Go to the source code of this file.
Namespaces | |
| mnist_cnn_one_iteration | |
Variables | |
| int | mnist_cnn_one_iteration.batch_size = 128 |
| int | mnist_cnn_one_iteration.nb_classes = 10 |
| int | mnist_cnn_one_iteration.nb_epoch = 1 |
| mnist_cnn_one_iteration.img_rows | |
| mnist_cnn_one_iteration.img_cols | |
| int | mnist_cnn_one_iteration.nb_filters = 4 |
| int | mnist_cnn_one_iteration.nb_pool = 2 |
| int | mnist_cnn_one_iteration.nb_conv = 3 |
| mnist_cnn_one_iteration.X_test = X_test.reshape(X_test.shape[0], 1, img_rows, img_cols) | |
| mnist_cnn_one_iteration.y_test | |
| mnist_cnn_one_iteration.X_train = X_train.reshape(X_train.shape[0], 1, img_rows, img_cols) | |
| mnist_cnn_one_iteration.Y_train = np_utils.to_categorical(y_train, nb_classes) | |
| mnist_cnn_one_iteration.Y_test = np_utils.to_categorical(y_test, nb_classes) | |
| mnist_cnn_one_iteration.model = Sequential() | |
| mnist_cnn_one_iteration.loss | |
| mnist_cnn_one_iteration.optimizer | |
| mnist_cnn_one_iteration.verbose | |
| mnist_cnn_one_iteration.validation_data | |
| mnist_cnn_one_iteration.overwrite | |
| mnist_cnn_one_iteration.a = X_train[0,0] | |
1.8.11
