
# 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__)

import abc
import copy
import dataclasses
from dataclasses import dataclass
from typing import ClassVar, Dict, Type, TypeVar

from ..features import Features


A		:   Optional[int]         =    TypeVar('''T''', bound='''TaskTemplate''')



@dataclass(frozen=_a						)
class       a_   ( abc.ABC						):
			# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON serialization
			a  : str
			a  : ClassVar[Features]
			a  : ClassVar[Features]






			def       UpperCamelCase_							(			self							, __UpperCamelCase     ):
									return copy.deepcopy(self     )






			@property
			def       UpperCamelCase_							(			self     ):
									return Features(**self.input_schema							, **self.label_schema     )






			@property
			@abc.abstractmethod
			def       UpperCamelCase_							(			self     ):
									raise NotImplementedError






			@classmethod
			def       UpperCamelCase_							(			cls							, __UpperCamelCase     ):
									_lowercase									=				{f.name for f in dataclasses.fields(cls     )}
									return cls(**{k: v for k, v in template_dict.items() if k in field_names}     )