PyTorch-GAN | PyTorch implementations of Generative Adversarial Networks | Machine Learning library
kandi X-RAY | PyTorch-GAN Summary
kandi X-RAY | PyTorch-GAN Summary
PyTorch implementations of Generative Adversarial Networks.
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Top functions reviewed by kandi - BETA
- Download the dataset
- Check if the folder exists
- Compute the loss
- Performs the forward computation
- Forward the model to the MLP prediction
- Assign the adain parameters to the model
- Compute the mean and log variance of an image
- Reparameterization
- Push a new element onto the stack
- Save a batch of samples
- Forward the model for the model
- Apply random mask to images
- Sample an image
- Compute the gradient of the loss function
- Calculate pullaway loss
- Calculate the loss of the boundary of the boundary
- Convert y to a categorical tensor
- Denormalize a tensor
- Sample images
- Samples noise in latent space
- Reparameterization function
- Compute the KL loss
- Calculate the gradient of the gradient
PyTorch-GAN Key Features
PyTorch-GAN Examples and Code Snippets
Lines of Code : 7
License : No License
Copy$ git clone https://github.com/ikr7/wandb-pytorch-gan-mnist-demo.git
$ cd wandb-pytorch-gan-mnist-demo
$ pip install -r requirements.txt
$ wandb login
$ cp params.yaml.template params.yaml
(edit params.yaml)
$ python src/train.py --params params. python dcgan.py
python dcgan.py --resume_generator path/to/your-generator-model.pth --resume_discriminator path/to/your-discriminator-model.pth
Community Discussions
Trending Discussions on PyTorch-GAN
QUESTION
Hi I'm looking this GAN implementation code. code here
My question is generator class has no input parameter when defining class Generator(#38 from the link) But when training, generator gets input z(#141 from the link). I looked into the nn.Module class which is parent of class Generator but I can't find input parameter for noise z. Can anyone help?
...ANSWER
Answered 2022-Apr-05 at 08:33Consider every quoted line (38, 88 and 141):
- On line 38 is a definition of class, by putting
nn.Modulein brackets it's declaring inheritance ofclass Generatorfrom class nn.Module (which is common way to define your own neural network). - On line 88 instance of class Generator is created -- for parameters it needs all what's inside brackets of
__init__(line 39), besidesself, that's why brackets on line 88 is empty. - And on line 141 there is a calling of
genearator, behavior here defined by methodforward(line 58) and there is one parameter to be passed --z.
Again, line 88 creates an instance, line 141 calls forward method of an instance.
QUESTION
I was reading the code for Generative Adversarial Nets Code by https://github.com/eriklindernoren/PyTorch-GAN/blob/master/implementations/gan/gan.py, I would like to know what the * sign means here, I searched on Google and Stackoverflow but could not find a clear explanation.
...ANSWER
Answered 2021-Mar-24 at 12:10*x is iterable unpacking notation in Python. See this related answer.
def block returns a list of layers, and *block(...) unpacks the returned list into positional arguments to the nn.Sequential call.
Here's a simpler example:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
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Install PyTorch-GAN
You can use PyTorch-GAN like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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