






import math
import os
import sys






def 				lowerCamelCase__				(_UpperCAmelCase):
			SCREAMING_SNAKE_CASE						= ''
			try:
						with open(_UpperCAmelCase							,       'rb') as binary_file:
									SCREAMING_SNAKE_CASE						= binary_file.read()
						for dat in data:
									SCREAMING_SNAKE_CASE						= F'''{dat:08b}'''
									result += curr_byte
						return result
			except OSError:
						print('File not accessible')
						sys.exit()






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase):
			lexicon.pop(_UpperCAmelCase)
			SCREAMING_SNAKE_CASE						= last_match_id

			if math.loga(_UpperCAmelCase).is_integer():
						for curr_key in lexicon:
									SCREAMING_SNAKE_CASE						= '0' + lexicon[curr_key]

			SCREAMING_SNAKE_CASE						= bin(_UpperCAmelCase)[2:]






def 				lowerCamelCase__				(_UpperCAmelCase):
			SCREAMING_SNAKE_CASE						= {'0': '0', '1': '1'}
			SCREAMING_SNAKE_CASE				,						SCREAMING_SNAKE_CASE						= '', ''
			SCREAMING_SNAKE_CASE						= len(_UpperCAmelCase)

			for i in range(len(_UpperCAmelCase)):
						curr_string += data_bits[i]
						if curr_string not in lexicon:
									continue

						SCREAMING_SNAKE_CASE						= lexicon[curr_string]
						result += last_match_id
						add_key_to_lexicon(_UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase							,       _UpperCAmelCase)
						index += 1
						SCREAMING_SNAKE_CASE						= ''

			while curr_string != "" and curr_string not in lexicon:
						curr_string += "0"

			if curr_string != "":
						SCREAMING_SNAKE_CASE						= lexicon[curr_string]
						result += last_match_id

			return result






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			SCREAMING_SNAKE_CASE						= os.path.getsize(_UpperCAmelCase)
			SCREAMING_SNAKE_CASE						= bin(_UpperCAmelCase)[2:]
			SCREAMING_SNAKE_CASE						= len(_UpperCAmelCase)

			return "0" * (length_length - 1) + file_length_binary + compressed






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			SCREAMING_SNAKE_CASE						= 8
			try:
						with open(_UpperCAmelCase							,       'wb') as opened_file:
									SCREAMING_SNAKE_CASE						= [
									    to_write[i : i + byte_length]
									    for i in range(0							,       len(_UpperCAmelCase)							,       _UpperCAmelCase)
									]

									if len(result_byte_array[-1]) % byte_length == 0:
												result_byte_array.append('10000000')
									else:
												result_byte_array[-1] += "1" + "0" * (
												    byte_length - len(result_byte_array[-1]) - 1
												)

									for elem in result_byte_array:
												opened_file.write(int(_UpperCAmelCase							,       2).to_bytes(1							,       byteorder='big'))
			except OSError:
						print('File not accessible')
						sys.exit()






def 				lowerCamelCase__				(_UpperCAmelCase							,       _UpperCAmelCase):
			SCREAMING_SNAKE_CASE						= read_file_binary(_UpperCAmelCase)
			SCREAMING_SNAKE_CASE						= compress_data(_UpperCAmelCase)
			SCREAMING_SNAKE_CASE						= add_file_length(_UpperCAmelCase							,       _UpperCAmelCase)
			write_file_binary(_UpperCAmelCase							,       _UpperCAmelCase)


if __name__ == "__main__":
				compress(sys.argv[1], sys.argv[2])












from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_torch_available,
)


a_		:						int             =    {
    'configuration_speecht5': [
        'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP',
        'SpeechT5Config',
        'SpeechT5HifiGanConfig',
    ],
    'feature_extraction_speecht5': ['SpeechT5FeatureExtractor'],
    'processing_speecht5': ['SpeechT5Processor'],
}

try:
				if not is_sentencepiece_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				a_		:						Optional[Any]             =    ['SpeechT5Tokenizer']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				a_		:						Optional[int]             =    [
				    'SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'SpeechT5ForSpeechToText',
				    'SpeechT5ForSpeechToSpeech',
				    'SpeechT5ForTextToSpeech',
				    'SpeechT5Model',
				    'SpeechT5PreTrainedModel',
				    'SpeechT5HifiGan',
				]

if TYPE_CHECKING:
				from .configuration_speechta import (
				    SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    SPEECHT5_PRETRAINED_HIFIGAN_CONFIG_ARCHIVE_MAP,
				    SpeechTaConfig,
				    SpeechTaHifiGanConfig,
				)
				from .feature_extraction_speechta import SpeechTaFeatureExtractor
				from .processing_speechta import SpeechTaProcessor

				try:
								if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .tokenization_speechta import SpeechTaTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_speechta import (
								    SPEECHT5_PRETRAINED_MODEL_ARCHIVE_LIST,
								    SpeechTaForSpeechToSpeech,
								    SpeechTaForSpeechToText,
								    SpeechTaForTextToSpeech,
								    SpeechTaHifiGan,
								    SpeechTaModel,
								    SpeechTaPreTrainedModel,
								)

else:
				import sys

				a_		:						Dict             =    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




