





'''simple docstring'''







from typing import Any


class    __a :

	def __init__(							self							:       Any				)   ->    Optional[int]:







							"""simple docstring"""
							UpperCAmelCase_     : Dict         =					[]
							UpperCAmelCase_     : Dict         =					0

	def __str__(							self							:       Optional[Any]				)   ->    List[str]:







							"""simple docstring"""
							UpperCAmelCase_     : int         =					'<' + str(self.stack				)[1:-1] + '>'
							return printed

	def       UpperCAmelCase__		(							self							:       List[str]    ,       __magic_name__							:       Tuple				)   ->    None:







							"""simple docstring"""
							self.stack.append(__UpperCamelCase				)
							UpperCAmelCase_     : Union[str, Any]         =					self.length + 1

	def       UpperCAmelCase__		(							self							:       int				)   ->    Any:







							"""simple docstring"""
							self.rotate(1				)
							UpperCAmelCase_     : str         =					self.stack[self.length - 1]
							UpperCAmelCase_     : List[Any]         =					self.stack[:-1]
							self.rotate(self.length - 1				)
							UpperCAmelCase_     : Optional[Any]         =					self.length - 1
							return dequeued

	def       UpperCAmelCase__		(							self							:       str    ,       __magic_name__							:       Tuple				)   ->    None:







							"""simple docstring"""







							for _ in range(__UpperCamelCase				):
													UpperCAmelCase_     : Dict         =					self.stack[0]
													UpperCAmelCase_     : Any         =					self.stack[1:]
													self.put(__UpperCamelCase				)
													UpperCAmelCase_     : Optional[Any]         =					self.length - 1

	def       UpperCAmelCase__		(							self							:       List[Any]				)   ->    Any:







							"""simple docstring"""
							UpperCAmelCase_     : Union[str, Any]         =					self.get()
							self.put(__UpperCamelCase				)
							self.rotate(self.length - 1				)
							return front



	def       UpperCAmelCase__		(							self							:       int				)   ->    int:







							"""simple docstring"""
							return self.length












'''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

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


snake_case_       :    List[Any]          =					{
    "configuration_tvlt": ["TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP", "TvltConfig"],
    "feature_extraction_tvlt": ["TvltFeatureExtractor"],
    "processing_tvlt": ["TvltProcessor"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_       :    Optional[int]          =					[
					    "TVLT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "TvltModel",
					    "TvltForPreTraining",
					    "TvltForAudioVisualClassification",
					    "TvltPreTrainedModel",
					]

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_       :    List[Any]          =					["TvltImageProcessor"]


if TYPE_CHECKING:
					from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
					from .processing_tvlt import TvltProcessor
					from .feature_extraction_tvlt import TvltFeatureExtractor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tvlt import (
										    TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TvltForAudioVisualClassification,
										    TvltForPreTraining,
										    TvltModel,
										    TvltPreTrainedModel,
										)

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_tvlt import TvltImageProcessor


else:
					import sys

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





