tvm | Open deep learning compiler stack for cpu , gpu

by KnowingNothing Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | tvm Summary

tvm is a Python library. tvm has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However tvm build file is not available. You can download it from GitHub.

Open deep learning compiler stack for cpu, gpu and specialized accelerators

Support

Quality

Security

License

Reuse

Support

tvm has a low active ecosystem.

It has 3 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

tvm has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of tvm is current.

Quality

tvm has no bugs reported.

Security

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

License

tvm is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

tvm releases are not available. You will need to build from source code and install.

tvm 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.

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tvm Key Features

No Key Features are available at this moment for tvm.

tvm Examples and Code Snippets

No Code Snippets are available at this moment for tvm.

Community Discussions

No Community Discussions are available at this moment for tvm.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install tvm

You can download it from GitHub.
You can use tvm 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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