这个包添加了对CUDA张量类型的支持,它实现了与CPU张量同样的功能,但是它使用GPU进计算。 CUDA semantics 中写了对CUDA 工作机制的更多细节 先介绍关于cuda的几个基本的函数: 1、torch.cuda.current_device() [SOURCE] 返回当前选择的设备的索引 2、torch.cuda.current_stream
torch.cuda.get_device_capability(device=None)# device (torch.device or int, optional) – device for which to return the device# capability. This function is a no-op if this argument is a negative integer.# It uses the current device, given by current_device(), if device is# None (def...
torch.cuda.current_stream(device=None) torch.cuda.default_stream(device=None) class torch.cuda.device(device) torch.cuda.device_count() class torch.cuda.device_of(obj) torch.cuda.empty_cache() torch.cuda.get_device_capability(device=None) torch.cuda.get_device_name(device=None) torch.cuda.i...
torch.cuda.get_device_capability(device=None)[source] 获取设备的cuda功能。 参数 device (torch.device or int, optional)– 用于返回设备功能的设备。如果这个参数是一个负整数,那么这个函数就是no-op。如果设备为None(默认),则使用current_device()提供的当前设备。
Check cuda - torch.cuda.get_device_capability … 29ffaa2 Collaborator tautomer commented Sep 13, 2024 • edited I had to use HIPPYNN_USE_CUSTOM_KERNEL=false to compile the docs. I initially added this in my PR as well, but I deleted it at the end. Actually, the cupy part also...
Summary: Mirror get_device_capability on MTIA per https://fburl.com/gdoc/p4lo5avn At the moment, both the major and minor version are just 0 Test Plan: Unit test: buck2 test //mtia/host_runtime/tor...
首先,你需要确定你的GPU所支持的CUDA计算能力。这可以通过运行以下Python代码来获取: python import torch print(torch.cuda.get_device_capability()) 该命令将返回一个元组,例如(8, 9),表示你的GPU支持CUDA架构8.9。 2. 打开终端或命令行界面 确保你已经打开了终端或命令行界面,以便输入环境变量设置命令。 3....
Uses the current device, given by current_device(), if device is None (default). Returns: the major and minor cuda capability of the device Return type: tuple(int, int)torch.cuda.get_device_name(device)[source] Gets the name of a device. Parameters: device (torch.device or int, ...
Default: if None, uses the current device for the default tensor type (see torch.set_default_tensor_type()). device will be the CPU for CPU tensor types and the current CUDA device for CUDA tensor types. Example: 代码语言:javascript 代码运行次数:0 运行 AI代码解释 复制 >>> a = numpy...
在安装YOLO v3之前要先检查已经安装的系统组件,Jetson Nano的OS镜像已经自带了JetPack,cuda,cudnn,opencv等都已经安装好,我们要分别检查一下环境。 2、检查CUDA Jetson-nano中已经安装了CUDA10.0版本,但必须先将路径加入到环境变量中。 sudo vim ~/.bashrc 1. 在最后添加: export CUDA_HOME=/usr/local/cuda-10.0...