Jun 18, 2026 · Distributed Training Scalable distributed training and performance optimization in research and production is enabled by the torch.distributed backend.

CUDA 13.2 ROCm 7.2 CPU pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126

You can write new neural network layers in Python using the torch API or your favorite NumPy-based libraries such as SciPy. If you want to write your layers in C/C++, we provide a

CUDA 13.2 ROCm 7.2 CPU pip3 install torch torchvision --index-url https://download.pytorch.org/whl/cu126 旧版本 PyTorch

创建张量： torch.randn(2, 3) 创建一个 2 行 3 列的张量，填充随机数（遵循正态分布）。 device=device 和 dtype=dtype 分别指定了计算设备（CPU 或

Extending torch.func with autograd.Function Frequently Asked Questions Getting Started on Intel GPU Gradcheck mechanics HIP (ROCm) semantics Features for large-scale deployments Li

Apr 2, 2025 · 问题 1：CUDA 版本不匹配 现象：安装后 torch.cuda.is_available() 返回 False 解决： 卸载现有 CUDA： sudo apt remove cuda* （Linux） 通过 PyT

Jun 17, 2026 · You can write new neural network layers in Python using the torch API or your favorite NumPy-based libraries such as SciPy. If you want to write your layers in C/C+

torch-0.3.0.post4-cp27-cp27m-linux_x86_64.whl torch-0.3.0.post4-cp27-cp27mu-linux_x86_64.whl torch-0.3.0.post4-cp35-cp35m-linux_x86_64.whl torch-0.3.0.post4-cp36 ...

如果 torch.cuda.is_available () 输出 True，则说明 PyTorch 成功识别到你的 GPU。 一个简单的实例，构建一个随机初始化的张量：