


'''simple docstring'''
def 				lowerCamelCase_   (   __UpperCamelCase				:					list		)				->  list:







     """simple docstring"""
     for i, _ in enumerate(__UpperCamelCase		):
          if (i % 2 == 1) == (nums[i - 1] > nums[i]):
               _A		,							_A				=       nums[i], nums[i - 1]

     return nums


if __name__ == "__main__":
    print("""Enter the array elements:""")
    lowerCAmelCase  =				list(map(int, input().split()))
    print("""The unsorted array is:""")
    print(array)
    print("""Array after Wiggle sort:""")
    print(wiggle_sort(array))









'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowerCAmelCase  =				{
    """configuration_convnextv2""": [
        """CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ConvNextV2Config""",
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase  =				[
        """CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """ConvNextV2ForImageClassification""",
        """ConvNextV2Model""",
        """ConvNextV2PreTrainedModel""",
        """ConvNextV2Backbone""",
    ]


if TYPE_CHECKING:
    from .configuration_convnextva import (
        CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
        ConvNextVaConfig,
    )

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_convnextva import (
            CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
            ConvNextVaBackbone,
            ConvNextVaForImageClassification,
            ConvNextVaModel,
            ConvNextVaPreTrainedModel,
        )

else:
    import sys

    lowerCAmelCase  =				_LazyModule(__name__, globals()["""__file__"""], _import_structure)





