pytorch-MNIST-CelebA-cGAN-cDCGAN
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znxlwm
Pytorch implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Generative Adversarial Networks (cDCGAN) for MNIST dataset
error: RuntimeError: output with shape [1, 28, 28] doesn't match the broadcast shape [3, 28, 28] MNIST has [1, 28, 28] and [3. 28. 28] two format. In this code,...
https://github.com/znxlwm/pytorch-MNIST-CelebA-cGAN-cDCGAN/blob/bc8be7888af1ea98f82af15b4e913cf6aed938e1/pytorch_MNIST_cDCGAN.py#L69 I see in so much other codes what uses only Conv2D and Sigmod, but never a Conv2D, LeakyReLU and Sigmoid.
Would much appreciate a link if so, been trying for days.
@znxlwm good job you did. And also I think the figure about the framework of cGAN and cDCGan looks very clean and beautiful, what's the software you use? thanks.
Can Anybody please help how to pass custom datasets instead of MNIST? `train_loader = torch.utils.data.DataLoader( datasets.MNIST('data', train=True, download=False, transform=transform), batch_size=batch_size, shuffle=True)`
I notice that you use "y_ = (torch.rand(mini_batch, 1) * 10).type(torch.LongTensor).squeeze()" in line 235,why not use the real y_ from input image?
Hello, Thanks for sharing your implementation of cDCGAN. I have tried implementing it for MNIST data set following the same steps you did in 'pytorch_MNIST_cDCGAN.py' with same parameter settings except...
ERROR
ValueError: Using a target size (torch.Size([128])) that is different to the input size (torch.Size([128, 6, 6])) is deprecated. Please ensure they have the same size.
There are no files named "Fixed_results", it seems that some files are missed
