Viewing File: /home/ubuntu/combine_ai/combine/lib/python3.10/site-packages/transformers/models/dpt/__init__.py

# 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 ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable


_import_structure = {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["feature_extraction_dpt"] = ["DPTFeatureExtractor"]
    _import_structure["image_processing_dpt"] = ["DPTImageProcessor"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _import_structure["modeling_dpt"] = [
        "DPT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "DPTForDepthEstimation",
        "DPTForSemanticSegmentation",
        "DPTModel",
        "DPTPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_dpt import DPT_PRETRAINED_CONFIG_ARCHIVE_MAP, DPTConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_dpt import DPTFeatureExtractor
        from .image_processing_dpt import DPTImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_dpt import (
            DPT_PRETRAINED_MODEL_ARCHIVE_LIST,
            DPTForDepthEstimation,
            DPTForSemanticSegmentation,
            DPTModel,
            DPTPreTrainedModel,
        )


else:
    import sys

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