






"""simple docstring"""



_lowerCAmelCase  :  Dict   =			{hex(i)[2:]: i for i in range(16)}  # Use [:2] to strip off the leading '0x'


def   SCREAMING_SNAKE_CASE__					(     snake_case					:   str							)->		int:






					'''simple docstring'''



					UpperCAmelCase__	:						Union[str, Any]       =       hex_string.strip().lower()
					if not hex_string:
										raise ValueError("Empty string was passed to the function"							)
					UpperCAmelCase__	:						str       =       hex_string[0] == "-"
					if is_negative:
										UpperCAmelCase__	:						List[Any]       =       hex_string[1:]
					if not all(char in hex_table for char in hex_string							):
										raise ValueError("Non-hexadecimal value was passed to the function"							)
					UpperCAmelCase__	:						str       =       0
					for char in hex_string:
										UpperCAmelCase__	:						List[Any]       =       16 * decimal_number + hex_table[char]
					return -decimal_number if is_negative else decimal_number


if __name__ == "__main__":
	from doctest import testmod

	testmod()










"""simple docstring"""



import json
import os
import shutil
import tempfile
import unittest

from transformers.models.wavaveca import WavaVecaCTCTokenizer, WavaVecaFeatureExtractor, WavaVecaProcessor
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.utils import FEATURE_EXTRACTOR_NAME

from .test_feature_extraction_wavaveca import floats_list




class  lowerCAmelCase__ (						unittest.TestCase      ):
   def 			__a       (		self			:  str       ):


        '''simple docstring'''
        UpperCAmelCase__	:						Tuple       =       "<pad> <s> </s> <unk> | E T A O N I H S R D L U M W C F G Y P B V K ' X J Q Z".split(" "       )
        UpperCAmelCase__	:						Dict       =       dict(zip(snake_case__       , range(len(snake_case__       )       )       )       )

        UpperCAmelCase__	:						Dict       =       {
            "pad_token": "<pad>",
            "unk_token": "<unk>",
            "bos_token": "<s>",
            "eos_token": "</s>",
        }
        UpperCAmelCase__	:						str       =       {
            "feature_size": 1,
            "padding_value": 0.0,
            "sampling_rate": 1_6_0_0_0,
            "return_attention_mask": False,
            "do_normalize": True,
        }

        UpperCAmelCase__	:						List[str]       =       tempfile.mkdtemp()
        UpperCAmelCase__	:						int       =       os.path.join(self.tmpdirname       , VOCAB_FILES_NAMES["vocab_file"]       )
        UpperCAmelCase__	:						List[str]       =       os.path.join(self.tmpdirname       , snake_case__       )
        with open(self.vocab_file       , "w"       , encoding="utf-8"       ) as fp:
             fp.write(json.dumps(snake_case__       ) + "\n"       )

        with open(self.feature_extraction_file       , "w"       , encoding="utf-8"       ) as fp:
             fp.write(json.dumps(snake_case__       ) + "\n"       )
   def 			__a       (		self			:  List[str]       , **snake_case__			:  Optional[int]       ):


        '''simple docstring'''
        UpperCAmelCase__	:						Dict       =       self.add_kwargs_tokens_map.copy()
        kwargs.update(snake_case__       )
        return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname       , **snake_case__       )
   def 			__a       (		self			:  List[Any]       , **snake_case__			:  str       ):


        '''simple docstring'''
        return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname       , **snake_case__       )
   def 			__a       (		self			:  List[str]       ):


        '''simple docstring'''
        shutil.rmtree(self.tmpdirname       )
   def 			__a       (		self			:  int       ):


        '''simple docstring'''
        UpperCAmelCase__	:						int       =       self.get_tokenizer()
        UpperCAmelCase__	:						List[Any]       =       self.get_feature_extractor()

        UpperCAmelCase__	:						Optional[Any]       =       WavaVecaProcessor(tokenizer=snake_case__       , feature_extractor=snake_case__       )

        processor.save_pretrained(self.tmpdirname       )
        UpperCAmelCase__	:						List[Any]       =       WavaVecaProcessor.from_pretrained(self.tmpdirname       )

        self.assertEqual(processor.tokenizer.get_vocab()       , tokenizer.get_vocab()       )
        self.assertIsInstance(processor.tokenizer       , snake_case__       )

        self.assertEqual(processor.feature_extractor.to_json_string()       , feature_extractor.to_json_string()       )
        self.assertIsInstance(processor.feature_extractor       , snake_case__       )
   def 			__a       (		self			:  Dict       ):


