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algorithm_schemas

Config YAML specification classes related to algorithms.

Classes​

AggregatorConfig​

class AggregatorConfig(    secure: bool, weights: Optional[dict[str, Union[int, float]]] = None,):

Configuration for the Aggregator.

Variables​

  • static secure : bool
  • static weights : Optional[dict[str, typing.Union[int, float]]]

AlgorithmConfig​

class AlgorithmConfig(name: str, arguments: Optional[Any] = None):

Configuration for the Algorithm.

Subclasses​

Variables​

  • static arguments : Optional[Any]
  • static name : str

BscanImageAndMaskGenerationAlgorithmArgumentsConfig​

class BscanImageAndMaskGenerationAlgorithmArgumentsConfig(    segmentation_configs: list[bscan_mod.SegmentationConfig],    save_path: Optional[Path] = None,    output_original_bscans: Optional[bool] = False,    image_format: Optional[bscan_mod.ImageFormats] = ImageFormats.JPEG,    image_optimize: Optional[bool] = True,    image_quality: Optional[int] = 90,    image_subsampling: Optional[int] = 0,    image_progressive: Optional[bool] = True,    image_transparency: Optional[bool] = False,):

Configuration for BscanImageAndMaskGenerationAlgorithm arguments.

Variables​

  • static image_optimize : Optional[bool]
  • static image_progressive : Optional[bool]
  • static image_quality : Optional[int]
  • static image_subsampling : Optional[int]
  • static image_transparency : Optional[bool]
  • static output_original_bscans : Optional[bool]

BscanImageAndMaskGenerationAlgorithmConfig​

class BscanImageAndMaskGenerationAlgorithmConfig(    name: str, arguments: Optional[BscanImageAndMaskGenerationAlgorithmArgumentsConfig],):

Configuration for BscanImageAndMaskGenerationAlgorithm.

Ancestors​

Variables​

  • static name : str

CSVReportAlgorithmArgumentsConfig​

class CSVReportAlgorithmArgumentsConfig(    save_path: Optional[Path] = None,    original_cols: Optional[list[str]] = None,    filter: Optional[list[ColumnFilter]] = None,):

Configuration for CSVReportAlgorithm arguments.

Variables​

  • static original_cols : Optional[list[str]]

CSVReportAlgorithmConfig​

class CSVReportAlgorithmConfig(    name: str,    arguments: Optional[CSVReportAlgorithmArgumentsConfig] = CSVReportAlgorithmArgumentsConfig(save_path=None, original_cols=None, filter=None),):

Configuration for CSVReportAlgorithm.

Ancestors​

Variables​

  • static name : str

CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig​

class CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig(    save_path: Optional[Path] = None,    trial_name: Optional[str] = None,    original_cols: Optional[list[str]] = None,    aux_cols: Optional[list[str]] = [],    rename_columns: Optional[dict[str, str]] = None,    filter: Optional[list[ColumnFilter]] = None,    match_patient_visit: Optional[MatchPatientVisit] = None,    matched_csv_path: Optional[Path] = None,    produce_matched_only: bool = True,    csv_extensions: Optional[list[str]] = None,    produce_trial_notes_csv: bool = False,    sorting_columns: Optional[dict[str, str]] = None,):

Configuration for CSVReportGeneratorOphthalmologyAlgorithm arguments.

Variables​

  • static aux_cols : Optional[list[str]]
  • static csv_extensions : Optional[list[str]]
  • static original_cols : Optional[list[str]]
  • static produce_matched_only : bool
  • static produce_trial_notes_csv : bool
  • static rename_columns : Optional[dict[str, str]]
  • static sorting_columns : Optional[dict[str, str]]
  • static trial_name : Optional[str]

CSVReportGeneratorOphthalmologyAlgorithmConfig​

class CSVReportGeneratorOphthalmologyAlgorithmConfig(    name: str,    arguments: Optional[CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig] = CSVReportGeneratorOphthalmologyAlgorithmArgumentsConfig(save_path=None, trial_name=None, original_cols=None, aux_cols=[], rename_columns=None, filter=None, match_patient_visit=None, matched_csv_path=None, produce_matched_only=True, csv_extensions=None, produce_trial_notes_csv=False, sorting_columns=None),):

Configuration for CSVReportGeneratorOphthalmologyAlgorithm.

