






from typing import TYPE_CHECKING

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


__lowerCamelCase      :    Tuple   		=   {"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTConfig""", """ViTOnnxConfig"""]}

try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase      :    Tuple   		=   ["""ViTFeatureExtractor"""]
				__lowerCamelCase      :    List[str]   		=   ["""ViTImageProcessor"""]

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase      :    Optional[int]   		=   [
				    """VIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """ViTForImageClassification""",
				    """ViTForMaskedImageModeling""",
				    """ViTModel""",
				    """ViTPreTrainedModel""",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase      :    Union[str, Any]   		=   [
				    """TFViTForImageClassification""",
				    """TFViTModel""",
				    """TFViTPreTrainedModel""",
				]

try:
				if not is_flax_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__lowerCamelCase      :    Dict   		=   [
				    """FlaxViTForImageClassification""",
				    """FlaxViTModel""",
				    """FlaxViTPreTrainedModel""",
				]

if TYPE_CHECKING:
				from .configuration_vit import VIT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTConfig, ViTOnnxConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_vit import ViTFeatureExtractor
								from .image_processing_vit import ViTImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_vit import (
								    VIT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    ViTForImageClassification,
								    ViTForMaskedImageModeling,
								    ViTModel,
								    ViTPreTrainedModel,
								)

				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_vit import TFViTForImageClassification, TFViTModel, TFViTPreTrainedModel

				try:
								if not is_flax_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_flax_vit import FlaxViTForImageClassification, FlaxViTModel, FlaxViTPreTrainedModel


else:
				import sys

				__lowerCamelCase      :    Any   		=   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)











def   SCREAMING_SNAKE_CASE       (				snake_case_      :							list     ):
	if len(snake_case_     ) <= 1:
		return lst

	snake_case__				:   List[Any]     =						1

	while i < len(snake_case_     ):
		if lst[i - 1] <= lst[i]:
			i += 1
		else:
			snake_case__,		snake_case__				:   Tuple     =						lst[i], lst[i - 1]
			i -= 1
			if i == 0:
				snake_case__				:   Union[str, Any]     =						1

	return lst


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



