


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


UpperCAmelCase__   	=							{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__   	=							['''SqueezeBertTokenizerFast''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__   	=							[
      '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''SqueezeBertForMaskedLM''',
      '''SqueezeBertForMultipleChoice''',
      '''SqueezeBertForQuestionAnswering''',
      '''SqueezeBertForSequenceClassification''',
      '''SqueezeBertForTokenClassification''',
      '''SqueezeBertModel''',
      '''SqueezeBertModule''',
      '''SqueezeBertPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_squeezebert import (
      SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
      SqueezeBertConfig,
      SqueezeBertOnnxConfig,
  )
  from .tokenization_squeezebert import SqueezeBertTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_squeezebert import (
        SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        SqueezeBertForMaskedLM,
        SqueezeBertForMultipleChoice,
        SqueezeBertForQuestionAnswering,
        SqueezeBertForSequenceClassification,
        SqueezeBertForTokenClassification,
        SqueezeBertModel,
        SqueezeBertModule,
        SqueezeBertPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__   	=							_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_torch_available, is_vision_available


UpperCAmelCase__   	=							{
    '''configuration_efficientnet''': [
        '''EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EfficientNetConfig''',
        '''EfficientNetOnnxConfig''',
    ]
}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__   	=							['''EfficientNetImageProcessor''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase__   	=							[
      '''EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''EfficientNetForImageClassification''',
      '''EfficientNetModel''',
      '''EfficientNetPreTrainedModel''',
  ]

if TYPE_CHECKING:
  from .configuration_efficientnet import (
      EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
      EfficientNetConfig,
      EfficientNetOnnxConfig,
  )

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .image_processing_efficientnet import EfficientNetImageProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_efficientnet import (
        EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
        EfficientNetForImageClassification,
        EfficientNetModel,
        EfficientNetPreTrainedModel,
    )

else:
  import sys

  UpperCAmelCase__   	=							_LazyModule(__name__, globals()['''__file__'''], _import_structure)