Ancestors​

Variables​

  • static name : str

EHRPatientInfoDownloadAlgorithmConfig​

class EHRPatientInfoDownloadAlgorithmConfig(    name: str,    arguments: Optional[EHRPatientInfoDownloadArgumentsConfig] = EHRPatientInfoDownloadArgumentsConfig(),):

Configuration for EHRPatientInfoDownloadAlgorithm.

Ancestors​

Variables​

  • static name : str

EHRPatientInfoDownloadArgumentsConfig​

class EHRPatientInfoDownloadArgumentsConfig():

Configuration for EHRPatientInfoDownloadAlgorithm arguments.

EHRPatientQueryAlgorithmConfig​

class EHRPatientQueryAlgorithmConfig(    name: str,    arguments: EHRPatientQueryArgumentsConfig = EHRPatientQueryArgumentsConfig(),):

Configuration for EHRPatientQuery algorithm.

Ancestors​

Variables​

  • static name : str

EHRPatientQueryArgumentsConfig​

class EHRPatientQueryArgumentsConfig():

Configuration for EHRPatientQuery algorithm arguments.

ETDRSAlgorithmArgumentsConfig​

class ETDRSAlgorithmArgumentsConfig(    laterality: str,    slo_photo_location_prefixes: Optional[SLOSegmentationLocationPrefix] = None,    slo_image_metadata_columns: Optional[SLOImageMetadataColumns] = None,    oct_image_metadata_columns: Optional[OCTImageMetadataColumns] = None,    threshold: float = 0.7,    calculate_on_oct: bool = False,    slo_mm_width: float = 8.8,    slo_mm_height: float = 8.8,):

Configuration for ETDRSAlgorithm arguments.

Variables​

  • static calculate_on_oct : bool
  • static laterality : str
  • static slo_mm_height : float
  • static slo_mm_width : float
  • static threshold : float

ETDRSAlgorithmConfig​

class ETDRSAlgorithmConfig(name: str, arguments: Optional[ETDRSAlgorithmArgumentsConfig]):

Configuration for ETDRSAlgorithm.

Ancestors​

Variables​

  • static name : str

FederatedModelTrainingAlgorithmConfig​

class FederatedModelTrainingAlgorithmConfig(    name: str,    arguments: Optional[FederatedModelTrainingArgumentsConfig] = FederatedModelTrainingArgumentsConfig(modeller_checkpointing=True, checkpoint_filename=None),    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the FederatedModelTraining algorithm.

Ancestors​

Variables​

  • static name : str

FederatedModelTrainingArgumentsConfig​

class FederatedModelTrainingArgumentsConfig(    modeller_checkpointing: bool = True, checkpoint_filename: Optional[str] = None,):

Configuration for the FederatedModelTraining algorithm arguments.

Variables​

  • static checkpoint_filename : Optional[str]
  • static modeller_checkpointing : bool

FluidVolumeCalculationAlgorithmArgumentsConfig​

class FluidVolumeCalculationAlgorithmArgumentsConfig(    fluid_volume_include_segmentations: Optional[list[str]] = None,):

Configuration for FluidVolumeCalculationAlgorithm arguments.

Variables​

  • static fluid_volume_include_segmentations : Optional[list[str]]

FluidVolumeCalculationAlgorithmConfig​

class FluidVolumeCalculationAlgorithmConfig(    name: str,    arguments: Optional[FluidVolumeCalculationAlgorithmArgumentsConfig] = FluidVolumeCalculationAlgorithmArgumentsConfig(fluid_volume_include_segmentations=None),):

Configuration for FluidVolumeCalculationAlgorithm.

Ancestors​

Variables​

  • static name : str

FoveaCoordinatesAlgorithmArgumentsConfig​

class FoveaCoordinatesAlgorithmArgumentsConfig(    bscan_width_col: str = 'size_width',    location_prefixes: Optional[SLOSegmentationLocationPrefix] = None,):

Configuration for FoveaCoordinatesAlgorithm arguments.

Variables​

  • static bscan_width_col : str

FoveaCoordinatesAlgorithmConfig​

class FoveaCoordinatesAlgorithmConfig(    name: str,    arguments: Optional[FoveaCoordinatesAlgorithmArgumentsConfig] = FoveaCoordinatesAlgorithmArgumentsConfig(bscan_width_col='size_width', location_prefixes=None),):

Configuration for FoveaCoordinatesAlgorithm.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmAmethystArgumentsConfig​

class GATrialCalculationAlgorithmAmethystArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,):

Configuration for GATrialCalculationAlgorithmAmethyst arguments.

