87ff637109458f019eb574c798fcf28fc244f735,snntoolbox/model_libs/keras_input_lib.py,,evaluate,#Any#Any#Any#Any#,247

Before Change

        for i in range(batches):
            // Get samples from Keras.ImageDataGenerator
            x_batch, y_batch = dataflow.next()
            if True:  // Only for imagenet!
                print("Preprocessing input for ImageNet")
                x_batch = np.add(np.multiply(x_batch, 2. / 255.), - 1.).astype(
                    "float32")
            loss, acc = val_fn(x_batch, y_batch, verbose=0)
            score[0] += loss
            score[1] += acc
        score[0] /= batches

After Change

    (``Keras.ImageDataGenerator.flow_from_directory`` object).
    

    num_to_test = len(x_test) if x_test is not None else settings["num_to_test"]
    print("Using {} samples to evaluate input model.".format(num_to_test))

    if x_test is not None:
        score = val_fn(x_test, y_test, verbose=0)

Instances