Pytorch2TensorRT | pytorch源码解析生成tensorrt引擎
kandi X-RAY | Pytorch2TensorRT Summary
kandi X-RAY | Pytorch2TensorRT Summary
Pytorch2TensorRT is a Python library. Pytorch2TensorRT has no bugs, it has no vulnerabilities and it has low support. However Pytorch2TensorRT build file is not available. You can download it from GitHub.
pytorch源码解析生成tensorrt引擎
pytorch源码解析生成tensorrt引擎
Support
Quality
Security
License
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Support
Pytorch2TensorRT has a low active ecosystem.
It has 2 star(s) with 2 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
Pytorch2TensorRT has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Pytorch2TensorRT is current.
Quality
Pytorch2TensorRT has no bugs reported.
Security
Pytorch2TensorRT has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
Pytorch2TensorRT does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
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Pytorch2TensorRT releases are not available. You will need to build from source code and install.
Pytorch2TensorRT 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.
Top functions reviewed by kandi - BETA
kandi has reviewed Pytorch2TensorRT and discovered the below as its top functions. This is intended to give you an instant insight into Pytorch2TensorRT implemented functionality, and help decide if they suit your requirements.
- Plot a graphviz graph .
- Parse a refinedet .
- Calculate the center of a layer .
- Calculate the scale layer .
- Forward the layer .
- Build a transform .
- generate scale layer
- Allocate buffer and device buffers .
- Reshapes tensor .
- draws the image
Get all kandi verified functions for this library.
Pytorch2TensorRT Key Features
No Key Features are available at this moment for Pytorch2TensorRT.
Pytorch2TensorRT Examples and Code Snippets
No Code Snippets are available at this moment for Pytorch2TensorRT.
Community Discussions
No Community Discussions are available at this moment for Pytorch2TensorRT.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Pytorch2TensorRT
You can download it from GitHub.
You can use Pytorch2TensorRT 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 Pytorch2TensorRT 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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