
'''simple docstring'''
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,
)


lowerCAmelCase :  Optional[int]      =      {'configuration_t5': ['T5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'T5Config', 'T5OnnxConfig']}

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

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

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase :  Union[str, Any]      =      [
						    '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:
						lowerCAmelCase :  Union[str, Any]      =      [
						    'TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TFT5EncoderModel',
						    'TFT5ForConditionalGeneration',
						    'TFT5Model',
						    'TFT5PreTrainedModel',
						]

try:
						if not is_flax_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase :  Union[str, Any]      =      [
						    '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

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











"""simple docstring"""





def 		lowerCAmelCase_	(  lowercase_   :							Any		):

 '''simple docstring'''






 __SCREAMING_SNAKE_CASE :			Optional[int]												=       len(lowercase_		)
 for i in range(length - 1		):
  __SCREAMING_SNAKE_CASE :			str												=       False
  for j in range(length - 1 - i		):
   if collection[j] > collection[j + 1]:
    __SCREAMING_SNAKE_CASE :			Any												=       True
    __SCREAMING_SNAKE_CASE							,      __SCREAMING_SNAKE_CASE :			List[str]												=       collection[j + 1], collection[j]
  if not swapped:
   break  # Stop iteration if the collection is sorted.
 return collection


if __name__ == "__main__":
    import doctest
    import time

    doctest.testmod()

    _lowerCamelCase       =	input('''Enter numbers separated by a comma:''').strip()
    _lowerCamelCase       =	[int(item) for item in user_input.split(''',''')]
    _lowerCamelCase       =	time.process_time()
    print(*bubble_sort(unsorted), sep=''',''')
    print(f'Processing time: {(time.process_time() - start)%1e9 + 7}')

