"rander_graphs" error

[li-zemin]

Hi,
Thanks for your code,
When I trained 3D-VAE-IWGAN, a error happened around of "rander_graphs":

Traceback (most recent call last):
File "20-VAE-3D-IWGAN.py", line 162, in
track_valid_loss) # this will only work after a 50 iterations to allows for proper averating
File "../scripts/GANutils.py", line 224, in render_graphs
plt.plot(track_d_loss_iter, smoothed_d_loss, color = 'red')
File "/usr/local/lib/python2.7/dist-packages/matplotlib/pyplot.py", line 3261, in plot
ret = ax.plot(*args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/matplotlib/init.py", line 1717, in inner
return func(ax, *args, **kwargs)
File "/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_axes.py", line 1372, in plot
for line in self._get_lines(*args, **kwargs):
File "/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_base.py", line 404, in _grab_next_args
for seg in self._plot_args(this, kwargs):
File "/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_base.py", line 384, in _plot_args
x, y = self._xy_from_xy(x, y)
File "/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_base.py", line 243, in _xy_from_xy
"have shapes {} and {}".format(x.shape, y.shape))
ValueError: x and y must have same first dimension, but have shapes (56,) and (136,)

And I printed the length of "track_d_loss_iter" and "smoothed_d_loss", the length of "track_d_loss_iter" equals to(training set number / batch_size). The length of "smoothed_d_loss" comes from the function "def savitzky_golay(y, window_size, order, deriv=0, rate=1):". I have tried my best to understand the function, however, I could not fix this bug by myself.
And, could you help me:
Thanks!

[EdwardSmith1884]

I think I may have fixed the issue, I had a bug which allowed this section of code to be called too early. Can you check if it now works for you? btw for your information savitzky_golay is just a function to give a smooth average over the loss at each iteration. You can remove this line and the training will not be affected.

[li-zemin]

Thanks for your reply,
The bug was fixed out in your code newly pushed.
And your code shared was a great help to me. I have a lot to learn from you. Looking forward to communicating with you in the field of 3D Deep Learning.
Thank you very much!