Ancestors​

  • bitfount.runners.config_schemas.algorithm_schemas._GATrialCalculationAlgorithmBaseArgumentsConfig

GATrialCalculationAlgorithmAmethystConfig​

class GATrialCalculationAlgorithmAmethystConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmAmethystArgumentsConfig] = GATrialCalculationAlgorithmAmethystArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None),):

Configuration for GATrialCalculationAlgorithmAmethyst.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmBronzeArgumentsConfig​

class GATrialCalculationAlgorithmBronzeArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,    fovea_landmark_idx: Optional[int] = 1,):

Configuration for GATrialCalculationAlgorithmBronze arguments.

Ancestors​

  • bitfount.runners.config_schemas.algorithm_schemas._GATrialCalculationWithFoveaAlgorithmBaseArgumentsConfig

GATrialCalculationAlgorithmBronzeConfig​

class GATrialCalculationAlgorithmBronzeConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmBronzeArgumentsConfig] = GATrialCalculationAlgorithmBronzeArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None, fovea_landmark_idx=1),):

Configuration for GATrialCalculationAlgorithmBronze.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmCharcoalArgumentsConfig​

class GATrialCalculationAlgorithmCharcoalArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,    fovea_landmark_idx: Optional[int] = 1,):

Configuration for GATrialCalculationAlgorithmCharcoal arguments.

Ancestors​

  • bitfount.runners.config_schemas.algorithm_schemas._GATrialCalculationWithFoveaAlgorithmBaseArgumentsConfig

GATrialCalculationAlgorithmCharcoalConfig​

class GATrialCalculationAlgorithmCharcoalConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmCharcoalArgumentsConfig] = GATrialCalculationAlgorithmCharcoalArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None, fovea_landmark_idx=1),):

Configuration for GATrialCalculationAlgorithmCharcoal.

Ancestors​

Variables​

  • static name : str

GATrialCalculationAlgorithmJadeArgumentsConfig​

class GATrialCalculationAlgorithmJadeArgumentsConfig(    ga_area_include_segmentations: Optional[list[str]] = None,    ga_area_exclude_segmentations: Optional[list[str]] = None,):

Configuration for GATrialCalculationAlgorithmJade arguments.

Ancestors​

  • bitfount.runners.config_schemas.algorithm_schemas._GATrialCalculationAlgorithmBaseArgumentsConfig

GATrialCalculationAlgorithmJadeConfig​

class GATrialCalculationAlgorithmJadeConfig(    name: str,    arguments: Optional[GATrialCalculationAlgorithmJadeArgumentsConfig] = GATrialCalculationAlgorithmJadeArgumentsConfig(ga_area_include_segmentations=None, ga_area_exclude_segmentations=None),):

Configuration for GATrialCalculationAlgorithmJade.

Ancestors​

Variables​

  • static name : str

GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig​

class GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig(    report_metadata: Optional[ReportMetadata] = None,    filename_prefix: Optional[str] = None,    save_path: Optional[Path] = None,    filter: Optional[list[ColumnFilter]] = None,    pdf_filename_columns: Optional[list[str]] = None,    trial_name: Optional[str] = None,):

Configuration for GATrialPDFGeneratorAlgorithmAmethyst arguments.

Variables​

  • static filename_prefix : Optional[str]
  • static pdf_filename_columns : Optional[list[str]]
  • static trial_name : Optional[str]

GATrialPDFGeneratorAlgorithmAmethystConfig​

class GATrialPDFGeneratorAlgorithmAmethystConfig(    name: str,    arguments: Optional[GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig] = GATrialPDFGeneratorAlgorithmAmethystArgumentsConfig(report_metadata=None, filename_prefix=None, save_path=None, filter=None, pdf_filename_columns=None, trial_name=None),):

Configuration for GATrialPDFGeneratorAlgorithmAmethyst.

Ancestors​

Variables​

  • static name : str

GATrialPDFGeneratorAlgorithmJadeArgumentsConfig​

class GATrialPDFGeneratorAlgorithmJadeArgumentsConfig(    report_metadata: Optional[ReportMetadata] = None,    filename_prefix: Optional[str] = None,    save_path: Optional[Path] = None,    filter: Optional[list[ColumnFilter]] = None,    pdf_filename_columns: Optional[list[str]] = None,    trial_name: Optional[str] = None,):

Configuration for GATrialPDFGeneratorAlgorithmJade arguments.

