




'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_conditional_detr import ConditionalDetrImageProcessor


lowerCAmelCase  =				logging.get_logger(__name__)






class 					lowerCAmelCase_     (    A__  ):






       def __init__(   self ,    *_UpperCamelCase ,    **_UpperCamelCase      )->			Tuple:
            warnings.warn(
                'The class ConditionalDetrFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'
                ' Please use ConditionalDetrImageProcessor instead.' ,    _UpperCamelCase ,    )
            super().__init__(*_UpperCamelCase ,    **_UpperCamelCase      )









'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


lowerCAmelCase  =				{
    """configuration_segformer""": ["""SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SegformerConfig""", """SegformerOnnxConfig"""]
}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase  =				["""SegformerFeatureExtractor"""]
    lowerCAmelCase  =				["""SegformerImageProcessor"""]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase  =				[
        """SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """SegformerDecodeHead""",
        """SegformerForImageClassification""",
        """SegformerForSemanticSegmentation""",
        """SegformerLayer""",
        """SegformerModel""",
        """SegformerPreTrainedModel""",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCAmelCase  =				[
        """TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
        """TFSegformerDecodeHead""",
        """TFSegformerForImageClassification""",
        """TFSegformerForSemanticSegmentation""",
        """TFSegformerModel""",
        """TFSegformerPreTrainedModel""",
    ]


if TYPE_CHECKING:
    from .configuration_segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig, SegformerOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_segformer import SegformerFeatureExtractor
        from .image_processing_segformer import SegformerImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_segformer import (
            SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            SegformerDecodeHead,
            SegformerForImageClassification,
            SegformerForSemanticSegmentation,
            SegformerLayer,
            SegformerModel,
            SegformerPreTrainedModel,
        )
    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_segformer import (
            TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFSegformerDecodeHead,
            TFSegformerForImageClassification,
            TFSegformerForSemanticSegmentation,
            TFSegformerModel,
            TFSegformerPreTrainedModel,
        )

else:
    import sys

    lowerCAmelCase  =				_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





