def func_encode(sample):
x, y = sample
features = {
'val': ctf.float_feature([x]),
'label': ctf.float_feature([y])
}
return tf.train.Example(features=tf.train.Features(feature=features))
def _encode_func(sample):
patch_np = sample[0].numpy().flatten()
label_np = sample[1].numpy()
return ctfd.encode({
'patch': ctf.float_feature(patch_np),
'label': ctf.int64_feature(label_np)
})