SGAN | Stacked Generative Adversarial Networks | Machine Learning library

 by   xunhuang1995 Python Version: Current License: No License

kandi X-RAY | SGAN Summary

kandi X-RAY | SGAN Summary

SGAN is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Generative adversarial networks applications. SGAN has no bugs, it has no vulnerabilities and it has low support. However SGAN build file is not available. You can download it from GitHub.

Stacked Generative Adversarial Networks
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              SGAN has a low active ecosystem.
              It has 241 star(s) with 53 fork(s). There are 12 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 0 open issues and 1 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of SGAN is current.

            kandi-Quality Quality

              SGAN has 0 bugs and 49 code smells.

            kandi-Security Security

              SGAN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              SGAN code analysis shows 0 unresolved vulnerabilities.
              There are 2 security hotspots that need review.

            kandi-License License

              SGAN does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
              OutlinedDot
              Without a license, all rights are reserved, and you cannot use the library in your applications.

            kandi-Reuse Reuse

              SGAN releases are not available. You will need to build from source code and install.
              SGAN has no build file. You will be need to create the build yourself to build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              SGAN saves you 671 person hours of effort in developing the same functionality from scratch.
              It has 1556 lines of code, 18 functions and 8 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed SGAN and discovered the below as its top functions. This is intended to give you an instant insight into SGAN implemented functionality, and help decide if they suit your requirements.
            • Load the cifar data .
            • Perform Adam conditional update .
            • Calculate Adam updates .
            • Download and extract the CIFAR - 10 dataset .
            • Batch norm layer .
            • Calculate the output for a given shape .
            • Unpickle a file
            • Compute the log of the log of x along axis .
            • r Compute relu .
            • Returns the output shape for the given input shape .
            Get all kandi verified functions for this library.

            SGAN Key Features

            No Key Features are available at this moment for SGAN.

            SGAN Examples and Code Snippets

            No Code Snippets are available at this moment for SGAN.

            Community Discussions

            QUESTION

            How to implement fractionally strided convolution layers in pytorch?
            Asked 2021-Feb-20 at 10:51

            Before everything, I searched google and StackOverflow but I do not find any similar questions so here I propose a new one.

            I'm interested in this paper and want to implement this SGAN for my project. The paper mentioned that its generator network is composed of "a stack of fractionally strided convolution layers", I found two different ways of implementing this in pytorch, one is:

            ...

            ANSWER

            Answered 2021-Feb-20 at 10:51

            tldr; There are some shape constraints but both perform the same operations.

            The output shape of nn.ConvTranspose2d is given by y = (x − 1)s - 2p + d(k-1) + p_out + 1, where x and y are the input and ouput shape, respectively, k is the kernel size, s the stride, d the dilation, p and p_out the padding and padding out. Here we keep things simple with s=1, p=0, p_out=0, d=1.

            Therefore, the output shape of the transposed convolution is:

            Source https://stackoverflow.com/questions/66287552

            QUESTION

            Replicate Creating Dynamic Controls on Create/ EDIT Pages
            Asked 2020-Sep-05 at 14:19

            I want to display a List of File Attachments (filename only), the ability to Add new Attachments on the CREATE page works perfectly fine. I use the code from here See Screenshot below..

            ...

            ANSWER

            Answered 2020-Sep-05 at 14:19

            In your current jquery code new row was appending inside controls first div i.e : div:first because as you look at your html structure i.e :

            Source https://stackoverflow.com/questions/63745890

            QUESTION

            I keep getting an Assertion Error with StyleGAN
            Asked 2020-Jan-08 at 22:27

            Recently I have been playing around with StyleGAN and I have generated a dataset but I get the following when I try to run train.py.

            ...

            ANSWER

            Answered 2020-Jan-08 at 21:50

            As answered by @Chrispresso in the comments of this question, the directory that I was referencing in the following line was invalid and had to set it to a valid directory.

            Source https://stackoverflow.com/questions/59654172

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install SGAN

            You can download it from GitHub.
            You can use SGAN 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

            If you have any questions about the code, feel free to email me (xh258@cornell.edu).
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            CLONE
          • HTTPS

            https://github.com/xunhuang1995/SGAN.git

          • CLI

            gh repo clone xunhuang1995/SGAN

          • sshUrl

            git@github.com:xunhuang1995/SGAN.git

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