public/gpt-2/transformers/models/ibert/__init__.py

# 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_torch_available


_import_structure = {
    "configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig"],
}

if is_torch_available():
    _import_structure["modeling_ibert"] = [
        "IBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "IBertForMaskedLM",
        "IBertForMultipleChoice",
        "IBertForQuestionAnswering",
        "IBertForSequenceClassification",
        "IBertForTokenClassification",
        "IBertModel",
        "IBertPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_ibert import IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, IBertConfig

    if is_torch_available():
        from .modeling_ibert import (
            IBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            IBertForMaskedLM,
            IBertForMultipleChoice,
            IBertForQuestionAnswering,
            IBertForSequenceClassification,
            IBertForTokenClassification,
            IBertModel,
            IBertPreTrainedModel,
        )

else:
    import sys

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