Input Encoder

The input encoder generates a sample with index idx from the PreprocessResponse object. This sample will later be fetched as input by the network. The function is called for every evaluated sample. There should be a separate encoder for each input.

The @tensorleap_input_encoder decorator registers each input encoder into the Tensorleap integration.

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

@tensorleap_input_encoder(name='image', channel_dim=-1)
def input_encoder(idx: int, preprocess: PreprocessResponse) -> np.ndarray:
    return preprocess.data.iloc[idx]['samples'].astype('float32')

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