# 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 from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig from .tokenization_layoutlm import LayoutLMTokenizer _import_structure = { "configuration_layoutlm": ["LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMConfig"], "tokenization_layoutlm": ["LayoutLMTokenizer"], } if is_tokenizers_available(): _import_structure["tokenization_layoutlm_fast"] = ["LayoutLMTokenizerFast"] if is_torch_available(): _import_structure["modeling_layoutlm"] = [ "LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST", "LayoutLMForMaskedLM", "LayoutLMForSequenceClassification", "LayoutLMForTokenClassification", "LayoutLMModel", "LayoutLMPreTrainedModel", ] if is_tf_available(): _import_structure["modeling_tf_layoutlm"] = [ "TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST", "TFLayoutLMForMaskedLM", "TFLayoutLMForSequenceClassification", "TFLayoutLMForTokenClassification", "TFLayoutLMMainLayer", "TFLayoutLMModel", "TFLayoutLMPreTrainedModel", ] if TYPE_CHECKING: from .configuration_layoutlm import LAYOUTLM_PRETRAINED_CONFIG_ARCHIVE_MAP, LayoutLMConfig from .tokenization_layoutlm import LayoutLMTokenizer if is_tokenizers_available(): from .tokenization_layoutlm_fast import LayoutLMTokenizerFast if is_torch_available(): from .modeling_layoutlm import ( LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST, LayoutLMForMaskedLM, LayoutLMForSequenceClassification, LayoutLMForTokenClassification, LayoutLMModel, LayoutLMPreTrainedModel, ) if is_tf_available(): from .modeling_tf_layoutlm import ( TF_LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST, TFLayoutLMForMaskedLM, TFLayoutLMForSequenceClassification, TFLayoutLMForTokenClassification, TFLayoutLMMainLayer, TFLayoutLMModel, TFLayoutLMPreTrainedModel, ) else: import sys sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)