Variables
int	batch_size = 128

int	nb_classes = 10

int	nb_epoch = 1

	img_rows

	img_cols

int	nb_filters = 4

int	nb_pool = 2

int	nb_conv = 3

	X_test = X_test.reshape(X_test.shape[0], 1, img_rows, img_cols)

	y_test

	X_train = X_train.reshape(X_train.shape[0], 1, img_rows, img_cols)

	Y_train = np_utils.to_categorical(y_train, nb_classes)

	Y_test = np_utils.to_categorical(y_test, nb_classes)

	model = Sequential()

	loss

	optimizer

	verbose

	validation_data

	overwrite

	a = X_train[0,0]

Detailed Description

Save CNN network and one sample of train data.

Run one iteration of training of convnet on the MNIST dataset.

Variable Documentation

mnist_cnn_one_iteration.a = X_train[0,0]

Definition at line 78 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.batch_size = 128

Definition at line 17 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.img_cols

Definition at line 22 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.img_rows

Definition at line 22 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.loss

Definition at line 64 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.model = Sequential()

Definition at line 47 of file mnist_cnn_one_iteration.py.

int mnist_cnn_one_iteration.nb_classes = 10

Definition at line 18 of file mnist_cnn_one_iteration.py.

int mnist_cnn_one_iteration.nb_conv = 3

Definition at line 28 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.nb_epoch = 1

Definition at line 19 of file mnist_cnn_one_iteration.py.

int mnist_cnn_one_iteration.nb_filters = 4

Definition at line 24 of file mnist_cnn_one_iteration.py.

int mnist_cnn_one_iteration.nb_pool = 2

Definition at line 26 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.optimizer

Definition at line 65 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.overwrite

Definition at line 73 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.validation_data

Definition at line 68 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.verbose

Definition at line 68 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.X_test = X_test.reshape(X_test.shape[0], 1, img_rows, img_cols)

Definition at line 31 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.X_train = X_train.reshape(X_train.shape[0], 1, img_rows, img_cols)

Definition at line 33 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.y_test

Definition at line 31 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.Y_test = np_utils.to_categorical(y_test, nb_classes)

Definition at line 45 of file mnist_cnn_one_iteration.py.

mnist_cnn_one_iteration.Y_train = np_utils.to_categorical(y_train, nb_classes)

Definition at line 44 of file mnist_cnn_one_iteration.py.