Always show Test accuracy 1.0 for run_stacked_autoencoder_supervised.py

[robi56]

I just try with the file after a slight modifying for my custom data run_stacked_autoencoder_supervised.py with doc configuation

After running the code the output shows always test accuracy 1.0 . I put some wrong output label in testlabel.txt file , but at this case it also shows accuracy 1.0.

The CommandLine Output LookLike

Kingfisher:Deep-Learning-TensorFlow Nandi$ python practice/run_stacked_autoencoder_supervised.py --dae_layers 1024,784,512,256 --dae_batch_size 25 --dae_num_epochs 5 --verbose 1 --dae_corr_type masking --dae_corr_frac 0.0 --finetune_num_epochs 25 --finetune_opt momentum --momentum 0.9 --finetune_learning_rate 0.05 --dae_enc_act_func sigmoid --dae_dec_act_func sigmoid --dae_loss_func cross_entropy --finetune_act_func relu --finetune_loss_func softmax_cross_entropy --dropout 0.7 Creating /Users/Nazib/.yadlt/stored_models/sdae/ directory to save/restore models Creating /Users/Nazib/.yadlt/data/sdae/ directory to save model generated data Creating /Users/Nazib/.yadlt/logs/sdae/ directory to save tensorboard logs Creating /Users/Nazib/.yadlt/stored_models/sdae/dae-1 directory to save/restore models Creating /Users/Nazib/.yadlt/data/sdae/dae-1 directory to save model generated data Creating /Users/Nazib/.yadlt/logs/sdae/dae-1 directory to save tensorboard logs Creating /Users/Nazib/.yadlt/stored_models/sdae/dae-2 directory to save/restore models Creating /Users/Nazib/.yadlt/data/sdae/dae-2 directory to save model generated data Creating /Users/Nazib/.yadlt/logs/sdae/dae-2 directory to save tensorboard logs Creating /Users/Nazib/.yadlt/stored_models/sdae/dae-3 directory to save/restore models Creating /Users/Nazib/.yadlt/data/sdae/dae-3 directory to save model generated data Creating /Users/Nazib/.yadlt/logs/sdae/dae-3 directory to save tensorboard logs Creating /Users/Nazib/.yadlt/stored_models/sdae/dae-4 directory to save/restore models Creating /Users/Nazib/.yadlt/data/sdae/dae-4 directory to save model generated data Creating /Users/Nazib/.yadlt/logs/sdae/dae-4 directory to save tensorboard logs Training layer 1... Tensorboard logs dir for this run is /Users/Nazib/.yadlt/logs/sdae/dae-1/run5 Reconstruction loss at step 0: -8036.11 Reconstruction loss at step 1: -9851.44 Reconstruction loss at step 2: -11081.3 Reconstruction loss at step 3: -11957.8 Reconstruction loss at step 4: -12676.6 Training layer 2... Tensorboard logs dir for this run is /Users/Nazib/.yadlt/logs/sdae/dae-2/run5 Reconstruction loss at step 0: 0.659456 Reconstruction loss at step 1: 0.658065 Reconstruction loss at step 2: 0.656675 Reconstruction loss at step 3: 0.655287 Reconstruction loss at step 4: 0.653903 Training layer 3... Tensorboard logs dir for this run is /Users/Nazib/.yadlt/logs/sdae/dae-3/run5 Reconstruction loss at step 0: 0.788582 Reconstruction loss at step 1: 0.787858 Reconstruction loss at step 2: 0.787136 Reconstruction loss at step 3: 0.786414 Reconstruction loss at step 4: 0.785694 Training layer 4... Tensorboard logs dir for this run is /Users/Nazib/.yadlt/logs/sdae/dae-4/run5 Reconstruction loss at step 0: 0.743701 Reconstruction loss at step 1: 0.743354 Reconstruction loss at step 2: 0.743006 Reconstruction loss at step 3: 0.742658 Reconstruction loss at step 4: 0.742312 Tensorboard logs dir for this run is /Users/Nazib/.yadlt/logs/sdae/run5 Accuracy at step 0: 1.0 Accuracy at step 1: 1.0 Accuracy at step 2: 1.0 Accuracy at step 3: 1.0 Accuracy at step 4: 1.0 Accuracy at step 5: 1.0 Accuracy at step 6: 1.0 Accuracy at step 7: 1.0 Accuracy at step 8: 1.0 Accuracy at step 9: 1.0 Accuracy at step 10: 1.0 Accuracy at step 11: 1.0 Accuracy at step 12: 1.0 Accuracy at step 13: 1.0 Accuracy at step 14: 1.0 Accuracy at step 15: 1.0 Accuracy at step 16: 1.0 Accuracy at step 17: 1.0 Accuracy at step 18: 1.0 Accuracy at step 19: 1.0 Accuracy at step 20: 1.0 Accuracy at step 21: 1.0 Accuracy at step 22: 1.0 Accuracy at step 23: 1.0 Accuracy at step 24: 1.0 Test set accuracy: 1.0

I have create a folder Named Data1 and keep my data testdata.txt testlabel.txt traindata.txt trainlabel.txt

The modified code I use here run_stacked_autoencoder_supervised.txt

[siucaan]

I meet the same issue while run the "run_rbm.py". Could anybody give me a hand?