





"""simple docstring"""




from typing import TYPE_CHECKING

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


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

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

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a		:					Union[str, Any]	      =     [
		    '''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

		a		:					List[str]	      =     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





"""simple docstring"""
# Copyright 2022 The HuggingFace Team and The OpenBMB 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


_A							=  {
    """configuration_cpmant""": ["""CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CpmAntConfig"""],
    """tokenization_cpmant""": ["""CpmAntTokenizer"""],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _A							=  [
        """CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """CpmAntForCausalLM""",
        """CpmAntModel""",
        """CpmAntPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
    from .tokenization_cpmant import CpmAntTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_cpmant import (
            CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
            CpmAntForCausalLM,
            CpmAntModel,
            CpmAntPreTrainedModel,
        )


else:
    import sys

    _A							=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

