# Load entire dataset X, y = torch.load('some_training_set_with_labels.pt') # Train model for epoch in range(max_epochs): for i in range(n_batches): # Local batches and labels local_X, local_y = X[i*n_batches:(i+1)*n_batches,], y[i*n_batches:(i+1)*n_batches,] # Your model [...] # other # Unoptimized generator training_generator = SomeSingleCoreGenerator('some_training_set_with_labels.pt') # Train model for epoch in range(max_epochs): for local_X, local_y in training_generator: # Your model [...]