# 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_tf_available, is_tokenizers_available, is_torch_available, ) _import_structure = { "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"], "tokenization_bart": ["BartTokenizer"], } try: if not is_tokenizers_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["tokenization_bart_fast"] = ["BartTokenizerFast"] try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_bart"] = [ "BART_PRETRAINED_MODEL_ARCHIVE_LIST", "BartForCausalLM", "BartForConditionalGeneration", "BartForQuestionAnswering", "BartForSequenceClassification", "BartModel", "BartPreTrainedModel", "BartPretrainedModel", "PretrainedBartModel", ] try: if not is_tf_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_tf_bart"] = [ "TFBartForConditionalGeneration", "TFBartForSequenceClassification", "TFBartModel", "TFBartPretrainedModel", ] try: if not is_flax_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_flax_bart"] = [ "FlaxBartDecoderPreTrainedModel", "FlaxBartForCausalLM", "FlaxBartForConditionalGeneration", "FlaxBartForQuestionAnswering", "FlaxBartForSequenceClassification", "FlaxBartModel", "FlaxBartPreTrainedModel", ] if TYPE_CHECKING: from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig from .tokenization_bart import BartTokenizer try: if not is_tokenizers_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .tokenization_bart_fast import BartTokenizerFast try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_bart import ( BART_PRETRAINED_MODEL_ARCHIVE_LIST, BartForCausalLM, BartForConditionalGeneration, BartForQuestionAnswering, BartForSequenceClassification, BartModel, BartPreTrainedModel, BartPretrainedModel, PretrainedBartModel, ) try: if not is_tf_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_tf_bart import ( TFBartForConditionalGeneration, TFBartForSequenceClassification, TFBartModel, TFBartPretrainedModel, ) try: if not is_flax_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_flax_bart import ( FlaxBartDecoderPreTrainedModel, FlaxBartForCausalLM, FlaxBartForConditionalGeneration, FlaxBartForQuestionAnswering, FlaxBartForSequenceClassification, FlaxBartModel, FlaxBartPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)