Metadata-Version: 2.1
Name: gpuinfo
Version: 1.0.0a4
Summary: A quick access to nvidia gpu information
Home-page: UNKNOWN
Author: Zhang Tianyu
Author-email: tyz.xyz@qq.com
License: UNKNOWN
Project-URL: Source, https://github.com/FlyHighest/gpuinfo/
Description: # gpuinfo
        
        I implement some functions that can help users to obtain nvidia gpu information.
        
        To use gpuinfo, you need to be able to run 'ps' and 'nvidia-smi' in your terminal. 
        
        # Install with pip
        ```
        pip install gpuinfo
        ```  
        I only tested on linux system with python3.
        https://pypi.org/project/gpuinfo/
        
        # Usage
        
        ```python
        from gpuinfo import GPUInfo
        ```
        
        GPUInfo has the following functions:
            
            get_users(gpu_id)
                return a dict. show every user and memory on a certain gpu 
        
            check_empty()
                check_empty()
                return a list containing all GPU ids that no process is using currently.
            
            get_info()
                pid_list,percent,memory,gpu_used=get_info()
                return a dict and three lists. pid_list has pids as keys and gpu ids as values, showing which gpu the process is using
            
            get_user(pid)
                get_user(pid)
                Input a pid number , return its creator by linux command ps
            
            gpu_usage()
                gpu_usage()
                return two lists. The first list contains usage percent of every GPU. The second list contains the memory used of every GPU. The information is obtained by command 'nvidia-smi'
        
        # Example
        
        ```python
        from gpuinfo import GPUInfo
        
        available_device=GPUInfo.check_empty()
        #available_device就是一个含有所有没有任务的gpu编号的列表
        percent,memory=GPUInfo.gpu_usage()
        #获得所有gpu的使用百分比和显存占用量
        min_percent=percent.index(min([percent[i] for i in available_device]))
        #未被使用的gpu里percent最小的
        min_memory=memory.index(min([memory[i] for i in available_device]))
        #未被使用的gpu里显存占用量最少的
        
        #如果你使用pytorch
        torch.cuda.set_device(min_percent) 或者(min_memory)
        ```
        
Keywords: gpu information
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/plain
