



'''simple docstring'''
import math
import os
import sys






def A__       (	UpperCAmelCase_				):
						_UpperCamelCase   :						Union[str, Any]												=  ''
						try:
												with open(UpperCAmelCase_    ,    'rb'				) as binary_file:
																		_UpperCamelCase   :						Dict												=  binary_file.read()
												for dat in data:
																		_UpperCamelCase   :						Union[str, Any]												=  f'{dat:08b}'
																		result += curr_byte
												return result
						except OSError:
												print('File not accessible'				)
												sys.exit()






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				):
						lexicon.pop(UpperCAmelCase_				)
						_UpperCamelCase   :						Dict												=  last_match_id

						if math.loga(UpperCAmelCase_				).is_integer():
												for curr_key in lexicon:
																		_UpperCamelCase   :						Tuple												=  '0' + lexicon[curr_key]

						_UpperCamelCase   :						Optional[Any]												=  bin(UpperCAmelCase_				)[2:]






def A__       (	UpperCAmelCase_				):
						_UpperCamelCase   :						Optional[Any]												=  {'0': '0', '1': '1'}
						_UpperCamelCase							,     _UpperCamelCase   :						Any												=  '', ''
						_UpperCamelCase   :						int												=  len(UpperCAmelCase_				)

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

												_UpperCamelCase   :						Optional[int]												=  lexicon[curr_string]
												result += last_match_id
												add_key_to_lexicon(UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_    ,    UpperCAmelCase_				)
												index += 1
												_UpperCamelCase   :						Union[str, Any]												=  ''

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

						if curr_string != "":
												_UpperCamelCase   :						Union[str, Any]												=  lexicon[curr_string]
												result += last_match_id

						return result






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						Tuple												=  os.path.getsize(UpperCAmelCase_				)
						_UpperCamelCase   :						str												=  bin(UpperCAmelCase_				)[2:]
						_UpperCamelCase   :						Dict												=  len(UpperCAmelCase_				)

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






def A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						Union[str, Any]												=  8
						try:
												with open(UpperCAmelCase_    ,    'wb'				) as opened_file:
																		_UpperCamelCase   :						Tuple												=  [
																		    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 A__       (	UpperCAmelCase_    ,    UpperCAmelCase_				):
						_UpperCamelCase   :						Optional[Any]												=  read_file_binary(UpperCAmelCase_				)
						_UpperCamelCase   :						Tuple												=  compress_data(UpperCAmelCase_				)
						_UpperCamelCase   :						List[Any]												=  add_file_length(UpperCAmelCase_    ,    UpperCAmelCase_				)
						write_file_binary(UpperCAmelCase_    ,    UpperCAmelCase_				)


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







'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


snake_case_					:      Union[str, Any]    			=    {
    'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
    'tokenization_transfo_xl': ['TransfoXLCorpus', 'TransfoXLTokenizer'],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_					:      str    			=    [
					    'TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'AdaptiveEmbedding',
					    'TransfoXLForSequenceClassification',
					    'TransfoXLLMHeadModel',
					    'TransfoXLModel',
					    'TransfoXLPreTrainedModel',
					    'load_tf_weights_in_transfo_xl',
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_					:      Any    			=    [
					    'TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFAdaptiveEmbedding',
					    'TFTransfoXLForSequenceClassification',
					    'TFTransfoXLLMHeadModel',
					    'TFTransfoXLMainLayer',
					    'TFTransfoXLModel',
					    'TFTransfoXLPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_transfo_xl import TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP, TransfoXLConfig
					from .tokenization_transfo_xl import TransfoXLCorpus, TransfoXLTokenizer

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_transfo_xl import (
										    TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
										    AdaptiveEmbedding,
										    TransfoXLForSequenceClassification,
										    TransfoXLLMHeadModel,
										    TransfoXLModel,
										    TransfoXLPreTrainedModel,
										    load_tf_weights_in_transfo_xl,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_transfo_xl import (
										    TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFAdaptiveEmbedding,
										    TFTransfoXLForSequenceClassification,
										    TFTransfoXLLMHeadModel,
										    TFTransfoXLMainLayer,
										    TFTransfoXLModel,
										    TFTransfoXLPreTrainedModel,
										)

else:
					import sys

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


