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| # 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 ...utils import ( | |
| OptionalDependencyNotAvailable, | |
| _LazyModule, | |
| is_flax_available, | |
| is_sentencepiece_available, | |
| is_tf_available, | |
| is_tokenizers_available, | |
| is_torch_available, | |
| ) | |
| _import_structure = { | |
| "configuration_albert": ["ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "AlbertConfig", "AlbertOnnxConfig"], | |
| } | |
| try: | |
| if not is_sentencepiece_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| _import_structure["tokenization_albert"] = ["AlbertTokenizer"] | |
| try: | |
| if not is_tokenizers_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| _import_structure["tokenization_albert_fast"] = ["AlbertTokenizerFast"] | |
| try: | |
| if not is_torch_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| _import_structure["modeling_albert"] = [ | |
| "ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST", | |
| "AlbertForMaskedLM", | |
| "AlbertForMultipleChoice", | |
| "AlbertForPreTraining", | |
| "AlbertForQuestionAnswering", | |
| "AlbertForSequenceClassification", | |
| "AlbertForTokenClassification", | |
| "AlbertModel", | |
| "AlbertPreTrainedModel", | |
| "load_tf_weights_in_albert", | |
| ] | |
| try: | |
| if not is_tf_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| _import_structure["modeling_tf_albert"] = [ | |
| "TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST", | |
| "TFAlbertForMaskedLM", | |
| "TFAlbertForMultipleChoice", | |
| "TFAlbertForPreTraining", | |
| "TFAlbertForQuestionAnswering", | |
| "TFAlbertForSequenceClassification", | |
| "TFAlbertForTokenClassification", | |
| "TFAlbertMainLayer", | |
| "TFAlbertModel", | |
| "TFAlbertPreTrainedModel", | |
| ] | |
| try: | |
| if not is_flax_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| _import_structure["modeling_flax_albert"] = [ | |
| "FlaxAlbertForMaskedLM", | |
| "FlaxAlbertForMultipleChoice", | |
| "FlaxAlbertForPreTraining", | |
| "FlaxAlbertForQuestionAnswering", | |
| "FlaxAlbertForSequenceClassification", | |
| "FlaxAlbertForTokenClassification", | |
| "FlaxAlbertModel", | |
| "FlaxAlbertPreTrainedModel", | |
| ] | |
| if TYPE_CHECKING: | |
| from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig, AlbertOnnxConfig | |
| try: | |
| if not is_sentencepiece_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| from .tokenization_albert import AlbertTokenizer | |
| try: | |
| if not is_tokenizers_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| from .tokenization_albert_fast import AlbertTokenizerFast | |
| try: | |
| if not is_torch_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| from .modeling_albert import ( | |
| ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST, | |
| AlbertForMaskedLM, | |
| AlbertForMultipleChoice, | |
| AlbertForPreTraining, | |
| AlbertForQuestionAnswering, | |
| AlbertForSequenceClassification, | |
| AlbertForTokenClassification, | |
| AlbertModel, | |
| AlbertPreTrainedModel, | |
| load_tf_weights_in_albert, | |
| ) | |
| try: | |
| if not is_tf_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| from .modeling_tf_albert import ( | |
| TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST, | |
| TFAlbertForMaskedLM, | |
| TFAlbertForMultipleChoice, | |
| TFAlbertForPreTraining, | |
| TFAlbertForQuestionAnswering, | |
| TFAlbertForSequenceClassification, | |
| TFAlbertForTokenClassification, | |
| TFAlbertMainLayer, | |
| TFAlbertModel, | |
| TFAlbertPreTrainedModel, | |
| ) | |
| try: | |
| if not is_flax_available(): | |
| raise OptionalDependencyNotAvailable() | |
| except OptionalDependencyNotAvailable: | |
| pass | |
| else: | |
| from .modeling_flax_albert import ( | |
| FlaxAlbertForMaskedLM, | |
| FlaxAlbertForMultipleChoice, | |
| FlaxAlbertForPreTraining, | |
| FlaxAlbertForQuestionAnswering, | |
| FlaxAlbertForSequenceClassification, | |
| FlaxAlbertForTokenClassification, | |
| FlaxAlbertModel, | |
| FlaxAlbertPreTrainedModel, | |
| ) | |
| else: | |
| import sys | |
| sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__) | |