FastGAN-pytorch | Official implementation of the paper `` Towards Faster | Machine Learning library
kandi X-RAY | FastGAN-pytorch Summary
kandi X-RAY | FastGAN-pytorch Summary
FastGAN-pytorch is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Generative adversarial networks applications. FastGAN-pytorch has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.
The code is structured as follows:.
The code is structured as follows:.
Support
Quality
Security
License
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Support
FastGAN-pytorch has a low active ecosystem.
It has 499 star(s) with 90 fork(s). There are 10 watchers for this library.
It had no major release in the last 6 months.
There are 13 open issues and 36 have been closed. On average issues are closed in 22 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of FastGAN-pytorch is current.
Quality
FastGAN-pytorch has 0 bugs and 0 code smells.
Security
FastGAN-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
FastGAN-pytorch code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
FastGAN-pytorch is licensed under the GPL-3.0 License. This license is Strong Copyleft.
Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
Reuse
FastGAN-pytorch releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
It has 2562 lines of code, 181 functions and 19 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed FastGAN-pytorch and discovered the below as its top functions. This is intended to give you an instant insight into FastGAN-pytorch implemented functionality, and help decide if they suit your requirements.
- Train model
- Train the image
- Augment x with a given policy
- Get a directory of the training results
- Generate a video from selected locations
- Interpolate an arbitrary tween
- Batch function for batch_generate
- Generate image using stylegan2
- Convert a tensor lab to RGB
- Convert image to tensor
- Convert a tensor to a lab
- Convert a tensor image into an image
- Batch and save images
- Calculate feature features
- Save the network to disk
- Optimizes parameters
- Load inception v3 feature
- Calculate the early features
- Upsample block
- Extract feature from given generator function
- Create a block of convolutional block
- Concatenate image
- Find the closest image to the given image
- Extract features from inception
- Calculate the FID of a feature
- Interpolate an ellipsoid and z2
Get all kandi verified functions for this library.
FastGAN-pytorch Key Features
No Key Features are available at this moment for FastGAN-pytorch.
FastGAN-pytorch Examples and Code Snippets
No Code Snippets are available at this moment for FastGAN-pytorch.
Community Discussions
Trending Discussions on FastGAN-pytorch
QUESTION
FastGAN - RuntimeError: Error(s) in loading state_dict for Generator
Asked 2021-Oct-19 at 01:37
I'm running FastGAN (https://github.com/odegeasslbc/FastGAN-pytorch) on Google Colab and now trying to resume training from a saved .pth generated by the network. However, it keeps throwing this error:
...ANSWER
Answered 2021-Oct-07 at 10:30This is common when changing the attribute name of the submodules in your nn.Module.
Notice how most of your layer keys here differ from the ones contained in the loaded state dict because of their prefix: all keys in the dictionary have a 'module.' prefix.
A quick fix you be to slice away this prefix. You could for instance usea dict comprehension:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install FastGAN-pytorch
You can download it from GitHub.
You can use FastGAN-pytorch 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.
You can use FastGAN-pytorch 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.
Support
For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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