Python PreprocessingDataclassField Examples

Example #1

class BinaryInputFeatureConfig(BaseInputFeatureConfig):
    """BinaryInputFeature is a dataclass that configures the parameters used for a binary input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(feature_type=BINARY)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(BINARY).keys()),
        default="passthrough",
        description="Encoder to use for this binary feature.",
    )

Example #2

class DateInputFeatureConfig(BaseInputFeatureConfig):
    """DateInputFeature is a dataclass that configures the parameters used for a date input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(feature_type=DATE)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(DATE).keys()),
        default="embed",
        description="Encoder to use for this date feature.",
    )

Example #3

File: category_feature.py Project: ludwig-ai/ludwig

class CategoryInputFeatureConfig(BaseInputFeatureConfig):
    """CategoryInputFeature is a dataclass that configures the parameters used for a category input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(
        feature_type=CATEGORY)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(CATEGORY).keys()),
        default="dense",
        description="Encoder to use for this category feature.",
    )

Example #4

File: image_feature.py Project: ludwig-ai/ludwig

class ImageInputFeatureConfig(BaseInputFeatureConfig):
    """ImageInputFeatureConfig is a dataclass that configures the parameters used for an image input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(
        feature_type=IMAGE)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(IMAGE).keys()),
        default="stacked_cnn",
        description="Encoder to use for this image feature.",
    )

Example #5

File: vector_feature.py Project: ludwig-ai/ludwig

class VectorInputFeatureConfig(BaseInputFeatureConfig):
    """VectorInputFeatureConfig is a dataclass that configures the parameters used for a vector input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(
        feature_type=VECTOR)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(VECTOR).keys()),
        default="dense",
        description="Encoder to use for this vector feature.",
    )

Example #6

File: text_feature.py Project: ludwig-ai/ludwig

class TextInputFeatureConfig(BaseInputFeatureConfig):
    """TextInputFeatureConfig is a dataclass that configures the parameters used for a text input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(
        feature_type=TEXT)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(TEXT).keys()),
        default="parallel_cnn",
        description="Encoder to use for this text feature.",
    )

Example #7

File: number_feature.py Project: ludwig-ai/ludwig

class NumberInputFeatureConfig(BaseInputFeatureConfig):
    """NumberInputFeature is a dataclass that configures the parameters used for a number input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(
        feature_type=NUMBER)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(NUMBER).keys()),
        default="passthrough",
        description="Encoder to use for this number feature.",
    )

Example #8

File: audio_feature.py Project: ludwig-ai/ludwig

class AudioInputFeatureConfig(BaseInputFeatureConfig):
    """AudioFeatureInputFeature is a dataclass that configures the parameters used for an audio input feature."""

    preprocessing: BasePreprocessingConfig = PreprocessingDataclassField(
        feature_type=AUDIO)

    encoder: Optional[str] = schema_utils.StringOptions(
        list(get_encoder_classes(AUDIO).keys()),
        default="parallel_cnn",
        description="Encoder to use for this audio feature.",
    )