master
/ transformers / models / squeezebert / __init__.py

__init__.py @3c11360 — raw · history · blame 

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# flake8: noqa
# There's no way to ignore "F401 '...' imported but unused" warnings in this
# module, but to preserve other warnings. So, don't check this module at all.

# Copyright 2020 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 ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available


_import_structure = {
    "configuration_squeezebert": ["SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "SqueezeBertConfig"],
    "tokenization_squeezebert": ["SqueezeBertTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_squeezebert_fast"] = ["SqueezeBertTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_squeezebert"] = [
        "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
    from .tokenization_squeezebert import SqueezeBertTokenizer

    if is_tokenizers_available():
        from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

    if is_torch_available():
        from .modeling_squeezebert import (
            SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            SqueezeBertForMaskedLM,
            SqueezeBertForMultipleChoice,
            SqueezeBertForQuestionAnswering,
            SqueezeBertForSequenceClassification,
            SqueezeBertForTokenClassification,
            SqueezeBertModel,
            SqueezeBertModule,
            SqueezeBertPreTrainedModel,
        )

else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)