


'''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, is_vision_available


lowerCAmelCase						=					{
    """configuration_vivit""": ["""VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VivitConfig"""],
}
try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase						=					["""VivitImageProcessor"""]


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase						=					[
        """VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """VivitModel""",
        """VivitPreTrainedModel""",
        """VivitForVideoClassification""",
    ]


if TYPE_CHECKING:
    from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .image_processing_vivit import VivitImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_vivit import (
            VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            VivitForVideoClassification,
            VivitModel,
            VivitPreTrainedModel,
        )


else:
    import sys

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









'''simple docstring'''
class        lowerCAmelCase_  :






       def __init__( self			,     _UpperCamelCase   )->      None:
            _A				=							size
            _A				=							[0] * size
            _A				=							[0] * size






       @staticmethod
       def   UpperCamelCase						( _UpperCamelCase   )->      int:
            return index | (index + 1)






       @staticmethod
       def   UpperCamelCase						( _UpperCamelCase   )->      int:
            return (index & (index + 1)) - 1






       def   UpperCamelCase						( self			,     _UpperCamelCase			,     _UpperCamelCase   )->      None:
            _A				=							value
            while index < self.size:
                 _A				=							self.get_prev(_UpperCamelCase   ) + 1
                 if current_left_border == index:
                      _A				=							value
                 else:
                      _A				=							max(_UpperCamelCase			,     _UpperCamelCase			,     _UpperCamelCase   )
                 _A				=							self.get_next(_UpperCamelCase   )






       def   UpperCamelCase						( self			,     _UpperCamelCase			,     _UpperCamelCase   )->      int:
            right -= 1  # Because of right is exclusive
            _A				=							0
            while left <= right:
                 _A				=							self.get_prev(_UpperCamelCase   )
                 if left <= current_left:
                      _A				=							max(_UpperCamelCase			,     self.tree[right]   )
                      _A				=							current_left
                 else:
                      _A				=							max(_UpperCamelCase			,     self.arr[right]   )
                      right -= 1
            return result


if __name__ == "__main__":
    import doctest

    doctest.testmod()





