No such file or directory: 'TrainedModels/balloons/scale_factor=0.793701,alpha=100/Gs.pth' about singan

[jdc4429]

Some more information..

(base) jeff@jeff-desktop:~/SinGAN$ ./train cows.png
Random Seed: 384
GeneratorConcatSkip2CleanAdd(
(head): ConvBlock(
(conv): Conv2d(3, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
(body): Sequential(
(block1): ConvBlock(
(conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
(block2): ConvBlock(
(conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
(block3): ConvBlock(
(conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
)
(tail): Sequential(
(0): Conv2d(32, 3, kernel_size=(3, 3), stride=(1, 1))
(1): Tanh()
)
)
WDiscriminator(
(head): ConvBlock(
(conv): Conv2d(3, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
(body): Sequential(
(block1): ConvBlock(
(conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
(block2): ConvBlock(
(conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
(block3): ConvBlock(
(conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1))
(norm): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(LeakyRelu): LeakyReLU(negative_slope=0.2, inplace=True)
)
)
(tail): Conv2d(32, 1, kernel_size=(3, 3), stride=(1, 1))
)
/home/jeff/anaconda3/lib/python3.10/site-packages/torch/autograd/init.py:173: UserWarning: Error detected in ConvolutionBackward0. Traceback of forward call that caused the error:
File "/home/jeff/SinGAN/main_train.py", line 29, in
train(opt, Gs, Zs, reals, NoiseAmp)
File "/home/jeff/SinGAN/SinGAN/training.py", line 39, in train
z_curr,in_s,G_curr = train_single_scale(D_curr,G_curr,reals,Gs,Zs,in_s,NoiseAmp,opt)
File "/home/jeff/SinGAN/SinGAN/training.py", line 155, in train_single_scale
fake = netG(noise.detach(),prev)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/jeff/SinGAN/SinGAN/models.py", line 60, in forward
x = self.tail(x)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/nn/modules/container.py", line 141, in forward
input = module(input)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 447, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 443, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
(Triggered internally at ../torch/csrc/autograd/python_anomaly_mode.cpp:104.)
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
Traceback (most recent call last):
File "/home/jeff/SinGAN/main_train.py", line 29, in
train(opt, Gs, Zs, reals, NoiseAmp)
File "/home/jeff/SinGAN/SinGAN/training.py", line 39, in train
z_curr,in_s,G_curr = train_single_scale(D_curr,G_curr,reals,Gs,Zs,in_s,NoiseAmp,opt)
File "/home/jeff/SinGAN/SinGAN/training.py", line 178, in train_single_scale
errG.backward(retain_graph=True)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/_tensor.py", line 363, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph, inputs=inputs)
File "/home/jeff/anaconda3/lib/python3.10/site-packages/torch/autograd/init.py", line 173, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor [3, 32, 3, 3]] is at version 2; expected version 1 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!

[jdc4429]

When I do the training, it crashes after creating some of the files in the TrainedModels folder