Variables​

  • static filename_prefix : Optional[str]
  • static pdf_filename_columns : Optional[list[str]]
  • static trial_name : Optional[str]

GATrialPDFGeneratorAlgorithmJadeConfig​

class GATrialPDFGeneratorAlgorithmJadeConfig(    name: str,    arguments: Optional[GATrialPDFGeneratorAlgorithmJadeArgumentsConfig] = GATrialPDFGeneratorAlgorithmJadeArgumentsConfig(report_metadata=None, filename_prefix=None, save_path=None, filter=None, pdf_filename_columns=None, trial_name=None),):

Configuration for GATrialPDFGeneratorAlgorithmJade.

Ancestors​

Variables​

  • static name : str

GenericAlgorithmConfig​

class GenericAlgorithmConfig(name: str, arguments: _JSONDict = {}):

Configuration for unspecified algorithm plugins.

Raises

  • ValueError: if the algorithm name starts with bitfount.

Ancestors​

Variables​

  • static name : str

HuggingFaceImageClassificationInferenceAlgorithmConfig​

class HuggingFaceImageClassificationInferenceAlgorithmConfig(    name: str,    arguments: Optional[HuggingFaceImageClassificationInferenceArgumentsConfig],):

Configuration for HuggingFaceImageClassificationInference.

Ancestors​

Variables​

  • static name : str

HuggingFaceImageClassificationInferenceArgumentsConfig​

class HuggingFaceImageClassificationInferenceArgumentsConfig(    model_id: str,    apply_softmax_to_predictions: bool = True,    batch_size: int = 1,    seed: int = 42,    top_k: int = 5,):

Configuration for HuggingFaceImageClassificationInference arguments.

Variables​

  • static apply_softmax_to_predictions : bool
  • static batch_size : int
  • static model_id : str
  • static seed : int
  • static top_k : int

HuggingFaceImageSegmentationInferenceAlgorithmConfig​

class HuggingFaceImageSegmentationInferenceAlgorithmConfig(    name: str, arguments: Optional[HuggingFaceImageSegmentationInferenceArgumentsConfig],):

Configuration for HuggingFaceImageSegmentationInference.

Ancestors​

Variables​

  • static name : str

HuggingFaceImageSegmentationInferenceArgumentsConfig​

class HuggingFaceImageSegmentationInferenceArgumentsConfig(    model_id: str,    alpha: float = 0.3,    batch_size: int = 1,    dataframe_output: bool = False,    mask_threshold: float = 0.5,    overlap_mask_area_threshold: float = 0.5,    seed: int = 42,    save_path: Optional[str] = None,    subtask: Optional[str] = None,    threshold: float = 0.9,):

Configuration for HuggingFaceImageSegmentationInference arguments.

Variables​

  • static alpha : float
  • static batch_size : int
  • static dataframe_output : bool
  • static mask_threshold : float
  • static model_id : str
  • static overlap_mask_area_threshold : float
  • static save_path : Optional[str]
  • static seed : int
  • static subtask : Optional[str]
  • static threshold : float

HuggingFacePerplexityEvaluationAlgorithmConfig​

class HuggingFacePerplexityEvaluationAlgorithmConfig(    name: str, arguments: Optional[HuggingFacePerplexityEvaluationArgumentsConfig],):

Configuration for the HuggingFacePerplexityEvaluation algorithm.

Ancestors​

Variables​

  • static name : str

HuggingFacePerplexityEvaluationArgumentsConfig​

class HuggingFacePerplexityEvaluationArgumentsConfig(    model_id: str, stride: int = 512, seed: int = 42,):

Configuration for the HuggingFacePerplexityEvaluation algorithm arguments.

Variables​

  • static model_id : str
  • static seed : int
  • static stride : int

HuggingFaceTextClassificationInferenceAlgorithmConfig​

class HuggingFaceTextClassificationInferenceAlgorithmConfig(    name: str, arguments: Optional[HuggingFaceTextClassificationInferenceArgumentsConfig],):

Configuration for HuggingFaceTextClassificationInference.

Ancestors​

Variables​

  • static name : str

HuggingFaceTextClassificationInferenceArgumentsConfig​

class HuggingFaceTextClassificationInferenceArgumentsConfig(    model_id: str,    batch_size: int = 1,    function_to_apply: Optional[str] = None,    seed: int = 42,    top_k: int = 5,):

Configuration for HuggingFaceTextClassificationInference arguments.

