
import os
import unittest

from transformers import RealmTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.realm.tokenization_realm import RealmTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english





@require_tokenizers
class 						lowerCamelCase			(					__lowerCamelCase   ,		unittest.TestCase				):
	UpperCamelCase_     :				Dict								=  RealmTokenizer
	UpperCamelCase_     :				Optional[Any]								=  RealmTokenizerFast
	UpperCamelCase_     :				Dict								=  True
	UpperCamelCase_     :				int								=  True
	UpperCamelCase_     :				str								=  filter_non_english







	def    snake_case__    (    self			:Tuple )		->			Any:







				"""simple docstring"""






				super().setUp()

				SCREAMING_SNAKE_CASE    	=   [
				    '''[UNK]''',
				    '''[CLS]''',
				    '''[SEP]''',
				    '''[PAD]''',
				    '''[MASK]''',
				    '''want''',
				    '''##want''',
				    '''##ed''',
				    '''wa''',
				    '''un''',
				    '''runn''',
				    '''##ing''',
				    ''',''',
				    '''low''',
				    '''lowest''',
				]
				SCREAMING_SNAKE_CASE    	=   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] ) )







	def    snake_case__    (    self			:Union[str, Any]      ,    lowercase			:Optional[Any] )		->			Dict:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   '''UNwant\u00E9d,running'''
				SCREAMING_SNAKE_CASE    	=   '''unwanted, running'''
				return input_text, output_text







	def    snake_case__    (    self			:List[Any] )		->			str:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   self.tokenizer_class(self.vocab_file )

				SCREAMING_SNAKE_CASE    	=   tokenizer.tokenize('''UNwant\u00E9d,running''' )
				self.assertListEqual(lowercase      ,    ['''un''', '''##want''', '''##ed''', ''',''', '''runn''', '''##ing'''] )
				self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase )      ,    [9, 6, 7, 1_2, 1_0, 1_1] )







	def    snake_case__    (    self			:str )		->			int:







				"""simple docstring"""






				if not self.test_rust_tokenizer:
							return

				SCREAMING_SNAKE_CASE    	=   self.get_tokenizer()
				SCREAMING_SNAKE_CASE    	=   self.get_rust_tokenizer()

				SCREAMING_SNAKE_CASE    	=   '''UNwant\u00E9d,running'''

				SCREAMING_SNAKE_CASE    	=   tokenizer.tokenize(lowercase )
				SCREAMING_SNAKE_CASE    	=   rust_tokenizer.tokenize(lowercase )
				self.assertListEqual(lowercase      ,    lowercase )

				SCREAMING_SNAKE_CASE    	=   tokenizer.encode(lowercase      ,    add_special_tokens=lowercase )
				SCREAMING_SNAKE_CASE    	=   rust_tokenizer.encode(lowercase      ,    add_special_tokens=lowercase )
				self.assertListEqual(lowercase      ,    lowercase )

				SCREAMING_SNAKE_CASE    	=   self.get_rust_tokenizer()
				SCREAMING_SNAKE_CASE    	=   tokenizer.encode(lowercase )
				SCREAMING_SNAKE_CASE    	=   rust_tokenizer.encode(lowercase )
				self.assertListEqual(lowercase      ,    lowercase )

				# With lower casing
				SCREAMING_SNAKE_CASE    	=   self.get_tokenizer(do_lower_case=lowercase )
				SCREAMING_SNAKE_CASE    	=   self.get_rust_tokenizer(do_lower_case=lowercase )

				SCREAMING_SNAKE_CASE    	=   '''UNwant\u00E9d,running'''

				SCREAMING_SNAKE_CASE    	=   tokenizer.tokenize(lowercase )
				SCREAMING_SNAKE_CASE    	=   rust_tokenizer.tokenize(lowercase )
				self.assertListEqual(lowercase      ,    lowercase )

				SCREAMING_SNAKE_CASE    	=   tokenizer.encode(lowercase      ,    add_special_tokens=lowercase )
				SCREAMING_SNAKE_CASE    	=   rust_tokenizer.encode(lowercase      ,    add_special_tokens=lowercase )
				self.assertListEqual(lowercase      ,    lowercase )

