b78d0685b201fa433507a4d4e1d0a0f70a0dc783,scripts/keras_benchmarks/models/cifar10_cnn_benchmark.py,Cifar10CnnBenchmark,benchmarkCifar10Cnn,#Cifar10CnnBenchmark#Any#Any#,35

Before Change

        self._total_time = time.time() - start_time - time_callback.times[0]

        // Save model and weights
        if not os.path.isdir(save_dir):
          os.makedirs(save_dir)
        model_path = os.path.join(save_dir, model_name)
        model.save(model_path)
        print("Saved trained model at %s " % model_path)

After Change

        // initiate RMSprop optimizer
        opt = keras.optimizers.rmsprop(lr=0.0001, decay=1e-6)

        if str(keras_backend) is "tensorflow" and gpu_count > 1:
          model = multi_gpu_model(model, gpus=gpu_count)

        // Let"s train the model using RMSprop

Instances