OpenShift Container Platform 4.4 构建（build） 在 OpenShift Container Platform 中执行构建并与之交互 Last Updated: 2021-03-11 OpenShift Container Platform 4.4 构建（build） 在 OpenShift Container Platform 中执行构建并与之交互 . . . . . . . . . . . . . . . . . . . . . . . . . 目 目录 录 第 第 1 章 章 理解 理解镜 镜像 像构 构建 建 1.1. 构建（BUILD） 第 第 2 章 章 了解 了解构 构建配置 建配置 2.1. BUILDCONFIG 第 第 3 章 章 创 创建 建构 构建 建输 输入 入 3.1. 构建输入 3.2. DOCKERFILE 87 87 87 88 88 89 93 OpenShift Container Platform 4.4 构 构建（ 建（build） ） 2 目 目录 录 3 第 1 章 理解镜像构建 1.1. 构建（BUILD） 构建 (build)是将输入参数转换为结果对象的过程。此过程最常用于将输入参数或源代码转换为可运行的镜 像。BuildConfig 对象是整个构建过程的定义。

Using Istio to Build the Next 5G Platform David Lenrow Open Source Service Mesh Evangelist Neeraj Poddar Co-founder & Chief Architect, Aspen Mesh February 22, 2021 2 ©2021 Aspen Mesh. All rights reserved Observability, Debugging Uniform metrics and tracing for all CNF traffic Enforcement Primitives to Build Zero Trust Strong identity for users, workloads, devices, etc. Encrypting inter-CNF traffic via

pyflink-docs Release release-1.15 PyFlink Nov 23, 2022 CONTENTS 1 How to build docs locally 3 1.1 Getting Started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . pyflink-docs, Release release-1.15 PyFlink is a Python API for Apache Flink that allows you to build scalable batch and streaming workloads, such as real-time data processing pipelines, large-scale exploratory HOW TO BUILD DOCS LOCALLY 1. Install dependency requirements python3 -m pip install -r dev/requirements.txt 2. Conda install pandoc conda install pandoc 3. Build the docs python3 setup.py build_sphinx

pyflink-docs Release release-1.16 PyFlink Nov 23, 2022 CONTENTS 1 How to build docs locally 3 1.1 Getting Started . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . pyflink-docs, Release release-1.16 PyFlink is a Python API for Apache Flink that allows you to build scalable batch and streaming workloads, such as real-time data processing pipelines, large-scale exploratory HOW TO BUILD DOCS LOCALLY 1. Install dependency requirements python3 -m pip install -r dev/requirements.txt 2. Conda install pandoc conda install pandoc 3. Build the docs python3 setup.py build_sphinx

choose download based on your OS. Create a new conda environment Launch anaconda prompt, this will open base Anaconda environment. Let us create a new conda environment. This process is similar to virtualenv command in your conda terminal: conda create --name PythonCPU If you want, you can create and install modules using GPU also. In this tutorial, we follow CPU instructions. Activate conda environment is an IDE for executing python applications. Let us install this IDE in our conda environment using the below command: conda install spyder Install python libraries We have already known the python

depend on Conda-specific packages, which might not be available on PyPI, we recommend building these packages from source. A workaround is to manually install a Conda package manager, and add the conda path PYTHONPATH for example, using export PYTHONPATH="/opt/conda/lib/python3.8/site-packages" if your Conda package manager was installed in /opt/conda. NVIDIA PyTorch Container Versions The following table depend on Conda-specific packages, which might not be available on PyPI, we recommend building these packages from source. A workaround is to manually install a Conda package manager, and add the conda path

我们建议您安装最新版本的 transformers 库，或者至少安装 4.37.0 版本。 1.1.1 Pip 安装 pip install transformers -U 1.1.2 Conda 安装 conda install conda-forge::transformers 1.1.3 从源码安装 pip install git+https://github.com/huggingface/transformers ，或者在 Windows 子系统 Linux（WSL）上运行 start_wsl.bat 。另外，你也可以选择手动在 conda 环境中安装所需的依赖项。这 里以 MacOS 系统为例进行实践操作。 conda create -n textgen python=3.11 conda activate textgen pip install torch torchvision torchaudio 根据 LLaMA-Factory 官方指引构建好你的环境 2. 安装下列代码库（可选）： pip install deepspeed pip install flash-attn --no-build-isolation 3. 如你使用 FlashAttention-2 ，请确保你的 CUDA 版本在 11.6 以上。 准备数据 LLaMA-Factory 在 data 文件夹中提供了多

have a limited internet bandwidth, then installing pandas with Miniconda may be a better solution. Conda is the package manager that the Anaconda distribution is built upon. It is a package manager that create a minimal self contained Python installation, and then use the Conda command to install additional packages. First you will need Conda to be installed and downloading and running the Miniconda will do do this for you. The installer can be found here The next step is to create a new conda environment. A conda environment is like a virtualenv that allows you to specify a specific version of Python and

pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 380 3.4.2 How to build the pandas documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381 3.4.2.1 Requirements json_normalize . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1206 34.1.5.3 pandas.io.json.build_table_schema . . . . . . . . . . . . . . . . . . . . . . . . . . 1207 34.1.6 HTML . . . . . . . pandas has split off Google BigQuery support into a separate package pandas-gbq. You can conda install pandas-gbq -c conda-forge or pip install pandas-gbq to get it. The functional- ity of read_gbq() and DataFrame

Chang Pranay Manocha Installing PyTorch • ???????????? On your own computer • Anaconda/Miniconda: conda install pytorch -c pytorch • Others via pip: pip3 install torch • ???????????? On Princeton CS server Miniconda is installed: conda install pytorch -c pytorch Writing code • Up to you; feel free to use emacs, vim, PyCharm, etc. if you want. • Our recommendations: • Install: conda/pip3 install jupyter • again... Misc • Alternative : Static Computation Graphs: Alternative: Static graphs Step 1: Build computational graph describing our computation (including finding paths for backprop) Step 2: