cupy-performance | nullReports both , cpu and gpu time

by cupy Python Version: Current License: No License

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

kandi X-RAY | cupy-performance Summary

cupy-performance is a Python library. cupy-performance has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

cupy-performance

Support

Quality

Security

License

Reuse

Support

cupy-performance has a low active ecosystem.

It has 3 star(s) with 2 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of cupy-performance is current.

Quality

cupy-performance has 0 bugs and 0 code smells.

Security

cupy-performance has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

cupy-performance code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

cupy-performance 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

cupy-performance 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 are not available. Examples and code snippets are available.

It has 719 lines of code, 92 functions and 19 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed cupy-performance and discovered the below as its top functions. This is intended to give you an instant insight into cupy-performance implemented functionality, and help decide if they suit your requirements.

Compares two tests
Collects the benchmarks
Compute the comparison results for each experiment
Creates a test environment
Filter out the benchmarks
Load a module
Process a file
Run a git command
Runs the benchmark
Create key based on arguments
Generate a product of a dictionary
Run the benchmark
Initialize the experiment
Return a randomized random matrix
Collect all benchmarks from the given paths
Sanitize the dataframe
Calculate relative relative perf
Join two pandas DataFrames

Get all kandi verified functions for this library.

cupy-performance Key Features

No Key Features are available at this moment for cupy-performance.

cupy-performance Examples and Code Snippets

No Code Snippets are available at this moment for cupy-performance.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install cupy-performance

You can download it from GitHub.
You can use cupy-performance 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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