        '''simple docstring'''
        UpperCAmelCase__	:						List[Any]       =       WavaVecaProcessor(tokenizer=self.get_tokenizer()       , feature_extractor=self.get_feature_extractor()       )
        processor.save_pretrained(self.tmpdirname       )

        UpperCAmelCase__	:						str       =       self.get_tokenizer(bos_token="(BOS)"       , eos_token="(EOS)"       )
        UpperCAmelCase__	:						Optional[Any]       =       self.get_feature_extractor(do_normalize=snake_case__       , padding_value=1.0       )

        UpperCAmelCase__	:						Optional[Any]       =       WavaVecaProcessor.from_pretrained(
            self.tmpdirname       , bos_token="(BOS)"       , eos_token="(EOS)"       , do_normalize=snake_case__       , padding_value=1.0       )

        self.assertEqual(processor.tokenizer.get_vocab()       , tokenizer_add_kwargs.get_vocab()       )
        self.assertIsInstance(processor.tokenizer       , snake_case__       )

        self.assertEqual(processor.feature_extractor.to_json_string()       , feature_extractor_add_kwargs.to_json_string()       )
        self.assertIsInstance(processor.feature_extractor       , snake_case__       )
   def 			__a       (		self			:  Tuple       ):


        '''simple docstring'''
        UpperCAmelCase__	:						List[str]       =       self.get_feature_extractor()
        UpperCAmelCase__	:						str       =       self.get_tokenizer()

        UpperCAmelCase__	:						str       =       WavaVecaProcessor(tokenizer=snake_case__       , feature_extractor=snake_case__       )

        UpperCAmelCase__	:						Optional[int]       =       floats_list((3, 1_0_0_0)       )

        UpperCAmelCase__	:						int       =       feature_extractor(snake_case__       , return_tensors="np"       )
        UpperCAmelCase__	:						Optional[Any]       =       processor(snake_case__       , return_tensors="np"       )

        for key in input_feat_extract.keys():
             self.assertAlmostEqual(input_feat_extract[key].sum()       , input_processor[key].sum()       , delta=1e-2       )
   def 			__a       (		self			:  Optional[Any]       ):


        '''simple docstring'''
        UpperCAmelCase__	:						Dict       =       self.get_feature_extractor()
        UpperCAmelCase__	:						int       =       self.get_tokenizer()

        UpperCAmelCase__	:						Optional[int]       =       WavaVecaProcessor(tokenizer=snake_case__       , feature_extractor=snake_case__       )

        UpperCAmelCase__	:						Any       =       "This is a test string"

        UpperCAmelCase__	:						Optional[int]       =       processor(text=snake_case__       )

        UpperCAmelCase__	:						Optional[int]       =       tokenizer(snake_case__       )

        for key in encoded_tok.keys():
             self.assertListEqual(encoded_tok[key]       , encoded_processor[key]       )
   def 			__a       (		self			:  Optional[int]       ):


        '''simple docstring'''
        UpperCAmelCase__	:						str       =       self.get_feature_extractor()
        UpperCAmelCase__	:						str       =       self.get_tokenizer()

        UpperCAmelCase__	:						Optional[int]       =       WavaVecaProcessor(tokenizer=snake_case__       , feature_extractor=snake_case__       )

        UpperCAmelCase__	:						Optional[int]       =       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        UpperCAmelCase__	:						Dict       =       processor.batch_decode(snake_case__       )
        UpperCAmelCase__	:						Tuple       =       tokenizer.batch_decode(snake_case__       )

        self.assertListEqual(snake_case__       , snake_case__       )




   def 			__a       (		self			:  int       ):


        '''simple docstring'''
        UpperCAmelCase__	:						Dict       =       self.get_feature_extractor()
        UpperCAmelCase__	:						Any       =       self.get_tokenizer()

        UpperCAmelCase__	:						Dict       =       WavaVecaProcessor(tokenizer=snake_case__       , feature_extractor=snake_case__       )

        self.assertListEqual(
            processor.model_input_names       , feature_extractor.model_input_names       , msg="`processor` and `feature_extractor` model input names do not match"       , )


