public/gpt-2/transformers/models/hubert/__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 2021 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_torch_available


_import_structure = {
    "configuration_hubert": ["HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "HubertConfig"],
}

if is_torch_available():
    _import_structure["modeling_hubert"] = [
        "HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "HubertForCTC",
        "HubertModel",
        "HubertPreTrainedModel",
    ]


if is_tf_available():
    _import_structure["modeling_tf_hubert"] = [
        "TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFHubertForCTC",
        "TFHubertModel",
        "TFHubertPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

    if is_torch_available():
        from .modeling_hubert import (
            HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            HubertForCTC,
            HubertModel,
            HubertPreTrainedModel,
        )

    if is_tf_available():
        from .modeling_tf_hubert import (
            TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFHubertForCTC,
            TFHubertModel,
            TFHubertPreTrainedModel,
        )


else:
    import sys

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