public/gpt-2/transformers/models/distilbert/__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_tf_available, is_tokenizers_available, is_torch_available


_import_structure = {
    "configuration_distilbert": [
        "DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "DistilBertConfig",
        "DistilBertOnnxConfig",
    ],
    "tokenization_distilbert": ["DistilBertTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_distilbert_fast"] = ["DistilBertTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_distilbert"] = [
        "DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "DistilBertForMaskedLM",
        "DistilBertForMultipleChoice",
        "DistilBertForQuestionAnswering",
        "DistilBertForSequenceClassification",
        "DistilBertForTokenClassification",
        "DistilBertModel",
        "DistilBertPreTrainedModel",
    ]

if is_tf_available():
    _import_structure["modeling_tf_distilbert"] = [
        "TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFDistilBertForMaskedLM",
        "TFDistilBertForMultipleChoice",
        "TFDistilBertForQuestionAnswering",
        "TFDistilBertForSequenceClassification",
        "TFDistilBertForTokenClassification",
        "TFDistilBertMainLayer",
        "TFDistilBertModel",
        "TFDistilBertPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_distilbert import (
        DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
        DistilBertConfig,
        DistilBertOnnxConfig,
    )
    from .tokenization_distilbert import DistilBertTokenizer

    if is_tokenizers_available():
        from .tokenization_distilbert_fast import DistilBertTokenizerFast

    if is_torch_available():
        from .modeling_distilbert import (
            DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            DistilBertForMaskedLM,
            DistilBertForMultipleChoice,
            DistilBertForQuestionAnswering,
            DistilBertForSequenceClassification,
            DistilBertForTokenClassification,
            DistilBertModel,
            DistilBertPreTrainedModel,
        )

    if is_tf_available():
        from .modeling_tf_distilbert import (
            TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFDistilBertForMaskedLM,
            TFDistilBertForMultipleChoice,
            TFDistilBertForQuestionAnswering,
            TFDistilBertForSequenceClassification,
            TFDistilBertForTokenClassification,
            TFDistilBertMainLayer,
            TFDistilBertModel,
            TFDistilBertPreTrainedModel,
        )

else:
    import sys

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