Hello, when the code runs, the memory is full. What happened? My python version is 3.6, tensorflow version is 1.11, my GPU is 1080ti, thanks! the error is as follow: An error ocurred while starting the kernel 2019󈚥󈚦 08:40:45.229298: I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 2019󈚥󈚦 08:40:45.601632: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1411] Found device 0 with properties: name: GeForce GTX 1080 Ti major: 6 minor: 1 memoryClockRate(GHz): 1.582 pciBusID: 0000:65:00.0 totalMemory: 11.00GiB freeMemory: 9.10GiB 2019󈚥󈚦 08:40:45.603929: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1490] Adding visible gpu devices: 0 2019󈚥󈚦 08:40:46.556261: I tensorflow/core/common_runtime/gpu/gpu_device.cc:971] Device interconnect StreamExecutor with strength 1 edge matrix: 2019󈚥󈚦 08:40:46.558110: I tensorflow/core/common_runtime/gpu/gpu_device.cc:977] 0 2019󈚥󈚦 08:40:46.558407: I tensorflow/core/common_runtime/gpu/gpu_device.cc:990] 0: N 2019󈚥󈚦 08:40:46.558836: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1103] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 8789 MB memory) ‑> physical GPU (device: 0, name: GeForce GTX 1080 Ti, pci bus id: 0000:65:00.0, compute capability: 6.1)

Hello,can your code only generate 64×64 images? Can I generate an image of the specified size? For example: 256 × 256, if you can, what parameters need to be modified?thank you!

I have updated the code from TensorFlow 2.0-alpha to TensorFlow 2.0, everything works well except for WGAN-GP (it works in tf2.0-alpha). In tf2.0, The gradient penalty seems very unstable, but I cannot find out the problem. Does anybody help? I will be grateful.

Hi!

cartoon faces original size is [96, 96, 3],the number 3 means 3 channel RGB data. But if I have grayscale data with 3 slices, i.e the size is [121,145,3], Can I simply use this code? If not, what should I change based on this code?

Thanks for your work! Look forward to your response.

c_iter is defined but not used in all of the WGAN files. What is the correct behaviour? i.e should the critic be optimised heavily initially or not?

Also, can you confirm that you use a learning rate parameter of 0.0002, regardless of whether RMSProp or Adam is used as the optimiser?

i use the code whitch be used to train cartoon pictures with WGAN-GP. i don't know what the mean of n_critic = 5 , and why do you to set it. thanks.

I am getting this error while running train.py TypeError: Input 'filename' of 'ReadFile' Op has type float32 that does not match expected type of string. Please help with this. Thanks in advance

Hello, I am confused about how do you freeze the gradient descent to the other model. When training d_step, I suppose the generator should be freezed, as f_logit is based on generator and used in d_loss; similarly, when training g_step, I suppose the discriminator should be freezed, as f_logit depens on discriminator.

However, I do not see where you stop those gradients flowing to the unwanted part, either generator or discriminator. Would you please provide some hints for me? Thank you.

Have you compared the difference between the network structure of DCGAN and the structure of Resnet in WGAN-GP?Is the effect of Resnet will be better than the structure of DCGAN.

do you meet the program stop without mistakes when the code running for some time ,and the GPU stops work.I changed the value of num_threads。（from 16 to 10）。i run it again.i don't know Is it because the value is too high。

Hi Zhenliang He, I wonder whether you would be willing to please license this code under an open source license? If so please add a license, or if not please just close this request. Thanks, Connelly

Hi, - Your work is really interesting. But I have found there is a problem for your DCGAN that I didn't understand. You generate noise twice when train discriminator and generator for each iteration, like the blue lines in the following picture. In soumith code (includes some official DCGAN code), he only generate noise once: https://github.com/soumith/dcgan.torch. Could you please tell me the reason?

Traceback (most recent call last): File "D:/github/DCGAN-LSGAN-WGAN-GP-DRAGAN-Tensorflow-2-master/DCGAN-LSGAN-WGAN-GP-DRAGAN-Tensorflow-2-master/train.py", line 91, in G = module.ConvGenerator(input_shape=(1, 1, args.z_dim), output_channels=shape[-1], n_upsamplings=n_G_upsamplings, name='G_%s' % args.dataset) NameError: name 'shape' is not defined please tell me why