Variables​

  • static batch_size : int
  • static function_to_apply : Optional[str]
  • static model_id : str
  • static seed : int
  • static top_k : int

HuggingFaceTextGenerationInferenceAlgorithmConfig​

class HuggingFaceTextGenerationInferenceAlgorithmConfig(    name: str, arguments: Optional[HuggingFaceTextGenerationInferenceArgumentsConfig],):

Configuration for the HuggingFaceTextGenerationInference algorithm.

Ancestors​

Variables​

  • static name : str

HuggingFaceTextGenerationInferenceArgumentsConfig​

class HuggingFaceTextGenerationInferenceArgumentsConfig(    model_id: str,    prompt_format: Optional[str] = None,    max_length: int = 50,    num_return_sequences: int = 1,    seed: int = 42,    min_new_tokens: int = 1,    repetition_penalty: float = 1.0,    num_beams: int = 1,    early_stopping: bool = True,    pad_token_id: Optional[int] = None,    eos_token_id: Optional[int] = None,    device: Optional[str] = None,    torch_dtype: str = 'float32',):

Configuration for the HuggingFaceTextGenerationInference algorithm arguments.

Variables​

  • static device : Optional[str]
  • static early_stopping : bool
  • static eos_token_id : Optional[int]
  • static max_length : int
  • static min_new_tokens : int
  • static model_id : str
  • static num_beams : int
  • static num_return_sequences : int
  • static pad_token_id : Optional[int]
  • static prompt_format : Optional[str]
  • static repetition_penalty : float
  • static seed : int
  • static torch_dtype : str

ImageSelectionAlgorithmArgumentsConfig​

class ImageSelectionAlgorithmArgumentsConfig():

Configuration for ImageSelectionAlgorithm arguments.

ImageSelectionAlgorithmConfig​

class ImageSelectionAlgorithmConfig(    name: str, arguments: ImageSelectionAlgorithmArgumentsConfig,):

Configuration for ImageSelectionAlgorithm algorithm.

Ancestors​

Variables​

  • static name : str

ModelAlgorithmConfig​

class ModelAlgorithmConfig(    name: str,    arguments: Optional[Any] = None,    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the Model algorithms.

Ancestors​

Subclasses​

Variables​

ModelEvaluationAlgorithmConfig​

class ModelEvaluationAlgorithmConfig(    name: str,    arguments: Optional[ModelEvaluationArgumentsConfig],    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the ModelEvaluation algorithm.

Ancestors​

Variables​

  • static name : str

ModelEvaluationArgumentsConfig​

class ModelEvaluationArgumentsConfig():

Configuration for the ModelEvaluation algorithm arguments.

ModelInferenceAlgorithmConfig​

class ModelInferenceAlgorithmConfig(    name: str,    arguments: ModelInferenceArgumentsConfig = ModelInferenceArgumentsConfig(class_outputs=None, postprocessors=None),    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the ModelInference algorithm.

Ancestors​

Variables​

  • static name : str

ModelInferenceArgumentsConfig​

class ModelInferenceArgumentsConfig(    class_outputs: Optional[list[str]] = None,    postprocessors: Optional[list[dict[str, str]]] = None,):

Configuration for the ModelInference algorithm arguments.

Variables​

  • static class_outputs : Optional[list[str]]
  • static postprocessors : Optional[list[dict[str, str]]]

ModelTrainingAndEvaluationAlgorithmConfig​

class ModelTrainingAndEvaluationAlgorithmConfig(    name: str,    arguments: Optional[ModelTrainingAndEvaluationArgumentsConfig],    model: Optional[ModelConfig] = None,    pretrained_file: Optional[Path] = None,):

Configuration for the ModelTrainingAndEvaluation algorithm.

Ancestors​

Variables​

  • static name : str

ModelTrainingAndEvaluationArgumentsConfig​

class ModelTrainingAndEvaluationArgumentsConfig():

Configuration for the ModelTrainingAndEvaluation algorithm arguments.

PrivateSqlQueryAlgorithmConfig​

class PrivateSqlQueryAlgorithmConfig(    name: str, arguments: PrivateSqlQueryArgumentsConfig,):

Configuration for the PrivateSqlQuery algorithm.

Ancestors​

Variables​

  • static name : str

PrivateSqlQueryArgumentsConfig​

class PrivateSqlQueryArgumentsConfig(    query: str,    epsilon: float,    delta: float,    column_ranges: Union[dict[str, PrivateSqlQueryColumnArgumentsConfig], dict[str, dict[str, PrivateSqlQueryColumnArgumentsConfig]]],    table: Optional[str] = None,    db_schema: Optional[str] = None,):

Configuration for the PrivateSqlQuery algorithm arguments.

