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data and can be used to augment the original dataset. Let’s generate synthetic financial data samples using the trained generator: # Generate synthetic data num_samples = 1000 noise = np.random.normal(0, 1, (num_samples, input_dim)) synthetic_data = generator.predict(noise) # Denormalize the real