




from typing import TYPE_CHECKING

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


snake_case_ : List[Any]    		=       {
    "configuration_rembert": ["REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RemBertConfig", "RemBertOnnxConfig"]
}

try:
    if not is_sentencepiece_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : int    		=       ["RemBertTokenizer"]

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : List[Any]    		=       ["RemBertTokenizerFast"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : Optional[int]    		=       [
        "REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "RemBertForCausalLM",
        "RemBertForMaskedLM",
        "RemBertForMultipleChoice",
        "RemBertForQuestionAnswering",
        "RemBertForSequenceClassification",
        "RemBertForTokenClassification",
        "RemBertLayer",
        "RemBertModel",
        "RemBertPreTrainedModel",
        "load_tf_weights_in_rembert",
    ]


try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_ : int    		=       [
        "TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFRemBertForCausalLM",
        "TFRemBertForMaskedLM",
        "TFRemBertForMultipleChoice",
        "TFRemBertForQuestionAnswering",
        "TFRemBertForSequenceClassification",
        "TFRemBertForTokenClassification",
        "TFRemBertLayer",
        "TFRemBertModel",
        "TFRemBertPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_rembert import REMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RemBertConfig, RemBertOnnxConfig

    try:
        if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_rembert import RemBertTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_rembert_fast import RemBertTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_rembert import (
            REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            RemBertForCausalLM,
            RemBertForMaskedLM,
            RemBertForMultipleChoice,
            RemBertForQuestionAnswering,
            RemBertForSequenceClassification,
            RemBertForTokenClassification,
            RemBertLayer,
            RemBertModel,
            RemBertPreTrainedModel,
            load_tf_weights_in_rembert,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_rembert import (
            TF_REMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFRemBertForCausalLM,
            TFRemBertForMaskedLM,
            TFRemBertForMultipleChoice,
            TFRemBertForQuestionAnswering,
            TFRemBertForSequenceClassification,
            TFRemBertForTokenClassification,
            TFRemBertLayer,
            TFRemBertModel,
            TFRemBertPreTrainedModel,
        )


else:
    import sys

    snake_case_ : List[str]    		=       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)












"""simple docstring"""






def      _snake_case			(				lowercase__		):
				stooge(lowercase__							,    0							,    len(lowercase__		) - 1		)
				return arr







def      _snake_case			(				lowercase__							,    lowercase__							,    lowercase__		):
				if i >= h:
								return

				# If first element is smaller than the last then swap them
				if arr[i] > arr[h]:
								_lowerCamelCase, _lowerCamelCase     :			Optional[Any]    =    arr[h], arr[i]

				# If there are more than 2 elements in the array
				if h - i + 1 > 2:
								_lowerCamelCase     :			Union[str, Any]    =    (int)((h - i + 1) / 3		)

								# Recursively sort first 2/3 elements
								stooge(lowercase__							,    lowercase__							,    (h - t)		)

								# Recursively sort last 2/3 elements
								stooge(lowercase__							,    i + t							,    (lowercase__)		)

								# Recursively sort first 2/3 elements
								stooge(lowercase__							,    lowercase__							,    (h - t)		)


if __name__ == "__main__":
			lowercase__     						=						input("""Enter numbers separated by a comma:\n""").strip()
			lowercase__     						=						[int(item) for item in user_input.split(""",""")]
			print(stooge_sort(unsorted))