class_docstr: ImageInputFeatureConfigMixin is a dataclass that configures the parameters used in both the image input
  feature and the image global defaults section of the Ludwig Config.
class_docstr_tok: ["ImageInputFeatureConfigMixin","is","a","dataclass","that","configures","the","parameters","used","in","both","the","image","input","feature","and","the","image","global","defaults","section","of","the","Ludwig","Config","."]
code: def has_augmentation(self) -> bool:
      # Check for None, False, and []
      return bool(self.augmentation)
  
file_path: ludwig/ludwig/schema/features/image_feature.py
imports: from typing import List
  from ludwig.api_annotations import DeveloperAPI
  from ludwig.constants import IMAGE, MODEL_ECD
  from ludwig.schema import utils
  from ludwig.schema.encoders.base import BaseEncoderConfig
  from ludwig.schema.encoders.utils import EncoderDataclassField
  from ludwig.schema.features.augmentation.base import BaseAugmentationConfig
  from ludwig.schema.features.augmentation.image import RandomHorizontalFlipConfig, RandomRotateConfig
  from ludwig.schema.features.augmentation.utils import AugmentationDataclassField
  from ludwig.schema.features.base import BaseInputFeatureConfig
  from ludwig.schema.features.preprocessing.base import BasePreprocessingConfig
  from ludwig.schema.features.preprocessing.utils import PreprocessingDataclassField
  from ludwig.schema.features.utils import ecd_defaults_config_registry, ecd_input_config_registry, input_mixin_registry
  from ludwig.schema.utils import BaseMarshmallowConfig, ludwig_dataclass
label_desc: Use image node_id 1 for calling the ImageInputFeatureConfigMixin obj's underlying member method code with example usage: obj.has_augmentation() and returns: bool