x_train = x_train.astype('float32') / 255. x_test = x_test.astype('float32') / 255. x_train = x_train.reshape((len(x_train), np.prod(x_train.shape[1:]))) x_test = x ...
prob_drop_input = 0.2 # drop probability for dropout @ input layer prob_drop_hidden = 0.5 # drop probability for dropout @ fc layer ...
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