				SCREAMING_SNAKE_CASE    	=   self.get_rust_tokenizer()
				SCREAMING_SNAKE_CASE    	=   tokenizer.encode(lowercase )
				SCREAMING_SNAKE_CASE    	=   rust_tokenizer.encode(lowercase )
				self.assertListEqual(lowercase      ,    lowercase )







	def    snake_case__    (    self			:Optional[int] )		->			str:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer()

				self.assertListEqual(tokenizer.tokenize('''ah\u535A\u63A8zz''' )      ,    ['''ah''', '''\u535A''', '''\u63A8''', '''zz'''] )







	def    snake_case__    (    self			:str )		->			Any:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  ''' )      ,    ['''hello''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
				self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' )      ,    ['''hello'''] )







	def    snake_case__    (    self			:Optional[int] )		->			Union[str, Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase      ,    strip_accents=lowercase )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' )      ,    ['''hällo''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
				self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' )      ,    ['''h\u00E9llo'''] )







	def    snake_case__    (    self			:Union[str, Any] )		->			int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase      ,    strip_accents=lowercase )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' )      ,    ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
				self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' )      ,    ['''hello'''] )







	def    snake_case__    (    self			:Union[str, Any] )		->			List[str]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' )      ,    ['''hallo''', '''!''', '''how''', '''are''', '''you''', '''?'''] )
				self.assertListEqual(tokenizer.tokenize('''H\u00E9llo''' )      ,    ['''hello'''] )







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







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU?  ''' )      ,    ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?'''] )







	def    snake_case__    (    self			:Union[str, Any] )		->			Optional[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase      ,    strip_accents=lowercase )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' )      ,    ['''HäLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?'''] )







	def    snake_case__    (    self			:Any )		->			List[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase      ,    strip_accents=lowercase )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHäLLo!how  \n Are yoU?  ''' )      ,    ['''HaLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?'''] )







	def    snake_case__    (    self			:List[str] )		->			Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   BasicTokenizer(do_lower_case=lowercase      ,    never_split=['''[UNK]'''] )

				self.assertListEqual(
				    tokenizer.tokenize(''' \tHeLLo!how  \n Are yoU? [UNK]''' )      ,    ['''HeLLo''', '''!''', '''how''', '''Are''', '''yoU''', '''?''', '''[UNK]'''] )







	def    snake_case__    (    self			:Optional[Any] )		->			List[Any]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   ['''[UNK]''', '''[CLS]''', '''[SEP]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''']

				SCREAMING_SNAKE_CASE    	=   {}
				for i, token in enumerate(lowercase ):
							SCREAMING_SNAKE_CASE    	=   i
				SCREAMING_SNAKE_CASE    	=   WordpieceTokenizer(vocab=lowercase      ,    unk_token='''[UNK]''' )

				self.assertListEqual(tokenizer.tokenize('''''' )      ,    [] )

				self.assertListEqual(tokenizer.tokenize('''unwanted running''' )      ,    ['''un''', '''##want''', '''##ed''', '''runn''', '''##ing'''] )

				self.assertListEqual(tokenizer.tokenize('''unwantedX running''' )      ,    ['''[UNK]''', '''runn''', '''##ing'''] )







	def    snake_case__    (    self			:Union[str, Any] )		->			Dict:







				"""simple docstring"""






				self.assertTrue(_is_whitespace(''' ''' ) )
				self.assertTrue(_is_whitespace('''\t''' ) )
				self.assertTrue(_is_whitespace('''\r''' ) )
				self.assertTrue(_is_whitespace('''\n''' ) )
				self.assertTrue(_is_whitespace('''\u00A0''' ) )

				self.assertFalse(_is_whitespace('''A''' ) )
				self.assertFalse(_is_whitespace('''-''' ) )







	def    snake_case__    (    self			:Any )		->			int:







				"""simple docstring"""






				self.assertTrue(_is_control('''\u0005''' ) )

				self.assertFalse(_is_control('''A''' ) )
				self.assertFalse(_is_control(''' ''' ) )
				self.assertFalse(_is_control('''\t''' ) )
				self.assertFalse(_is_control('''\r''' ) )







	def    snake_case__    (    self			:Optional[int] )		->			Dict:







