about attack_pipeline.py

[fzpr]

Hello Dr.mirsky.
I tried implement your code for creating injector and remover models.
I used world coord for 169 sample E.g :
filename | z | x | y
LIDC-IDRI-0003/1-001.dcm | -169.6239465 | -47.40284557 | -30.171209
LIDC-IDRI-0011/1-001.dcm | -67.08815205 | -72.97101044 | 49.02652606
LIDC-IDRI-0012/1-001.dcm | -196.1703197 | 92.33199711 | 0.471155965
LIDC-IDRI-0013/1-001.dcm | -124.4263249 | -36.51308198 | -65.21501284
LIDC-IDRI-0014/1-001.dcm | -135.9209832 | 59.49693039 | -6.696593702
for creating injector model.

After completing the generator training process, the D loss, acc and G loss reach :

[Epoch 199/200] [Batch 342/347] [D loss: 0.000427, acc: 100%] [G loss: 4.560094] time: 1 day, 4:55:22.522646
[Epoch 199/200] [Batch 343/347] [D loss: 0.000721, acc: 100%] [G loss: 4.883993] time: 1 day, 4:55:24.019246
[Epoch 199/200] [Batch 344/347] [D loss: 0.000610, acc: 100%] [G loss: 5.273649] time: 1 day, 4:55:25.515293
[Epoch 199/200] [Batch 345/347] [D loss: 0.001337, acc: 100%] [G loss: 4.006495] time: 1 day, 4:55:27.011006

When using the generator model to inject into a new scan by running the 3A_inject_evidence.py , after adding noise touch ups in the attack_pipeline.py

CT-GAN/procedures/attack_pipeline.py

Line 184 in 5601ca1

print("Adding noise touch-ups...")

In output i receive these runtime warnings :

Adding noise touch-ups...
/home/Desktop/final2/env/lib/python3.8/site-packages/numpy/core/_methods.py:233: RuntimeWarning: Degrees of freedom <= 0 for slice
  ret = _var(a, axis=axis, dtype=dtype, out=out, ddof=ddof,
/home/Desktop/final2/env/lib/python3.8/site-packages/numpy/core/_methods.py:194: RuntimeWarning: invalid value encountered in true_divide
  arrmean = um.true_divide(
/home/Desktop/final2/env/lib/python3.8/site-packages/numpy/core/_methods.py:226: RuntimeWarning: invalid value encountered in double_scalars
  ret = ret.dtype.type(ret / rcount)
/home/Desktop/final2/env/lib/python3.8/site-packages/numpy/core/fromnumeric.py:3372: RuntimeWarning: Mean of empty slice.
  return _methods._mean(a, axis=axis, dtype=dtype,
/home/Desktop/final2/env/lib/python3.8/site-packages/numpy/core/_methods.py:170: RuntimeWarning: invalid value encountered in double_scalars
  ret = ret.dtype.type(ret / rcount)
touch-ups complete

And as a result of the injection process, some saved scan looks like this:

For some scans, I don't receive the runtime warnings and the injection is applied to the saved scan.
Can you help me with this?