




'''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,
)


a__         =     {
    '''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:
		a__         =     [
		    '''TVLT_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''TvltModel''',
		    '''TvltForPreTraining''',
		    '''TvltForAudioVisualClassification''',
		    '''TvltPreTrainedModel''',
		]

try:
		if not is_vision_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__         =     ['''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

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





'''simple docstring'''

class __magic_name__:






						def __init__(   self						:						List[Any]       ):



									'''simple docstring'''






									snake_case__          =						[]
									snake_case__          =						0
									snake_case__          =						0






						def __str__(   self						:						Union[str, Any]       ):



									'''simple docstring'''






									snake_case__          =						"""<""" + str(self.entries       )[1:-1] + """>"""
									return printed






						def       __lowerCAmelCase(   self						:						List[Any]					,   __UpperCamelCase						:						List[Any]       ):



									'''simple docstring'''






									self.entries.append(__UpperCamelCase       )
									snake_case__          =						self.length + 1






						def       __lowerCAmelCase(   self						:						int       ):



									'''simple docstring'''






									snake_case__          =						self.length - 1
									snake_case__          =						self.entries[self.front]
									# self.front-=1
									# self.entries = self.entries[self.front:]
									snake_case__          =						self.entries[1:]
									return dequeued






						def       __lowerCAmelCase(   self						:						str					,   __UpperCamelCase						:						Optional[Any]       ):



									'''simple docstring'''






									for _ in range(__UpperCamelCase       ):
												self.put(self.get()       )






						def       __lowerCAmelCase(   self						:						List[Any]       ):



									'''simple docstring'''






									return self.entries[0]






						def       __lowerCAmelCase(   self						:						str       ):



									'''simple docstring'''






									return self.length