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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_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)
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