# 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_torch_available, is_vision_available


_import_structure = {
    "configuration_maskformer": ["MaskFormerConfig"],
    "configuration_maskformer_swin": ["MaskFormerSwinConfig"],
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["feature_extraction_maskformer"] = ["MaskFormerFeatureExtractor"]
    _import_structure["image_processing_maskformer"] = ["MaskFormerImageProcessor"]


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_maskformer"] = [
        "MaskFormerForInstanceSegmentation",
        "MaskFormerModel",
        "MaskFormerPreTrainedModel",
    ]
    _import_structure["modeling_maskformer_swin"] = [
        "MaskFormerSwinBackbone",
        "MaskFormerSwinModel",
        "MaskFormerSwinPreTrainedModel",
    ]

if TYPE_CHECKING:
    from .configuration_maskformer import MaskFormerConfig
    from .configuration_maskformer_swin import MaskFormerSwinConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_maskformer import MaskFormerFeatureExtractor
        from .image_processing_maskformer import MaskFormerImageProcessor
    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_maskformer import (
            MaskFormerForInstanceSegmentation,
            MaskFormerModel,
            MaskFormerPreTrainedModel,
        )
        from .modeling_maskformer_swin import (
            MaskFormerSwinBackbone,
            MaskFormerSwinModel,
            MaskFormerSwinPreTrainedModel,
        )


else:
    import sys

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