def run(self):
dataset = self.source.train_dataset()<EOL>num_samples = len(dataset)<EOL>fig, ax = plt.subplots(self.cases, self.samples+<NUM_LIT:1>)<EOL>selected_sample = np.sort(np.random.choice(num_samples, self.cases, replace=False))<EOL>for i in range(self.cases):<EOL><INDENT>raw_image, _ = dataset.get_raw(selected_sample[i])<EOL>ax[i, <NUM_LIT:0>].imshow(raw_image)<EOL>ax[i, <NUM_LIT:0>].set_title("<STR_LIT>")<EOL>for j in range(self.samples):<EOL><INDENT>augmented_image, _ = dataset[selected_sample[i]]<EOL>augmented_image = dataset.denormalize(augmented_image)<EOL>ax[i, j+<NUM_LIT:1>].imshow(augmented_image)<EOL><DEDENT><DEDENT>plt.show()<EOL>
Run the visualization