				"""simple docstring"""






				self.assertTrue(_is_punctuation('''-''' ) )
				self.assertTrue(_is_punctuation('''$''' ) )
				self.assertTrue(_is_punctuation('''`''' ) )
				self.assertTrue(_is_punctuation('''.''' ) )

				self.assertFalse(_is_punctuation('''A''' ) )
				self.assertFalse(_is_punctuation(''' ''' ) )







	def    snake_case__    (    self			:int )		->			Any:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   self.get_tokenizer()

				# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
				self.assertListEqual([tokenizer.tokenize(lowercase ) for t in ['''Test''', '''\xad''', '''test''']]      ,    [['''[UNK]'''], [], ['''[UNK]''']] )

				if self.test_rust_tokenizer:
							SCREAMING_SNAKE_CASE    	=   self.get_rust_tokenizer()
							self.assertListEqual(
							    [rust_tokenizer.tokenize(lowercase ) for t in ['''Test''', '''\xad''', '''test''']]      ,    [['''[UNK]'''], [], ['''[UNK]''']] )







	@slow
	def    snake_case__    (    self			:Optional[Any] )		->			Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   self.tokenizer_class.from_pretrained('''bert-base-uncased''' )

				SCREAMING_SNAKE_CASE    	=   tokenizer.encode('''sequence builders'''      ,    add_special_tokens=lowercase )
				SCREAMING_SNAKE_CASE    	=   tokenizer.encode('''multi-sequence build'''      ,    add_special_tokens=lowercase )

				SCREAMING_SNAKE_CASE    	=   tokenizer.build_inputs_with_special_tokens(lowercase )
				SCREAMING_SNAKE_CASE    	=   tokenizer.build_inputs_with_special_tokens(lowercase      ,    lowercase )

				assert encoded_sentence == [1_0_1] + text + [1_0_2]
				assert encoded_pair == [1_0_1] + text + [1_0_2] + text_a + [1_0_2]







	def    snake_case__    (    self			:Any )		->			Optional[int]:







				"""simple docstring"""






				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
										SCREAMING_SNAKE_CASE    	=   self.rust_tokenizer_class.from_pretrained(lowercase      ,    **lowercase )

										SCREAMING_SNAKE_CASE    	=   f"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
										SCREAMING_SNAKE_CASE    	=   tokenizer_r.encode_plus(
										    lowercase      ,    return_attention_mask=lowercase      ,    return_token_type_ids=lowercase      ,    return_offsets_mapping=lowercase      ,    add_special_tokens=lowercase      ,    )

										SCREAMING_SNAKE_CASE    	=   tokenizer_r.do_lower_case if hasattr(lowercase      ,    '''do_lower_case''' ) else False
										SCREAMING_SNAKE_CASE    	=   (
										    [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), '''A'''),
										        ((1, 2), ''','''),
										        ((3, 5), '''na'''),
										        ((5, 6), '''##ï'''),
										        ((6, 8), '''##ve'''),
										        ((9, 1_5), tokenizer_r.mask_token),
										        ((1_6, 2_1), '''Allen'''),
										        ((2_1, 2_3), '''##NL'''),
										        ((2_3, 2_4), '''##P'''),
										        ((2_5, 3_3), '''sentence'''),
										        ((3_3, 3_4), '''.'''),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										    if not do_lower_case
										    else [
										        ((0, 0), tokenizer_r.cls_token),
										        ((0, 1), '''a'''),
										        ((1, 2), ''','''),
										        ((3, 8), '''naive'''),
										        ((9, 1_5), tokenizer_r.mask_token),
										        ((1_6, 2_1), '''allen'''),
										        ((2_1, 2_3), '''##nl'''),
										        ((2_3, 2_4), '''##p'''),
										        ((2_5, 3_3), '''sentence'''),
										        ((3_3, 3_4), '''.'''),
										        ((0, 0), tokenizer_r.sep_token),
										    ]
										)

										self.assertEqual(
										    [e[1] for e in expected_results]      ,    tokenizer_r.convert_ids_to_tokens(tokens['''input_ids'''] ) )
										self.assertEqual([e[0] for e in expected_results]      ,    tokens['''offset_mapping'''] )