Variables​

  • static db_schema : Optional[str]
  • static delta : float
  • static epsilon : float
  • static query : str
  • static table : Optional[str]

PrivateSqlQueryColumnArgumentsConfig​

class PrivateSqlQueryColumnArgumentsConfig(    lower: Optional[int] = None, upper: Optional[int] = None,):

Configuration for the PrivateSqlQuery algorithm column arguments.

Variables​

  • static lower : Optional[int]
  • static upper : Optional[int]

RecordFilterAlgorithmArgumentsConfig​

class RecordFilterAlgorithmArgumentsConfig(    strategies: Sequence[Union[FilterStrategy, str]],    filter_args_list: list[dict[str, Any]],):

Configuration for RecordFilter algorithm arguments.

Variables​

  • static filter_args_list : list[dict[str, typing.Any]]

RecordFilterAlgorithmConfig​

class RecordFilterAlgorithmConfig(    name: str, arguments: Optional[RecordFilterAlgorithmArgumentsConfig],):

Configuration for RecordFilter algorithm.

Ancestors​

Variables​

  • static name : str

ReduceCSVAlgorithmCharcoalArgumentsConfig​

class ReduceCSVAlgorithmCharcoalArgumentsConfig(    save_path: Optional[Path] = None,    eligible_only: bool = True,    delete_intermediate: bool = True,):

Configuration for ReduceCSVAlgorithmCharcoal arguments.

Variables​

  • static delete_intermediate : bool
  • static eligible_only : bool

ReduceCSVAlgorithmCharcoalConfig​

class ReduceCSVAlgorithmCharcoalConfig(    name: str,    arguments: Optional[ReduceCSVAlgorithmCharcoalArgumentsConfig] = ReduceCSVAlgorithmCharcoalArgumentsConfig(save_path=None, eligible_only=True, delete_intermediate=True),):

Configuration for ReduceCSVAlgorithmCharcoal.

Ancestors​

Variables​

  • static name : str

S3UploadAlgorithmArgumentsConfig​

class S3UploadAlgorithmArgumentsConfig(    s3_bucket: str, aws_region: Optional[str], aws_profile: str = 'default',):

Configuration for S3UploadAlgorithm arguments.

Variables​

  • static aws_profile : str
  • static aws_region : Optional[str]
  • static s3_bucket : str

S3UploadAlgorithmConfig​

class S3UploadAlgorithmConfig(    name: str, arguments: Optional[S3UploadAlgorithmArgumentsConfig],):

Configuration for S3UploadAlgorithm.

Ancestors​

Variables​

  • static name : str

SqlQueryAlgorithmConfig​

class SqlQueryAlgorithmConfig(name: str, arguments: SqlQueryArgumentsConfig):

Configuration for the SqlQuery algorithm.

Ancestors​

Variables​

  • static name : str

SqlQueryArgumentsConfig​

class SqlQueryArgumentsConfig(query: str, table: Optional[str] = None):

Configuration for the SqlQuery algorithm arguments.

Variables​

  • static query : str
  • static table : Optional[str]

TIMMFineTuningAlgorithmConfig​

class TIMMFineTuningAlgorithmConfig(    name: str, arguments: Optional[TIMMFineTuningArgumentsConfig],):

Configuration for TIMMFineTuning algorithm.

Ancestors​

Variables​

  • static name : str

TIMMFineTuningArgumentsConfig​

class TIMMFineTuningArgumentsConfig(    model_id: str,    args: Optional[TemplatedTimmTrainingConfig] = None,    batch_transformations: Optional[dict[str, list[Union[str, _JSONDict]]]] = None,    labels: Optional[list[str]] = None,    return_weights: bool = False,    save_path: Optional[Path] = None,):

Configuration for TIMMFineTuning algorithm arguments.

Variables​

  • static labels : Optional[list[str]]
  • static model_id : str
  • static return_weights : bool

TIMMInferenceAlgorithmConfig​

class TIMMInferenceAlgorithmConfig(    name: str, arguments: Optional[TIMMInferenceArgumentsConfig],):

Configuration for TIMMInference algorithm.

