Constant accuracy over epochs
In order to fully answer this question (specific to your case) we'd need to know what loss function you are using and how you measure accuracy.
In general, this can certainly happen for a variety of reasons.  The easiest reason to illustrate is with a simple classifier.  Suppose you have a 2-class classification problem (for simplicity) and an input $x$ and label (1, 0), i.e. the label says it belongs to class 1 and not class 2.  When you feed $x$ through your network you get an output: $y=(p_1, p_2)$.  If $p_1 > p_2$ then the prediction is correct (i.e. you chose the right class).  The loss function can continue to go down until $p_1=1$ and $p_2=0$ (the target).  So, you can have lots of correct predictions (high accuracy) but still have room to improve the output to better match the labels (room for improved loss).
I am training a gan and I am the accuracy doesn't change over epoch meanwhile the loss is deacresing.
Is there something wrong or it is normal because it's a gan?
Thank you in advance.