Cuda set device pytorch. Jun 2, 2023 · For interacting Pytorch tensors through CUDA, we can use the following utility functions: To demonstrate the above functions, we'll be creating a test tensor and do the following operations: Apr 7, 2025 · torch. device("cuda" if torch. There are various code examples on PyTorch Tutorials and in the documentation linked above that could help you. Typically, to do this you might have used if-statements and cuda() calls to do this: This recipe requires PyTorch 2. Jun 21, 2018 · To set the device dynamically in your code, you can use device = torch. This function is a no-op if this argument is negative. When creating a tensor, you can explicitly define which device you want it to reside on. Set the current device. 0 or later. cuda. set_device函数用于设置当前使用的cuda设备，在当拥有多个可用的GPU且能被pytorch识别的cuda设备情况下（环境变量CUDA_VISIBLE_DEVICES可以影响GPU设备到cuda设备的映射）。 Jan 22, 2025 · PyTorch supports multiple devices, primarily CPUs and CUDA-enabled GPUs. Usage of this function is discouraged in favor of device. . device or int) – selected device. device (torch. In most cases it’s better to use CUDA_VISIBLE_DEVICES environmental variable. It is common practice to write PyTorch code in a device-agnostic way, and then switch between CPU and CUDA depending on what hardware is available. is_available() else "cpu") to set cuda as your device if possible. Jul 29, 2025 · In this blog, we will explore the fundamental concepts, usage methods, common practices, and best practices related to setting the default CUDA device in PyTorch. 0. xafyhp ytktq ffrouri gcg kftpv rtis esltv ccriy ujcdbx kyfawm