stouputils.data_science.config.set module

Configuration file for the project.

class DataScienceConfig

Bases: object

Configuration class for the project.

SEED: int = 42

Seed for the random number generator.

ERROR_LOG: LogLevels = 2

Log level for errors for all functions.

AUGMENTED_FILE_SUFFIX: str = '_aug_'

Suffix for augmented files, e.g. ‘image_008_aug_1.png’.

AUGMENTED_DIRECTORY_PREFIX: str = 'aug_'

Prefix for augmented directories, e.g. ‘data/hip_implant’ -> ‘data/aug_hip_implant’.

PREPROCESSED_DIRECTORY_SUFFIX: str = '_preprocessed'

Suffix for preprocessed directories, e.g. ‘data/hip_implant’ -> ‘data/hip_implant_preprocessed’.

ROOT: str = '/home/runner/work/stouputils/stouputils'

Root directory of the project.

MLFLOW_FOLDER: str = '/home/runner/work/stouputils/stouputils/mlruns'

Folder containing the mlflow data.

MLFLOW_URI: str = 'file:///home/runner/work/stouputils/stouputils/mlruns'

URI to the mlflow data.

DATA_FOLDER: str = '/home/runner/work/stouputils/stouputils/data'

Folder containing all the data (e.g. subfolders containing images).

TEMP_FOLDER: str = '/home/runner/work/stouputils/stouputils/temp'

Folder containing temporary files (e.g. models checkpoints, plots, etc.).

LOGS_FOLDER: str = '/home/runner/work/stouputils/stouputils/logs'

Folder containing the logs.

TENSORBOARD_FOLDER: str = '/home/runner/work/stouputils/stouputils/tensorboard'

Folder containing the tensorboard logs.

TEST_SIZE: float = 0.2

Size of the test set by default (0.2 means 80% training, 20% test).

VALIDATION_SIZE: float = 0.2

Size of the validation set by default (0.2 means 80% training, 20% validation).

SAVE_MODEL: bool = False

If the model should be saved in the mlflow folder using mlflow.*.save_model.

DO_SALIENCY_AND_GRADCAM: bool = True

If the saliency and gradcam should be done during the run.

DO_LEARNING_RATE_FINDER: Literal[0, 1, 2] = 1

If the learning rate finder should be done during the run. 0: no, 1: only plot, 2: plot and use value for the remaining run

DO_UNFREEZE_FINDER: Literal[0, 1, 2] = 0

If the unfreeze finder should be done during the run. 0: no, 1: only plot, 2: plot and use value for the remaining run

DO_FIT_IN_SUBPROCESS: bool = True

If the model should be fitted in a subprocess. Is memory efficient, and more stable. Turn it off only if you are having issues.

Note: This allow a program to make lots of runs without getting killed by the OS for using too much resources. (e.g. LeaveOneOut Cross Validation, Grid Search, etc.)

MIXED_PRECISION_POLICY: Literal['mixed_float16', 'mixed_bfloat16', 'float32'] = 'mixed_float16'

Mixed precision policy to use. Turn back to “float32” if you are having issues with a specific model or metrics. See: https://www.tensorflow.org/guide/mixed_precision

TENSORFLOW_DEVICE: str = '/gpu:1'

TensorFlow device to use.