



from typing import TYPE_CHECKING

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


_snake_case	=						{
    "configuration_groupvit": [
        "GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "GroupViTConfig",
        "GroupViTOnnxConfig",
        "GroupViTTextConfig",
        "GroupViTVisionConfig",
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case	=						[
						    "GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "GroupViTModel",
						    "GroupViTPreTrainedModel",
						    "GroupViTTextModel",
						    "GroupViTVisionModel",
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_snake_case	=						[
						    "TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "TFGroupViTModel",
						    "TFGroupViTPreTrainedModel",
						    "TFGroupViTTextModel",
						    "TFGroupViTVisionModel",
						]

if TYPE_CHECKING:
						from .configuration_groupvit import (
						    GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    GroupViTConfig,
						    GroupViTOnnxConfig,
						    GroupViTTextConfig,
						    GroupViTVisionConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_groupvit import (
												    GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    GroupViTModel,
												    GroupViTPreTrainedModel,
												    GroupViTTextModel,
												    GroupViTVisionModel,
												)

						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_groupvit import (
												    TF_GROUPVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFGroupViTModel,
												    TFGroupViTPreTrainedModel,
												    TFGroupViTTextModel,
												    TFGroupViTVisionModel,
												)

else:
						import sys

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





def        A       (      _lowerCamelCase						):





							'''simple docstring'''




							_lowerCAmelCase  :							int				     =					len(_lowerCamelCase						)
							for i in range(1       ,				_lowerCamelCase						):
														_lowerCAmelCase  :							List[Any]				     =					collection[i]
														_lowerCAmelCase  :							str				     =					0
														_lowerCAmelCase  :							Union[str, Any]				     =					i - 1

														while low <= high:
																					_lowerCAmelCase  :							List[str]				     =					(low + high) // 2
																					if val < collection[mid]:
																												_lowerCAmelCase  :							Optional[int]				     =					mid - 1
																					else:
																												_lowerCAmelCase  :							List[str]				     =					mid + 1
														for j in range(_lowerCamelCase       ,				_lowerCamelCase       ,				-1						):
																					_lowerCAmelCase  :							int				     =					collection[j - 1]
														_lowerCAmelCase  :							Optional[int]				     =					val
							return collection


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