




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


_snake_case			=						{'''configuration_t5''': ['''T5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''T5Config''', '''T5OnnxConfig''']}

try:
	if not is_sentencepiece_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_snake_case			=						['''T5Tokenizer''']

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_snake_case			=						['''T5TokenizerFast''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_snake_case			=						[
	    '''T5_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''T5EncoderModel''',
	    '''T5ForConditionalGeneration''',
	    '''T5Model''',
	    '''T5PreTrainedModel''',
	    '''load_tf_weights_in_t5''',
	    '''T5ForQuestionAnswering''',
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_snake_case			=						[
	    '''TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''TFT5EncoderModel''',
	    '''TFT5ForConditionalGeneration''',
	    '''TFT5Model''',
	    '''TFT5PreTrainedModel''',
	]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_snake_case			=						[
	    '''FlaxT5EncoderModel''',
	    '''FlaxT5ForConditionalGeneration''',
	    '''FlaxT5Model''',
	    '''FlaxT5PreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

	try:
		if not is_sentencepiece_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_ta import TaTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_ta_fast import TaTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_ta import (
		    T5_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TaEncoderModel,
		    TaForConditionalGeneration,
		    TaForQuestionAnswering,
		    TaModel,
		    TaPreTrainedModel,
		    load_tf_weights_in_ta,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_ta import (
		    TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFTaEncoderModel,
		    TFTaForConditionalGeneration,
		    TFTaModel,
		    TFTaPreTrainedModel,
		)

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_ta import (
		    FlaxTaEncoderModel,
		    FlaxTaForConditionalGeneration,
		    FlaxTaModel,
		    FlaxTaPreTrainedModel,
		)


else:
	import sys

	_snake_case			=						_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





def   _UpperCamelCase   (			snake_case__							)						->   list:
							__UpperCAmelCase						:			Optional[int]         =   1.3
							__UpperCAmelCase						:			Any         =   len(snake_case__							)
							__UpperCAmelCase						:			Optional[Any]         =   False

							while not completed:
														# Update the gap value for a next comb
														__UpperCAmelCase						:			List[str]         =   int(gap / shrink_factor							)
														if gap <= 1:
																					__UpperCAmelCase						:			Dict         =   True

														__UpperCAmelCase						:			List[Any]         =   0
														while index + gap < len(snake_case__							):
																					if data[index] > data[index + gap]:
																												# Swap values
																												__UpperCAmelCase    ,	__UpperCAmelCase						:			Tuple         =   data[index + gap], data[index]
																												__UpperCAmelCase						:			List[str]         =   False
																					index += 1

							return data


if __name__ == "__main__":
	import doctest

	doctest.testmod()

	_snake_case			=						input('''Enter numbers separated by a comma:\n''').strip()
	_snake_case			=						[int(item) for item in user_input.split(''',''')]
	print(comb_sort(unsorted))




