# 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 ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tf_available,
    is_torch_available,
)


_import_structure = {
    "configuration_unispeech_sat": ["UniSpeechSatConfig"],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_unispeech_sat"] = [
        "UniSpeechSatForAudioFrameClassification",
        "UniSpeechSatForCTC",
        "UniSpeechSatForPreTraining",
        "UniSpeechSatForSequenceClassification",
        "UniSpeechSatForXVector",
        "UniSpeechSatModel",
        "UniSpeechSatPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_unispeech_sat import UniSpeechSatConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_unispeech_sat import (
            UniSpeechSatForAudioFrameClassification,
            UniSpeechSatForCTC,
            UniSpeechSatForPreTraining,
            UniSpeechSatForSequenceClassification,
            UniSpeechSatForXVector,
            UniSpeechSatModel,
            UniSpeechSatPreTrainedModel,
        )

else:
    import sys

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