





# 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


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


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    snake_case_           =      [
        '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

    snake_case_           =      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)








class 		SCREAMING_SNAKE_CASE__    :


      def __init__(self	:				str    ,      a__	:				list				):





         """simple docstring"""



         __snake_case								=       set_counts
         __snake_case								=       max(a__				)
         __snake_case								=       len(a__				)
         __snake_case								=       [1] * num_sets
         __snake_case								=       list(range(a__				)				)


      def        a			(self	:				str    ,      a__	:				int    ,      a__	:				int				):





         """simple docstring"""



         __snake_case								=       self.get_parent(a__				)
         __snake_case								=       self.get_parent(a__				)

         if src_parent == dst_parent:
            return False

         if self.ranks[dst_parent] >= self.ranks[src_parent]:
            self.set_counts[dst_parent] += self.set_counts[src_parent]
            __snake_case								=       0
            __snake_case								=       dst_parent
            if self.ranks[dst_parent] == self.ranks[src_parent]:
               self.ranks[dst_parent] += 1
            __snake_case								=       self.set_counts[dst_parent]
         else:
            self.set_counts[src_parent] += self.set_counts[dst_parent]
            __snake_case								=       0
            __snake_case								=       src_parent
            __snake_case								=       self.set_counts[src_parent]

         __snake_case								=       max(self.max_set    ,      a__				)
         return True


      def        a			(self	:				Union[str, Any]    ,      a__	:				int				):





         """simple docstring"""



         if self.parents[disj_set] == disj_set:
            return disj_set
         __snake_case								=       self.get_parent(self.parents[disj_set]				)
         return self.parents[disj_set]

