lowercase__    :   List[Any]						= residual_kernel_size
        lowercase__    :   Tuple						= dilation_growth_rate
        lowercase__    :   Any						= use_causal_conv
        lowercase__    :   Optional[int]						= pad_mode
        lowercase__    :   List[Any]						= compress
        lowercase__    :   Any						= num_lstm_layers
        lowercase__    :   str						= trim_right_ratio
        lowercase__    :   Union[str, Any]						= codebook_size
        lowercase__    :   Any						= codebook_dim if codebook_dim is not None else hidden_size
        lowercase__    :   str						= use_conv_shortcut

        if self.norm_type not in ["weight_norm", "time_group_norm"]:
         raise ValueError(
             F"""self.norm_type must be one of `\"weight_norm\"`, `\"time_group_norm\"`), got {self.norm_type}"""			)

        super().__init__(**__lowerCAmelCase			)

       @property
       def _lowerCAmelCase(						self			)  ->  Optional[int]:
        if self.chunk_length_s is None:
         return None
        else:
         return int(self.chunk_length_s * self.sampling_rate			)

       @property
       def _lowerCAmelCase(						self			)  ->  Optional[int]:
        if self.chunk_length_s is None or self.overlap is None:
         return None
        else:
         return max(1     ,       int((1.0 - self.overlap) * self.chunk_length			)			)

       @property
       def _lowerCAmelCase(						self			)  ->  int:
        lowercase__    :   Optional[Any]						= np.prod(self.upsampling_ratios			)
        return math.ceil(self.sampling_rate / hop_length			)


       @property
       def _lowerCAmelCase(						self			)  ->  int:
        return int(1000 * self.target_bandwidths[-1] // (self.frame_rate * 10)			)


'''simple docstring'''

import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin



@require_tokenizers
class       UpperCAmelCase  (						a__   ,						unittest.TestCase ):





       '''simple docstring'''



       SCREAMING_SNAKE_CASE 		=   OpenAIGPTTokenizer
       SCREAMING_SNAKE_CASE 		=   OpenAIGPTTokenizerFast
       SCREAMING_SNAKE_CASE 		=   True
       SCREAMING_SNAKE_CASE 		=   False

       def _lowerCAmelCase(						self			)  ->  Optional[int]:
        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        lowercase__    :   Optional[Any]						= [
            '''l''',
            '''o''',
            '''w''',
            '''e''',
            '''r''',
            '''s''',
            '''t''',
            '''i''',
            '''d''',
            '''n''',
            '''w</w>''',
            '''r</w>''',
            '''t</w>''',
            '''lo''',
            '''low''',
            '''er</w>''',
            '''low</w>''',
            '''lowest</w>''',
            '''newer</w>''',
            '''wider</w>''',
            '''<unk>''',
        ]
        lowercase__    :   Optional[int]						= dict(zip(__lowerCAmelCase     ,       range(len(__lowerCAmelCase			)			)			)			)
        lowercase__    :   Union[str, Any]						= ['''#version: 0.2''', '''l o''', '''lo w''', '''e r</w>''', '''''']

        lowercase__    :   Optional[int]						= os.path.join(self.tmpdirname     ,       VOCAB_FILES_NAMES['''vocab_file''']			)
        lowercase__    :   Optional[int]						= os.path.join(self.tmpdirname     ,       VOCAB_FILES_NAMES['''merges_file''']			)
        with open(self.vocab_file     ,       '''w'''			) as fp:
         fp.write(json.dumps(__lowerCAmelCase			)			)
        with open(self.merges_file     ,       '''w'''			) as fp:
         fp.write('''\n'''.join(__lowerCAmelCase			)			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase			)  ->  Dict:
        return "lower newer", "lower newer"

       def _lowerCAmelCase(						self			)  ->  List[Any]:
        lowercase__    :   int						= OpenAIGPTTokenizer(self.vocab_file     ,       self.merges_file			)

        lowercase__    :   List[Any]						= '''lower'''
        lowercase__    :   Any						= ['''low''', '''er</w>''']
        lowercase__    :   Union[str, Any]						= tokenizer.tokenize(__lowerCAmelCase			)
        self.assertListEqual(__lowerCAmelCase     ,       __lowerCAmelCase			)

        lowercase__    :   Tuple						= tokens + ['''<unk>''']
        lowercase__    :   Optional[Any]						= [14, 15, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCAmelCase			)     ,       __lowerCAmelCase			)

       def _lowerCAmelCase(						self     ,       __lowerCAmelCase=15			)  ->  Optional[int]:
        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
         with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""			):
          lowercase__    :   List[str]						= self.rust_tokenizer_class.from_pretrained(__lowerCAmelCase     ,       **__lowerCAmelCase			)

          # Simple input
          lowercase__    :   List[str]						= '''This is a simple input'''
          lowercase__    :   Any						= ['''This is a simple input 1''', '''This is a simple input 2''']
          lowercase__    :   str						= ('''This is a simple input''', '''This is a pair''')
          lowercase__    :   str						= [
              ('''This is a simple input 1''', '''This is a simple input 2'''),
              ('''This is a simple pair 1''', '''This is a simple pair 2'''),
          ]

          # Simple input tests
          self.assertRaises(__lowerCAmelCase     ,       tokenizer_r.encode     ,       __lowerCAmelCase     ,       max_length=__lowerCAmelCase     ,       padding='''max_length'''			)

          # Simple input
          self.assertRaises(__lowerCAmelCase     ,       tokenizer_r.encode_plus     ,       __lowerCAmelCase     ,       max_length=__lowerCAmelCase     ,       padding='''max_length'''			)

          # Simple input
          self.assertRaises(
              __lowerCAmelCase     ,       tokenizer_r.batch_encode_plus     ,       __lowerCAmelCase     ,       max_length=__lowerCAmelCase     ,       padding='''max_length'''     ,       )

          # Pair input
          self.assertRaises(__lowerCAmelCase     ,       tokenizer_r.encode     ,       __lowerCAmelCase     ,       max_length=__lowerCAmelCase     ,       padding='''max_length'''			)

          # Pair input
          self.assertRaises(__lowerCAmelCase     ,       tokenizer_r.encode_plus     ,       __lowerCAmelCase     ,       max_length=__lowerCAmelCase     ,       padding='''max_length'''			)

          # Pair input
          self.assertRaises(
              __lowerCAmelCase     ,       tokenizer_r.batch_encode_plus     ,       __lowerCAmelCase     ,       max_length=__lowerCAmelCase     ,       padding='''max_length'''     ,       )


       def _lowerCAmelCase(						self			)  ->  Tuple:
        pass



@require_ftfy
@require_spacy
@require_tokenizers
class       UpperCAmelCase  (						a__ ):





       '''simple docstring'''



       pass

