Ground Truth Encoder

The ground truth encoder generates a ground truth value correlated with a sample, with index idx, from the preprocess. It will later be used as the ground truth for the loss function. This function is called for each evaluated sample.

For example:

from code_loader.contract.datasetclasses import PreprocessResponse
from code_loader.inner_leap_binder.leapbinder_decorators import tensorleap_gt_encoder

@tensorleap_gt_encoder(name='classes')
def gt_encoder(idx: int, preprocess: Union[PreprocessResponse, list]) -> np.ndarray:
    return preprocess.data.iloc[idx]['ground_truth'].astype('float32')

The @tensorleap_gt_encoder decorator registers each gt encoder into the Tensorleap integration.

Usage within the full script can be found at the Dataset Script.

Guides

Full examples can be found at the Dataset Integration section of the following guides:

• MNIST Guide

• IMDB Guide