mnist_double_cnn.py File Reference

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Namespaces
	mnist_double_cnn

Variables
int	mnist_double_cnn.batch_size = 128
int	mnist_double_cnn.num_classes = 10
int	mnist_double_cnn.epochs = 100
	mnist_double_cnn.img_rows
	mnist_double_cnn.img_cols
	mnist_double_cnn.x_test = x_test.reshape(x_test.shape[0], 1, img_rows, img_cols)
	mnist_double_cnn.y_test = keras.utils.to_categorical(y_test, num_classes)
	mnist_double_cnn.x_train = x_train.reshape(x_train.shape[0], 1, img_rows, img_cols)
tuple	mnist_double_cnn.input_shape = (1, img_rows, img_cols)
	mnist_double_cnn.y_train = keras.utils.to_categorical(y_train, num_classes)
string	mnist_double_cnn.kernel_init = 'he_uniform'
	mnist_double_cnn.model = Sequential()
	mnist_double_cnn.loss
	mnist_double_cnn.optimizer
	mnist_double_cnn.metrics
	mnist_double_cnn.verbose
	mnist_double_cnn.validation_data
	mnist_double_cnn.score = model.evaluate(x_test, y_test, verbose=0)
	mnist_double_cnn.json_string = model.to_json()