	@slow
	def    snake_case__    (    self			:Any )		->			Optional[int]:







				"""simple docstring"""






				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
							with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})""" ):
										SCREAMING_SNAKE_CASE    	=   self.rust_tokenizer_class.from_pretrained(lowercase      ,    **lowercase )
										SCREAMING_SNAKE_CASE    	=   self.tokenizer_class.from_pretrained(lowercase      ,    **lowercase )
										SCREAMING_SNAKE_CASE    	=   [['''Hello world!''', '''Nice to meet you!'''], ['''The cute cat.''', '''The adorable dog.''']]

										SCREAMING_SNAKE_CASE    	=   tokenizer_r.batch_encode_candidates(lowercase      ,    max_length=1_0      ,    return_tensors='''np''' )
										SCREAMING_SNAKE_CASE    	=   tokenizer_p.batch_encode_candidates(lowercase      ,    max_length=1_0      ,    return_tensors='''np''' )

										SCREAMING_SNAKE_CASE    	=   (2, 2, 1_0)

										self.assertEqual(encoded_sentence_r['''input_ids'''].shape      ,    lowercase )
										self.assertEqual(encoded_sentence_r['''attention_mask'''].shape      ,    lowercase )
										self.assertEqual(encoded_sentence_r['''token_type_ids'''].shape      ,    lowercase )

										self.assertEqual(encoded_sentence_p['''input_ids'''].shape      ,    lowercase )
										self.assertEqual(encoded_sentence_p['''attention_mask'''].shape      ,    lowercase )
										self.assertEqual(encoded_sentence_p['''token_type_ids'''].shape      ,    lowercase )

import argparse
import os
from dataclasses import dataclass

import torch
import torchaudio
from tqdm import tqdm

from transformers import AutoConfig, AutoModelForCTC, AutoProcessor





class 						lowerCamelCase			:







	def __init__(    self			:Optional[int]      ,    lowercase			:Optional[Any]      ,    lowercase			:Optional[int]      ,    lowercase			:int )		->			Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   cuda
				SCREAMING_SNAKE_CASE    	=   AutoConfig.from_pretrained(lowercase )
				SCREAMING_SNAKE_CASE    	=   AutoModelForCTC.from_pretrained(lowercase )
				self.model.eval()
				if self.cuda:
							self.model.to(device='''cuda''' )
				SCREAMING_SNAKE_CASE    	=   AutoProcessor.from_pretrained(lowercase )
				SCREAMING_SNAKE_CASE    	=   torchaudio.transforms.Resample(lowercase      ,    1_6_0_0_0 )
				SCREAMING_SNAKE_CASE    	=   0
				SCREAMING_SNAKE_CASE    	=   list(self.processor.tokenizer.get_vocab().keys() )
				for i in range(len(lowercase ) ):
							if vocab[i] == "[PAD]" or vocab[i] == "<pad>":
										SCREAMING_SNAKE_CASE    	=   i
				print('''Blank Token id [PAD]/<pad>'''      ,    lowercase )
				SCREAMING_SNAKE_CASE    	=   blank_id







	def    snake_case__    (    self			:Any      ,    lowercase			:int )		->			Optional[int]:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE	,       SCREAMING_SNAKE_CASE    	=   torchaudio.load(lowercase )
				SCREAMING_SNAKE_CASE    	=   self.resampler(lowercase ).squeeze().numpy()
				return speech







	def    snake_case__    (    self			:Union[str, Any]      ,    lowercase			:Optional[Any] )		->			int:







				"""simple docstring"""






				SCREAMING_SNAKE_CASE    	=   self.blank_id
				SCREAMING_SNAKE_CASE    	=   '''|'''.join(item['''sent'''].split(''' ''' ) )
				if not os.path.isfile(item['''wav_path'''] ):
							print(item['''wav_path''']      ,    '''not found in wavs directory''' )

