msd_pytorch | Pytorch implementation of the mixed-scale dense network | Machine Learning library

by ahendriksen Python Version: v0.8.0 License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | msd_pytorch Summary

msd_pytorch is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. msd_pytorch has no bugs, it has no vulnerabilities, it has build file available and it has low support. However msd_pytorch has a Non-SPDX License. You can download it from GitHub.

A Pytorch implementation of the mixed-scale dense network described in https://doi.org/10.1073/pnas.1715832114

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Quality

Security

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Support

msd_pytorch has a low active ecosystem.

It has 6 star(s) with 6 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 2 have been closed. On average issues are closed in 5 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of msd_pytorch is v0.8.0

Quality

msd_pytorch has no bugs reported.

Security

msd_pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

msd_pytorch has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

msd_pytorch releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

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msd_pytorch Key Features

No Key Features are available at this moment for msd_pytorch.

msd_pytorch Examples and Code Snippets

Mixed-scale Dense Networks for PyTorch,Cite

Python

Lines of Code : 10

License : Non-SPDX (NOASSERTION)

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@software{hendriksen-2019-msd-pytor,
  author       = {Hendriksen, Allard A.},
  title        = {ahendriksenh/msd\_pytorch: v0.7.2},
  month        = dec,
  year         = 2019,
  publisher    = {Zenodo},
  version      = {v0.7.2},
  doi          = {

Installing from source

Python

Lines of Code : 4

License : Non-SPDX (NOASSERTION)

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git clone https://github.com/ahendriksen/msd_pytorch.git
cd msd_pytorch

CC=/path/to/compatible/cpp/compiler pip install -e .[dev]

pip install -e .[dev]

Installing with Conda

Python

Lines of Code : 2

License : Non-SPDX (NOASSERTION)

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conda install msd_pytorch=0.10.1 cudatoolkit=11.1 -c aahendriksen -c pytorch -c defaults -c conda-forge
conda install msd_pytorch=0.10.1 cudatoolkit=10.2 -c aahendriksen -c pytorch -c defaults -c conda-forge

Community Discussions

Trending Discussions on msd_pytorch

Torchscripting a module with _ConvNd in forward

QUESTION

Torchscripting a module with _ConvNd in forward

Asked 2020-Mar-05 at 08:32

I am using PyTorch 1.4 and need to export a model with convolutions inside a loop in forward:

...

ANSWER

Answered 2020-Mar-04 at 17:55

You can use nn.ModuleList() in the following way.

Also, note that you can't subscript nn.ModuleList currently probably due to a bug as mentioned in issue#16123, but use the workaround as mentioned below.

Source https://stackoverflow.com/questions/60530703

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

Vulnerabilities

No vulnerabilities reported

Install msd_pytorch

It takes a few steps to setup Mixed-scale Dense Networks for PyTorch on your machine. We recommend installing Anaconda package manager for Python 3.

Support

Contributions are always welcome. Please submit pull requests against the dev branch. If you have any issues, questions, or remarks, then please open an issue on GitHub.

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