Ancestors​

Variables​

  • static name : str

TIMMInferenceArgumentsConfig​

class TIMMInferenceArgumentsConfig(    model_id: str,    num_classes: Optional[int] = None,    checkpoint_path: Optional[Path] = None,    class_outputs: Optional[list[str]] = None,    batch_transformations: Optional[list[Union[str, _JSONDict]]] = None,):

Configuration for TIMMInference algorithm arguments.

Variables​

  • static class_outputs : Optional[list[str]]
  • static model_id : str
  • static num_classes : Optional[int]

TemplatedTimmTrainingConfig​

class TemplatedTimmTrainingConfig(    pretrained: bool = True,    initial_checkpoint: str = '',    num_classes: Optional[int] = None,    gp: Optional[str] = None,    img_size: Optional[int] = None,    in_chans: Optional[int] = None,    input_size: Optional[tuple[int, int, int]] = None,    crop_pct: Optional[float] = None,    mean: Optional[list[float]] = None,    std: Optional[list[float]] = None,    interpolation: str = '',    batch_size: int = 16,    validation_batch_size: Optional[int] = None,    channels_last: bool = False,    fuser: str = '',    grad_accum_steps: int = 1,    grad_checkpointing: bool = False,    fast_norm: bool = False,    model_kwargs: dict[str, Any] = {},    head_init_scale: Optional[float] = None,    head_init_bias: Optional[float] = None,    torchscript: bool = False,    torchcompile: Optional[str] = None,    opt: str = 'sgd',    opt_eps: Optional[float] = None,    opt_betas: Optional[list[float]] = None,    momentum: float = 0.9,    weight_decay: float = 0.05,    clip_grad: Optional[float] = None,    clip_mode: str = 'norm',    layer_decay: Optional[float] = 0.65,    opt_kwargs: dict[str, Any] = {},    sched: str = 'constant_with_warmup',    sched_on_updates: bool = False,    lr: Optional[float] = 1e-05,    lr_base: float = 0.005,    lr_base_size: int = 256,    lr_base_scale: str = '',    lr_noise: Optional[list[float]] = None,    lr_noise_pct: float = 0.67,    lr_noise_std: float = 1.0,    lr_cycle_mul: float = 1.0,    lr_cycle_decay: float = 0.5,    lr_cycle_limit: int = 1,    lr_k_decay: float = 1.0,    warmup_lr: float = 1e-05,    min_lr: float = 0,    epochs: int = 300,    epoch_repeats: float = 0.0,    start_epoch: Optional[int] = None,    decay_milestones: list[int] = [90, 180, 270],    decay_epochs: float = 90,    warmup_epochs: int = 5,    warmup_prefix: bool = False,    cooldown_epochs: int = 0,    patience_epochs: int = 10,    decay_rate: float = 1.0,    aug_splits: int = 0,    jsd_loss: bool = False,    bce_loss: bool = False,    bce_target_thresh: Optional[float] = None,    resplit: bool = False,    mixup: float = 0.0,    cutmix: float = 0.0,    cutmix_minmax: Optional[list[float]] = None,    mixup_prob: float = 1.0,    mixup_switch_prob: float = 0.5,    mixup_mode: str = 'batch',    mixup_off_epoch: int = 0,    smoothing: float = 0.1,    drop: float = 0.0,    drop_connect: Optional[float] = None,    drop_path: Optional[float] = 0.2,    drop_block: Optional[float] = None,    bn_momentum: Optional[float] = None,    bn_eps: Optional[float] = None,    sync_bn: bool = False,    dist_bn: str = 'reduce',    split_bn: bool = False,    model_ema: bool = False,    model_ema_force_cpu: bool = False,    model_ema_decay: float = 0.9998,    seed: int = 42,    log_interval: int = 50,    recovery_interval: int = 0,    checkpoint_hist: int = 10,    workers: int = 4,    save_images: bool = False,    amp: bool = False,    amp_dtype: str = 'float16',    amp_impl: str = 'native',    no_ddp_bb: bool = False,    synchronize_step: bool = False,    no_prefetcher: bool = False,    eval_metric: str = 'top1',    tta: int = 0,    local_rank: int = 0,):

Configuration for TIMMFineTuning algorithm arguments.

Ancestors​

Variables​

  • static batch_size : int
  • static epochs : int
  • static lr : Optional[float]

TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig(    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    largest_ga_lesion_upper_bound: Optional[float] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,):

Configuration for TrialInclusionCriteriaMatchAlgorithmAmethyst arguments.

