Comments (4)
By the way, when i run the code under tensorflow 0.9, the loss and accuracy stay the same after every iteration.
the result is like this:
Iteration: 119 Loss: 230.362 Train Accuracy: 9.42857 Test Accuracy: 12.6263
I also tried to run under tensorflow 0.10, the loss will change a little bit, but could almost be ignored.
from dynamic-tensorflow-tutorial.
@wenyong-h Your loss is not moving because you are not getting any gradient. Please check the terminal when you run the jupyter notebook. Is there any error?
from dynamic-tensorflow-tutorial.
@KnHuq i'm running the python file, not the ipython notebook. There was no error.
I tried using AdamOptimizer
instead of AdadeltaOptimizer
, then everything is right.
this is the result of one run of the Vanilla RNN
Iteration: 119 Loss: 46.1185 Train Accuracy: 99.6429 Test Accuracy: 94.697
from dynamic-tensorflow-tutorial.
@wenyong-h You are right! One transpose will do the same thing!
from dynamic-tensorflow-tutorial.
Related Issues (7)
- Can you explain why batch_input size ? HOT 2
- what is the difference between your dynamic implemetion of rnn and tf.nn.dynamic_rnn function ? HOT 3
- AttributeError: 'module' object has not attribute 'scan' HOT 1
- Please help with Neural Stack Machine HOT 1
- Run your repo in tensorflow 1.1.0 HOT 1
- Can not run your repo in tensorflow 1.3.0 HOT 1
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from dynamic-tensorflow-tutorial.