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

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase					:    int           = {
    'configuration_efficientformer': [
        'EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EfficientFormerConfig',
    ]
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    Dict           = ['EfficientFormerImageProcessor']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    List[Any]           = [
						    'EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'EfficientFormerForImageClassification',
						    'EfficientFormerForImageClassificationWithTeacher',
						    'EfficientFormerModel',
						    'EfficientFormerPreTrainedModel',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    List[str]           = [
						    'TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'TFEfficientFormerForImageClassification',
						    'TFEfficientFormerForImageClassificationWithTeacher',
						    'TFEfficientFormerModel',
						    'TFEfficientFormerPreTrainedModel',
						]

if TYPE_CHECKING:
						from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .image_processing_efficientformer import EfficientFormerImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_efficientformer import (
												    EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    EfficientFormerForImageClassification,
												    EfficientFormerForImageClassificationWithTeacher,
												    EfficientFormerModel,
												    EfficientFormerPreTrainedModel,
												)
						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_efficientformer import (
												    TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFEfficientFormerForImageClassification,
												    TFEfficientFormerForImageClassificationWithTeacher,
												    TFEfficientFormerModel,
												    TFEfficientFormerPreTrainedModel,
												)

else:
						import sys

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






'''simple docstring'''





def snake_case_     (					lowercase__		):

  if len(lowercase__		) <= 1:
    return [tuple(lowercase__		)]

  UpperCAmelCase__      :					Union[str, Any]				       =							[]

  def generate(lowercase__   ,       lowercase__		):
    UpperCAmelCase__      :					str				       =							[0] * n
    res.append(tuple(lowercase__		)		)

    UpperCAmelCase__      :					Any				       =							0
    while i < n:
      if c[i] < i:
        if i % 2 == 0:
          UpperCAmelCase__       ,			UpperCAmelCase__      :					str				       =							arr[i], arr[0]
        else:
          UpperCAmelCase__       ,			UpperCAmelCase__      :					Optional[Any]				       =							arr[i], arr[c[i]]
        res.append(tuple(lowercase__		)		)
        c[i] += 1
        UpperCAmelCase__      :					List[str]				       =							0
      else:
        UpperCAmelCase__      :					Dict				       =							0
        i += 1

  generate(len(lowercase__		)   ,       lowercase__		)
  return res


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