				SCREAMING_SNAKE_CASE    	=   self.speech_file_to_array_fn(item['''wav_path'''] )
				SCREAMING_SNAKE_CASE    	=   self.processor(lowercase      ,    sampling_rate=1_6_0_0_0      ,    return_tensors='''pt'''      ,    padding=lowercase )
				if self.cuda:
							SCREAMING_SNAKE_CASE    	=   inputs.to(device='''cuda''' )

				with torch.no_grad():
							SCREAMING_SNAKE_CASE    	=   self.model(inputs.input_values ).logits

				# get the emission probability at frame level
				SCREAMING_SNAKE_CASE    	=   torch.log_softmax(lowercase      ,    dim=-1 )
				SCREAMING_SNAKE_CASE    	=   emissions[0].cpu().detach()

				# get labels from vocab
				SCREAMING_SNAKE_CASE    	=   ([''''''] + list(self.processor.tokenizer.get_vocab().keys() ))[
				    :-1
				]  # logits don't align with the tokenizer's vocab

				SCREAMING_SNAKE_CASE    	=   {c: i for i, c in enumerate(lowercase )}
				SCREAMING_SNAKE_CASE    	=   []
				for c in transcript:
							if c in dictionary:
										tokens.append(dictionary[c] )

				def get_trellis(lowercase			:List[Any]      ,    lowercase			:Any      ,    lowercase			:int=0 ):
							SCREAMING_SNAKE_CASE    	=   emission.size(0 )
							SCREAMING_SNAKE_CASE    	=   len(lowercase )

							# Trellis has extra diemsions for both time axis and tokens.
							# The extra dim for tokens represents <SoS> (start-of-sentence)
							# The extra dim for time axis is for simplification of the code.
							SCREAMING_SNAKE_CASE    	=   torch.full((num_frames + 1, num_tokens + 1)      ,    -float('''inf''' ) )
							SCREAMING_SNAKE_CASE    	=   0
							for t in range(lowercase ):
										SCREAMING_SNAKE_CASE    	=   torch.maximum(
										    # Score for staying at the same token
										    trellis[t, 1:] + emission[t, blank_id]      ,    trellis[t, :-1] + emission[t, tokens]      ,    )
							return trellis

				SCREAMING_SNAKE_CASE    	=   get_trellis(lowercase      ,    lowercase      ,    lowercase )





				@dataclass
				class 						lowerCamelCase			:
					UpperCamelCase_     :				int
					UpperCamelCase_     :				int
					UpperCamelCase_     :				float

				def backtrack(lowercase			:Optional[int]      ,    lowercase			:List[str]      ,    lowercase			:Union[str, Any]      ,    lowercase			:Optional[Any]=0 ):
							SCREAMING_SNAKE_CASE    	=   trellis.size(1 ) - 1
							SCREAMING_SNAKE_CASE    	=   torch.argmax(trellis[:, j] ).item()

							SCREAMING_SNAKE_CASE    	=   []
							for t in range(lowercase      ,    0      ,    -1 ):
										# 1. Figure out if the current position was stay or change
										# Note (again):
										# `emission[J-1]` is the emission at time frame `J` of trellis dimension.
										# Score for token staying the same from time frame J-1 to T.
										SCREAMING_SNAKE_CASE    	=   trellis[t - 1, j] + emission[t - 1, blank_id]
										# Score for token changing from C-1 at T-1 to J at T.
										SCREAMING_SNAKE_CASE    	=   trellis[t - 1, j - 1] + emission[t - 1, tokens[j - 1]]

										# 2. Store the path with frame-wise probability.
										SCREAMING_SNAKE_CASE    	=   emission[t - 1, tokens[j - 1] if changed > stayed else 0].exp().item()
										# Return token index and time index in non-trellis coordinate.
										path.append(Point(j - 1      ,    t - 1      ,    lowercase ) )

										# 3. Update the token
										if changed > stayed:
													j -= 1
													if j == 0:
																break
							else:
										raise ValueError('''Failed to align''' )
							return path[::-1]

				SCREAMING_SNAKE_CASE    	=   backtrack(lowercase      ,    lowercase      ,    lowercase      ,    lowercase )





