tensorflow-mnist-cnn
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hwalsuklee
MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.
Thanks for your code! And I have some questions, glad for your help. With the Ubuntu 18.04 and the tensorflow 0.12.0, when I run `python mnist_cnn_test.py --model-dir model/model01_99.61 --batch-size 5000...
I ran `python mnist_cnn_train.py` in terminal and the terminal returned ``` Optimization` Finished! test accuracy for the stored model: 0.9932 ``` Training logs are saved in "logs/train" , however, there...
Hello, Going through the code of your project, I think the parameter `is_training` is not taken into account for the CNN model in file `mnist_cnn_train.py`. I've seen that the `cnn_model.CNN`...
tf.scalar_summary is deprecated since tensorflow 1.0, so I migrate it to tf.summary.scalar to support lastest tensorflow.
When the model is created "y = cnn_model.CNN(x) ", the is_training variable is not passed. Thus in the testing section when performing y_final = sess.run(y, feed_dict={x: batch_xs, y_: batch_ys, is_training:...
I use this code on my own data. I restore model(saver.restore(sess, myModelPath)),and then test. if I set test batch size is 1,the result will be [ 0. 0. 0. 0....
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MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.