# Copyright 2022 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_tokenizers_available, is_torch_available _import_structure = { "configuration_markuplm": ["MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "MarkupLMConfig"], "feature_extraction_markuplm": ["MarkupLMFeatureExtractor"], "processing_markuplm": ["MarkupLMProcessor"], "tokenization_markuplm": ["MarkupLMTokenizer"], } try: if not is_tokenizers_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["tokenization_markuplm_fast"] = ["MarkupLMTokenizerFast"] try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: _import_structure["modeling_markuplm"] = [ "MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST", "MarkupLMForQuestionAnswering", "MarkupLMForSequenceClassification", "MarkupLMForTokenClassification", "MarkupLMModel", "MarkupLMPreTrainedModel", ] if TYPE_CHECKING: from .configuration_markuplm import MARKUPLM_PRETRAINED_CONFIG_ARCHIVE_MAP, MarkupLMConfig from .feature_extraction_markuplm import MarkupLMFeatureExtractor from .processing_markuplm import MarkupLMProcessor from .tokenization_markuplm import MarkupLMTokenizer try: if not is_tokenizers_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .tokenization_markuplm_fast import MarkupLMTokenizerFast try: if not is_torch_available(): raise OptionalDependencyNotAvailable() except OptionalDependencyNotAvailable: pass else: from .modeling_markuplm import ( MARKUPLM_PRETRAINED_MODEL_ARCHIVE_LIST, MarkupLMForQuestionAnswering, MarkupLMForSequenceClassification, MarkupLMForTokenClassification, MarkupLMModel, MarkupLMPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)