add_prediction

code_loader.leap_binder.add_prediction

The purpose of the leap_binder.add_prediction function is to describe the prediction(s) tensors for visualization and analysis purposes. This function adds a prediction type, which later can be assigned to the model graph prediction node(s).

code_loader.leap_binder.add_prediction(
    name=str,
    labels=List[str]
    channel_dim: int = -1
)

Args
name	(str) with the given name of the input, e.g. image
labels	(List[str]) an array containing the labels associated with this prediction
channel_dim	(defaults to -1). The dimension in which the channels exists in the prediction. channel_dim should be set to 1 for channel first predictions (i.e. - C,H,W).

Examples

Basic Usage

...

LABELS = ['0','1','2','3','4','5','6','7','8','9']
leap_binder.add_prediction(
    name='predicted_digit',
    labels=LABELS
)

Full script usage can be found at Integration Script.

Guides

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

• MNIST Guide

• IMDB Guide