

import math





class 			__lowerCAmelCase					:




  def __init__(    self							,       lowerCAmelCase )  ->			Optional[Any]:
        '''simple docstring'''






        _lowercase     	=len(lowerCAmelCase )
        _lowercase     	=[0] * (
            4 * self.N
        )  # approximate the overall size of segment tree with array N
        self.build(1							,       0							,       self.N - 1 )




  def   A__					(    self							,       lowerCAmelCase )  ->			List[str]:
        '''simple docstring'''






        return idx * 2




  def   A__					(    self							,       lowerCAmelCase )  ->			Optional[int]:
        '''simple docstring'''






        return idx * 2 + 1




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )  ->			Any:  # noqa: E741
        '''simple docstring'''






        if l == r:
              _lowercase     	=A[l]
        else:
              _lowercase     	=(l + r) // 2
              self.build(self.left(lowerCAmelCase )							,       lowerCAmelCase							,       lowerCAmelCase )
              self.build(self.right(lowerCAmelCase )							,       mid + 1							,       lowerCAmelCase )
              _lowercase     	=max(self.st[self.left(lowerCAmelCase )]							,       self.st[self.right(lowerCAmelCase )] )




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )  ->			Union[str, Any]:
        '''simple docstring'''






        return self.update_recursive(1							,       0							,       self.N - 1							,       a - 1							,       b - 1							,       lowerCAmelCase )




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )  ->			str:  # noqa: E741
        '''simple docstring'''






        if r < a or l > b:
              return True
        if l == r:
              _lowercase     	=val
              return True
        _lowercase     	=(l + r) // 2
        self.update_recursive(self.left(lowerCAmelCase )							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )
        self.update_recursive(self.right(lowerCAmelCase )							,       mid + 1							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )
        _lowercase     	=max(self.st[self.left(lowerCAmelCase )]							,       self.st[self.right(lowerCAmelCase )] )
        return True




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase )  ->			List[str]:
        '''simple docstring'''






        return self.query_recursive(1							,       0							,       self.N - 1							,       a - 1							,       b - 1 )




  def   A__					(    self							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )  ->			List[Any]:  # noqa: E741
        '''simple docstring'''






        if r < a or l > b:
              return -math.inf
        if l >= a and r <= b:
              return self.st[idx]
        _lowercase     	=(l + r) // 2
        _lowercase     	=self.query_recursive(self.left(lowerCAmelCase )							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )
        _lowercase     	=self.query_recursive(self.right(lowerCAmelCase )							,       mid + 1							,       lowerCAmelCase							,       lowerCAmelCase							,       lowerCAmelCase )
        return max(lowerCAmelCase							,       lowerCAmelCase )




  def   A__					(    self )  ->			int:
        '''simple docstring'''






        _lowercase     	=[]
        for i in range(1							,       N + 1 ):
              show_list += [self.query(lowerCAmelCase							,       lowerCAmelCase )]
        print(lowerCAmelCase )


if __name__ == "__main__":
  lowercase_     =       [1, 2, -4, 7, 3, -5, 6, 1_1, -2_0, 9, 1_4, 1_5, 5, 2, -8]
  lowercase_     =       1_5
  lowercase_     =       SegmentTree(A)
  print(segt.query(4, 6))
  print(segt.query(7, 1_1))
  print(segt.query(7, 1_2))
  segt.update(1, 3, 1_1_1)
  print(segt.query(1, 1_5))
  segt.update(7, 8, 2_3_5)
  segt.show_data()





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 )  ->			Tuple:
        '''simple docstring'''






        _lowercase     	='<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(' ' )
        _lowercase     	=dict(zip(lowerCAmelCase							,       range(len(lowerCAmelCase ) ) ) )

        _lowercase     	={
            'pad_token': '<pad>',
            'unk_token': '<unk>',
            'bos_token': '<s>',
            'eos_token': '</s>',
        }
        _lowercase     	={
            'feature_size': 1,
            'padding_value': 0.0,
            'sampling_rate': 16_000,
            'return_attention_mask': False,
            'do_normalize': True,
        }

        _lowercase     	=tempfile.mkdtemp()
        _lowercase     	=os.path.join(self.tmpdirname							,       VOCAB_FILES_NAMES['vocab_file'] )
        _lowercase     	=os.path.join(self.tmpdirname							,       lowerCAmelCase )
        with open(self.vocab_file							,       'w'							,       encoding='utf-8' ) as fp:
              fp.write(json.dumps(lowerCAmelCase ) + '\n' )

        with open(self.feature_extraction_file							,       'w'							,       encoding='utf-8' ) as fp:
              fp.write(json.dumps(lowerCAmelCase ) + '\n' )




  def   A__					(    self							,       **lowerCAmelCase )  ->			Optional[Any]:
        '''simple docstring'''






