'''simple docstring'''






from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_	   =			{
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_	   =			['MaskFormerFeatureExtractor']
    SCREAMING_SNAKE_CASE_	   =			['MaskFormerImageProcessor']


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    SCREAMING_SNAKE_CASE_	   =			[
        'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
        'MaskFormerForInstanceSegmentation',
        'MaskFormerModel',
        'MaskFormerPreTrainedModel',
    ]
    SCREAMING_SNAKE_CASE_	   =			[
        'MaskFormerSwinBackbone',
        'MaskFormerSwinModel',
        'MaskFormerSwinPreTrainedModel',
    ]

if TYPE_CHECKING:
    from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
    from .configuration_maskformer_swin import MaskFormerSwinConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_maskformer import MaskFormerFeatureExtractor
        from .image_processing_maskformer import MaskFormerImageProcessor
    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_maskformer import (
            MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            MaskFormerForInstanceSegmentation,
            MaskFormerModel,
            MaskFormerPreTrainedModel,
        )
        from .modeling_maskformer_swin import (
            MaskFormerSwinBackbone,
            MaskFormerSwinModel,
            MaskFormerSwinPreTrainedModel,
        )


else:
    import sys

    SCREAMING_SNAKE_CASE_	   =			_LazyModule(__name__, globals()['__file__'], _import_structure)
'''simple docstring'''






def  UpperCamelCase__					(					_lowercase    :				list[int]   ,    _lowercase    :				list[int]     )							->	None:
  __UpperCAmelCase:					Dict		= len(_lowercase     )
  print("""The following activities are selected:"""     )

  # The first activity is always selected
  __UpperCAmelCase:					Dict		= 0
  print(_lowercase   ,    end=""","""     )

  # Consider rest of the activities
  for j in range(_lowercase     ):
    # If this activity has start time greater than
    # or equal to the finish time of previously
    # selected activity, then select it
    if start[j] >= finish[i]:
      print(_lowercase   ,    end=""","""     )
      __UpperCAmelCase:					Optional[int]		= j


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    SCREAMING_SNAKE_CASE_	   =			[1, 3, 0, 5, 8, 5]
    SCREAMING_SNAKE_CASE_	   =			[2, 4, 6, 7, 9, 9]
    print_max_activities(start, finish)