public/gpt-2/transformers/models/lxmert/__init__.py

# 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_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

if is_tokenizers_available():
    _import_structure["tokenization_lxmert_fast"] = ["LxmertTokenizerFast"]

if is_torch_available():
    _import_structure["modeling_lxmert"] = [
        "LxmertEncoder",
        "LxmertForPreTraining",
        "LxmertForQuestionAnswering",
        "LxmertModel",
        "LxmertPreTrainedModel",
        "LxmertVisualFeatureEncoder",
        "LxmertXLayer",
    ]

if is_tf_available():
    _import_structure["modeling_tf_lxmert"] = [
        "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFLxmertForPreTraining",
        "TFLxmertMainLayer",
        "TFLxmertModel",
        "TFLxmertPreTrainedModel",
        "TFLxmertVisualFeatureEncoder",
    ]


if TYPE_CHECKING:
    from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
    from .tokenization_lxmert import LxmertTokenizer

    if is_tokenizers_available():
        from .tokenization_lxmert_fast import LxmertTokenizerFast

    if is_torch_available():
        from .modeling_lxmert import (
            LxmertEncoder,
            LxmertForPreTraining,
            LxmertForQuestionAnswering,
            LxmertModel,
            LxmertPreTrainedModel,
            LxmertVisualFeatureEncoder,
            LxmertXLayer,
        )

    if is_tf_available():
        from .modeling_tf_lxmert import (
            TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFLxmertForPreTraining,
            TFLxmertMainLayer,
            TFLxmertModel,
            TFLxmertPreTrainedModel,
            TFLxmertVisualFeatureEncoder,
        )

else:
    import sys

    sys.modules[__name__] = _LazyModule(__name__, globals()["__file__"], _import_structure)