一、Transformer Engine的安装 环境准备 首先,确保您的计算机已安装NVIDIA GPU,并安装了相应版本的CUDA和cuDNN。此外,您还需要安装Python和pip等必要的软件工具。 安装Transformer Engine 您可以通过pip命令安装Transformer Engine。在命令行中输入以下命令: pip install transformer-engine 这将自动下载并安装Transformer Engi...
pip show transformer-engine 如果这个命令返回了包的信息,说明包已经安装。如果返回了错误信息,说明包没有安装。 验证importlib.metadata是否能够正确找到已安装的包: 如果包已经安装,但Python还是报告找不到包,可能是importlib.metadata没有正确加载包的信息。可以尝试使用以下代码来检查: python import importlib.metadat...
# Clone repository, checkout stable branch, clone submodules git clone --branch stable --recursive https://github.com/NVIDIA/TransformerEngine.git cd TransformerEngine export NVTE_FRAMEWORK=pytorch # Optionally set framework pip install . # Build and install 错误处理: Requirements should be satisfie...
gitsubmoduleupdate--init--recursive Extra dependencies for testing can be installed by setting the “test” option: pipinstall.[test] To build the C++ extensions with debug symbols, e.g. with the-gflag: pipinstall.--global-option=--debug...
pip install -r requirements.txt #编译xFormers pip install -e . (非必须)验证安装 python -m xformers.info 一些报错及解决方法 报错:nvcc fatal : Unknown option -extended-lambda 解决方法: 提升本机cuda版本 参考环境:pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.6 ...
pip install git+https://github.com/NVIDIA/TransformerEngine.git@stable This will automatically detect if any supported deep learning frameworks are installed and build Transformer Engine support for them. To explicitly specify frameworks, set the environment variable NVTE_FRAMEWORK to a comma-separated...
pip install git+https://github.com/NVIDIA/TransformerEngine.git@stable This will automatically detect if any supported deep learning frameworks are installed and build Transformer Engine support for them. To explicitly specify frameworks, set the environment variable NVTE_FRAMEWORK to a comma-separated...
Transformer Engine in NGC Containers pip - from GitHub Additional Prerequisites Installation (stable release) Installation (development build) Getting Started Overview Let’s build a Transformer layer! Meet Transformer Engine Fused TE Modules Enabling FP8 ...
Transformer Engine とは、Transformer モデルの学習を効率的に行うためのオープンソース ライブラリで、GPU における Transformer モデルの学習効率を大幅に向上します。
pip - from GitHub Additional Prerequisites Installation (stable release) Installation (development build) Getting Started Overview Let’s build a Transformer layer! Meet Transformer Engine Fused TE Modules Enabling FP8 Python API documentation Common API Classes Format DelayedScaling Framework-specific API ...