				@dataclass
				class 						lowerCamelCase			:
					UpperCamelCase_     :				str
					UpperCamelCase_     :				int
					UpperCamelCase_     :				int
					UpperCamelCase_     :				float







					def __repr__(    self			:Optional[Any] )		->			str:







								"""simple docstring"""






								return f"""{self.label}\t{self.score:4.2f}\t{self.start*2_0:5d}\t{self.end*2_0:5d}"""







					@property
					def    snake_case__    (    self			:List[str] )		->			Any:







								"""simple docstring"""






								return self.end - self.start

				def merge_repeats(lowercase			:List[str] ):
							SCREAMING_SNAKE_CASE	,       SCREAMING_SNAKE_CASE    	=   0, 0
							SCREAMING_SNAKE_CASE    	=   []
							while ia < len(lowercase ):
										while ia < len(lowercase ) and path[ia].token_index == path[ia].token_index:
													ia += 1
										SCREAMING_SNAKE_CASE    	=   sum(path[k].score for k in range(lowercase      ,    lowercase ) ) / (ia - ia)
										segments.append(
										    Segment(
										        transcript[path[ia].token_index]      ,    path[ia].time_index      ,    path[ia - 1].time_index + 1      ,    lowercase      ,    ) )
										SCREAMING_SNAKE_CASE    	=   ia
							return segments

				SCREAMING_SNAKE_CASE    	=   merge_repeats(lowercase )
				with open(item['''out_path''']      ,    '''w''' ) as out_align:
							for seg in segments:
										out_align.write(str(lowercase ) + '''\n''' )







	def    snake_case__    (    self			:List[Any]      ,    lowercase			:Dict      ,    lowercase			:Tuple      ,    lowercase			:str )		->			Dict:







				"""simple docstring"""






				if not os.path.exists(lowercase ):
							os.makedirs(lowercase )

				# load text file
				SCREAMING_SNAKE_CASE    	=   open(lowercase      ,    encoding='''utf8''' ).readlines()

				SCREAMING_SNAKE_CASE    	=   []
				for line in lines:
							if len(line.strip().split('''\t''' ) ) != 2:
										print('''Script must be in format: 00001  this is my sentence''' )
										exit()

							SCREAMING_SNAKE_CASE	,       SCREAMING_SNAKE_CASE    	=   line.strip().split('''\t''' )
							SCREAMING_SNAKE_CASE    	=   os.path.join(lowercase      ,    wav_name + '''.wav''' )
							SCREAMING_SNAKE_CASE    	=   os.path.join(lowercase      ,    wav_name + '''.txt''' )

							items.append({'''sent''': sentence, '''wav_path''': wav_path, '''out_path''': out_path} )
				print('''Number of samples found in script file'''      ,    len(lowercase ) )

				for item in tqdm(lowercase ):
							self.align_single_sample(lowercase )



def       a			(   )    ->Optional[int]:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE    	=   argparse.ArgumentParser()

			parser.add_argument(
			    '''--model_name'''		,	type=a		,	default='''arijitx/wav2vec2-xls-r-300m-bengali'''		,	help='''wav2vec model name'''  )
			parser.add_argument('''--wav_dir'''		,	type=a		,	default='''./wavs'''		,	help='''directory containing wavs'''  )
			parser.add_argument('''--text_file'''		,	type=a		,	default='''script.txt'''		,	help='''file containing text'''  )
			parser.add_argument('''--input_wavs_sr'''		,	type=a		,	default=1_6000		,	help='''sampling rate of input audios'''  )
			parser.add_argument(
			    '''--output_dir'''		,	type=a		,	default='''./out_alignment'''		,	help='''output directory containing the alignment files'''  )
			parser.add_argument('''--cuda'''		,	action='''store_true'''  )

			SCREAMING_SNAKE_CASE    	=   parser.parse_args()

			SCREAMING_SNAKE_CASE    	=   WavaVecaAligner(args.model_name		,	args.input_wavs_sr		,	args.cuda  )
			aligner.align_data(args.wav_dir		,	args.text_file		,	args.output_dir  )


if __name__ == "__main__":
							main()