        _lowercase     	=self.add_kwargs_tokens_map.copy()
        kwargs.update(lowerCAmelCase )
        return WavaVecaCTCTokenizer.from_pretrained(self.tmpdirname							,       **lowerCAmelCase )




  def   A__					(    self							,       **lowerCAmelCase )  ->			List[str]:
        '''simple docstring'''






        return WavaVecaFeatureExtractor.from_pretrained(self.tmpdirname							,       **lowerCAmelCase )




  def   A__					(    self )  ->			Union[str, Any]:
        '''simple docstring'''






        shutil.rmtree(self.tmpdirname )




  def   A__					(    self )  ->			Optional[int]:
        '''simple docstring'''






        _lowercase     	=self.get_tokenizer()
        _lowercase     	=self.get_feature_extractor()

        _lowercase     	=WavaVecaProcessor(tokenizer=lowerCAmelCase							,       feature_extractor=lowerCAmelCase )

        processor.save_pretrained(self.tmpdirname )
        _lowercase     	=WavaVecaProcessor.from_pretrained(self.tmpdirname )

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

        self.assertEqual(processor.feature_extractor.to_json_string()							,       feature_extractor.to_json_string() )
        self.assertIsInstance(processor.feature_extractor							,       lowerCAmelCase )




  def   A__					(    self )  ->			str:
        '''simple docstring'''






        _lowercase     	=WavaVecaProcessor(tokenizer=self.get_tokenizer()							,       feature_extractor=self.get_feature_extractor() )
        processor.save_pretrained(self.tmpdirname )

        _lowercase     	=self.get_tokenizer(bos_token='(BOS)'							,       eos_token='(EOS)' )
        _lowercase     	=self.get_feature_extractor(do_normalize=lowerCAmelCase							,       padding_value=1.0 )

        _lowercase     	=WavaVecaProcessor.from_pretrained(
            self.tmpdirname							,       bos_token='(BOS)'							,       eos_token='(EOS)'							,       do_normalize=lowerCAmelCase							,       padding_value=1.0 )

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

        self.assertEqual(processor.feature_extractor.to_json_string()							,       feature_extractor_add_kwargs.to_json_string() )
        self.assertIsInstance(processor.feature_extractor							,       lowerCAmelCase )




  def   A__					(    self )  ->			List[Any]:
        '''simple docstring'''






        _lowercase     	=self.get_feature_extractor()
        _lowercase     	=self.get_tokenizer()

        _lowercase     	=WavaVecaProcessor(tokenizer=lowerCAmelCase							,       feature_extractor=lowerCAmelCase )

        _lowercase     	=floats_list((3, 1_000) )

        _lowercase     	=feature_extractor(lowerCAmelCase							,       return_tensors='np' )
        _lowercase     	=processor(lowerCAmelCase							,       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 )  ->			int:
        '''simple docstring'''






        _lowercase     	=self.get_feature_extractor()
        _lowercase     	=self.get_tokenizer()

        _lowercase     	=WavaVecaProcessor(tokenizer=lowerCAmelCase							,       feature_extractor=lowerCAmelCase )

        _lowercase     	='This is a test string'

        _lowercase     	=processor(text=lowerCAmelCase )

        _lowercase     	=tokenizer(lowerCAmelCase )

        for key in encoded_tok.keys():
              self.assertListEqual(encoded_tok[key]							,       encoded_processor[key] )




  def   A__					(    self )  ->			str:
        '''simple docstring'''






        _lowercase     	=self.get_feature_extractor()
        _lowercase     	=self.get_tokenizer()

        _lowercase     	=WavaVecaProcessor(tokenizer=lowerCAmelCase							,       feature_extractor=lowerCAmelCase )

        _lowercase     	=[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

        _lowercase     	=processor.batch_decode(lowerCAmelCase )
        _lowercase     	=tokenizer.batch_decode(lowerCAmelCase )

        self.assertListEqual(lowerCAmelCase							,       lowerCAmelCase )




  def   A__					(    self )  ->			str:
        '''simple docstring'''






        _lowercase     	=self.get_feature_extractor()
        _lowercase     	=self.get_tokenizer()

        _lowercase     	=WavaVecaProcessor(tokenizer=lowerCAmelCase							,       feature_extractor=lowerCAmelCase )

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