Ancestors​

  • bitfount.runners.config_schemas.algorithm_schemas._TrialInclusionCriteriaMatchAlgorithmBaseArgumentsConfig

TrialInclusionCriteriaMatchAlgorithmAmethystConfig​

class TrialInclusionCriteriaMatchAlgorithmAmethystConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmAmethystArgumentsConfig(cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, largest_ga_lesion_upper_bound=None, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, patient_age_lower_bound=None, patient_age_upper_bound=None),):

Configuration for TrialInclusionCriteriaMatchAlgorithmAmethyst.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig(    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    largest_ga_lesion_upper_bound: Optional[float] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,    distance_from_fovea_lower_bound: float = 0.0,    distance_from_fovea_upper_bound: float = inf,    exclude_foveal_ga: bool = False,    conditions_inclusion_codes: Optional[list[str]] = None,    conditions_exclusion_codes: Optional[list[str]] = None,    procedures_exclusion_codes: Optional[list[str]] = None,):

Configuration for TrialInclusionCriteriaMatchAlgorithmBronze arguments.

Ancestors​

  • bitfount.runners.config_schemas.algorithm_schemas._TrialInclusionCriteriaMatchAlgorithmBaseArgumentsConfig

Variables​

  • static conditions_exclusion_codes : Optional[list[str]]
  • static conditions_inclusion_codes : Optional[list[str]]
  • static distance_from_fovea_lower_bound : float
  • static distance_from_fovea_upper_bound : float
  • static exclude_foveal_ga : bool
  • static procedures_exclusion_codes : Optional[list[str]]

TrialInclusionCriteriaMatchAlgorithmBronzeConfig​

class TrialInclusionCriteriaMatchAlgorithmBronzeConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmBronzeArgumentsConfig(cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, largest_ga_lesion_upper_bound=None, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, patient_age_lower_bound=None, patient_age_upper_bound=None, distance_from_fovea_lower_bound=0.0, distance_from_fovea_upper_bound=inf, exclude_foveal_ga=False, conditions_inclusion_codes=None, conditions_exclusion_codes=None, procedures_exclusion_codes=None),):

Configuration for TrialInclusionCriteriaMatchAlgorithmBronze.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig(    cnv_threshold: float = 0.5,    largest_ga_lesion_lower_bound: float = 1.26,    largest_ga_lesion_upper_bound: Optional[float] = None,    total_ga_area_lower_bound: float = 2.5,    total_ga_area_upper_bound: float = 17.5,    patient_age_lower_bound: Optional[int] = None,    patient_age_upper_bound: Optional[int] = None,    conditions_inclusion_codes: Optional[list[str]] = None,    conditions_exclusion_codes: Optional[list[str]] = None,    procedures_exclusion_codes: Optional[list[str]] = None,):

Configuration for TrialInclusionCriteriaMatchAlgorithmCharcoal arguments.

Ancestors​

  • bitfount.runners.config_schemas.algorithm_schemas._TrialInclusionCriteriaMatchAlgorithmBaseArgumentsConfig

Variables​

  • static conditions_exclusion_codes : Optional[list[str]]
  • static conditions_inclusion_codes : Optional[list[str]]
  • static procedures_exclusion_codes : Optional[list[str]]

TrialInclusionCriteriaMatchAlgorithmCharcoalConfig​

class TrialInclusionCriteriaMatchAlgorithmCharcoalConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmCharcoalArgumentsConfig(cnv_threshold=0.5, largest_ga_lesion_lower_bound=1.26, largest_ga_lesion_upper_bound=None, total_ga_area_lower_bound=2.5, total_ga_area_upper_bound=17.5, patient_age_lower_bound=None, patient_age_upper_bound=None, conditions_inclusion_codes=None, conditions_exclusion_codes=None, procedures_exclusion_codes=None),):

Configuration for TrialInclusionCriteriaMatchAlgorithmCharcoal.

Ancestors​

Variables​

  • static name : str

TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig​

class TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig():

Configuration for TrialInclusionCriteriaMatchAlgorithmJade arguments.

TrialInclusionCriteriaMatchAlgorithmJadeConfig​

class TrialInclusionCriteriaMatchAlgorithmJadeConfig(    name: str,    arguments: Optional[TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig] = TrialInclusionCriteriaMatchAlgorithmJadeArgumentsConfig(),):

Configuration for TrialInclusionCriteriaMatchAlgorithmJade.

Ancestors​

Variables​

  • static name : str