Produces an out-of-range result for MNIST

[cliffbdf]

Produces an out-of-range result (reconstruction loss) for MNIST.

Here is the console output:

[vagrant@machinelearning DeepAutoencoder-TensorFlow]$ make run python ../Reference/Deep-Learning-TensorFlow/cmd_line/boltzmann/run_deep_autoencoder.py
--dataset mnist
--cifar_dir ../Reference/Datasets/MNIST/mnist.pkl
--main_dir deep-autoencoder
--model_name deeper-is-better
--rbm_layers 1000,500,250,100,30
--rbm_batch_size 128
--finetune_batch_size 128
--finetune_loss_func cross_entropy
--verbose 1 Extracting MNIST_data/train-images-idx3-ubyte.gz Extracting MNIST_data/train-labels-idx1-ubyte.gz Extracting MNIST_data/t10k-images-idx3-ubyte.gz Extracting MNIST_data/t10k-labels-idx1-ubyte.gz Training layer 1... 2017-11-09 02:43:59.295164: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 2017-11-09 02:43:59.317348: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 2017-11-09 02:43:59.317387: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. Tensorboard logs dir for this run is /home/vagrant/.yadlt/logs/run6 Reconstruction loss: nan: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [08:26<00:00, 50.62s/it] Training layer 2... Tensorboard logs dir for this run is /home/vagrant/.yadlt/logs/run7 Reconstruction loss: nan: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [06:20<00:00, 38.10s/it] Training layer 3... Tensorboard logs dir for this run is /home/vagrant/.yadlt/logs/run8 Reconstruction loss: nan: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [01:25<00:00, 8.56s/it] Training layer 4... Tensorboard logs dir for this run is /home/vagrant/.yadlt/logs/run9 Reconstruction loss: nan: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:25<00:00, 2.55s/it] Training layer 5... Tensorboard logs dir for this run is /home/vagrant/.yadlt/logs/run10 Reconstruction loss: nan: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:08<00:00, 1.14it/s] Tensorboard logs dir for this run is /home/vagrant/.yadlt/logs/run11 Reconstruction loss: nan: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [17:52<00:00, 107.29s/it] Test set reconstruction loss: nan [vagrant@machinelearning DeepAutoencoder-TensorFlow]$