tccg | Tensor Contraction Code Generator | Machine Learning library
kandi X-RAY | tccg Summary
kandi X-RAY | tccg Summary
tccg is a Python library typically used in Artificial Intelligence, Machine Learning, Pytorch applications. tccg has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
Tensor Contraction Code Generator
Tensor Contraction Code Generator
Support
Quality
Security
License
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Support
tccg has a low active ecosystem.
It has 24 star(s) with 1 fork(s). There are 4 watchers for this library.
It had no major release in the last 6 months.
tccg has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of tccg is current.
Quality
tccg has 0 bugs and 0 code smells.
Security
tccg has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
tccg code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
tccg 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.
Reuse
tccg 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, examples and code snippets are available.
It has 5379 lines of code, 197 functions and 20 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed tccg and discovered the below as its top functions. This is intended to give you an instant insight into tccg implemented functionality, and help decide if they suit your requirements.
- Generates code for the optimizer .
- Print the code to stdout .
- The main function .
- Generates a LoGBody .
- Generate testcases .
- generate code block
- Generate Eigen matrix
- Create tables .
- Generate CTF CTF .
- Splits the given indices into smaller indices .
Get all kandi verified functions for this library.
tccg Key Features
No Key Features are available at this moment for tccg.
tccg Examples and Code Snippets
No Code Snippets are available at this moment for tccg.
Community Discussions
Trending Discussions on tccg
QUESTION
Remove sequence by coordinates with Biopython
Asked 2020-Jan-29 at 13:23
Hel lo
I have a sequence such as :
...ANSWER
Answered 2020-Jan-29 at 13:20You could do this by taking the two parts you want and adding those back together:
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install tccg
Clone the repository into a desired directory and change to that location:. git clone https://github.com/HPAC/tccg.git cd tccg. python setup.py install --user.
Clone the repository into a desired directory and change to that location: git clone https://github.com/HPAC/tccg.git cd tccg
Install TCCG: python setup.py install --user
Export the TCCG_ROOT environment variable (add to your .bashrc): export TCCG_ROOT=pwd
Setup the your BLAS library within the $TCCG_ROOT/config.cfg (default: mkl).
You might have to add the installed location to your PATH environment variable: export PATH=$PATH:~/.local/bin
Please run tccg --help to get an overview of TCCG's parameters.
Clone the repository into a desired directory and change to that location: git clone https://github.com/HPAC/tccg.git cd tccg
Install TCCG: python setup.py install --user
Export the TCCG_ROOT environment variable (add to your .bashrc): export TCCG_ROOT=pwd
Setup the your BLAS library within the $TCCG_ROOT/config.cfg (default: mkl).
You might have to add the installed location to your PATH environment variable: export PATH=$PATH:~/.local/bin
Please run tccg --help to get an overview of TCCG's parameters.
Support
We are happy for any feedback or feature requests. Please contact springer@aices.rwth-aachen.de. We also welcome any contributions to the code base or the benchmark.
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