from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
    is_vision_available,
)


__SCREAMING_SNAKE_CASE						:   Union[str, Any]         =			{
    'configuration_owlvit': [
        'OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'OwlViTConfig',
        'OwlViTOnnxConfig',
        'OwlViTTextConfig',
        'OwlViTVisionConfig',
    ],
    'processing_owlvit': ['OwlViTProcessor'],
}


try:
				if not is_vision_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE						:   Union[str, Any]         =			['OwlViTFeatureExtractor']
				__SCREAMING_SNAKE_CASE						:   Optional[Any]         =			['OwlViTImageProcessor']

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE						:   Optional[int]         =			[
				    'OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'OwlViTModel',
				    'OwlViTPreTrainedModel',
				    'OwlViTTextModel',
				    'OwlViTVisionModel',
				    'OwlViTForObjectDetection',
				]

if TYPE_CHECKING:
				from .configuration_owlvit import (
				    OWLVIT_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    OwlViTConfig,
				    OwlViTOnnxConfig,
				    OwlViTTextConfig,
				    OwlViTVisionConfig,
				)
				from .processing_owlvit import OwlViTProcessor

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .feature_extraction_owlvit import OwlViTFeatureExtractor
								from .image_processing_owlvit import OwlViTImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_owlvit import (
								    OWLVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    OwlViTForObjectDetection,
								    OwlViTModel,
								    OwlViTPreTrainedModel,
								    OwlViTTextModel,
								    OwlViTVisionModel,
								)

else:
				import sys

				__SCREAMING_SNAKE_CASE						:   str         =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)
# 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_tokenizers_available, is_torch_available


__SCREAMING_SNAKE_CASE						:   Any         =			{'configuration_mra': ['MRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MraConfig']}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE						:   Optional[Any]         =			[
				    'MRA_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'MraForMaskedLM',
				    'MraForMultipleChoice',
				    'MraForQuestionAnswering',
				    'MraForSequenceClassification',
				    'MraForTokenClassification',
				    'MraLayer',
				    'MraModel',
				    'MraPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_mra import MRA_PRETRAINED_CONFIG_ARCHIVE_MAP, MraConfig

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mra import (
								    MRA_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MraForMaskedLM,
								    MraForMultipleChoice,
								    MraForQuestionAnswering,
								    MraForSequenceClassification,
								    MraForTokenClassification,
								    MraLayer,
								    MraModel,
								    MraPreTrainedModel,
								)
else:
				import sys

				__SCREAMING_SNAKE_CASE						:   str         =			_LazyModule(__name__, globals()['__file__'], _import_structure)