mnist_cnn_pool.py File Reference

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Namespaces
	mnist_cnn_pool

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