_2_proto_labels.py

# generating the labels for prototyped training data
sample_0_labels = np.full((10,), 0)
sample_1_labels = np.full((10,), 1)
# similarly intermediate labels can be generated
# ...
sample_9_labels = np.full((10,), 9)

# stacking the labels into a single array
proto_labels = np.concatenate((sample_0_labels,sample_1_labels,
                               sample_2_labels,sample_3_labels,
                               sample_4_labels,sample_5_labels,
                               sample_6_labels,sample_7_labels,
                               sample_8_labels,sample_9_labels),
                              axis = 0
                             )