OpenSAP_ml2_Week_1_InstallationGuide_Anaconda Open SAP Ml2 Week 1 Installation Guide Anaconda
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openSAP Enterprise Deep Learning with TensorFlow Installation Guide Anaconda, TensorFlow, Jupyter Notebooks Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. openSAP INSTALLATION GUIDE Introduction In this course, we offer hands-on exercises as an optional element. These exercises are not essential to complete the course successfully and pass the final exam. We will be using Jupyter notebooks, Python, and TensorFlow extensively throughout the course. All code examples from the course are made available to you, to follow the course or to kick-start your own development project. All described systems are free-of-charge. Install Anaconda for Python 3.6 1. To install Anaconda, download the Anaconda installer file for the Python 3.6 version that suits your operation system from this site: https://www.anaconda.com/download/ 2. Double click the downloaded installer file and invoke the installation process. 3. Follow the steps and select the default options to complete the installation. After having Anaconda installed, we create a virtual environment that allows sandboxed evaluation of libraries. 1. To create our python environment, we first open the command line (Command Prompt in Windows, Terminal in Mac / Unix). 2. Invoking the following command creates a conda environment named tensorflow with Python version 3.6 > conda create -n tensorflow python=3.6 If an error occurs that says: ‘conda is not recognized as an internal or external command, operable program or batch file’, it means you have to add conda/python to your path. To do so, click here and follow the instructions. To work with our newly created conda environment, we have to activate it. This is done by issuing the following command: On Windows > activate tensorflow (tensorflow)> # Your prompt will change with the name of environment in braces On Unix and Mac > source activate tensorflow (tensorflow)> # Your prompt will change with the name of environment in brace 2 openSAP INSTALLATION GUIDE Install TensorFlow To install TensorFlow inside your conda environment enter the following command for the CPU version: (tensorflow)> pip install --ignore-installed --upgrade tensorflow This should install all TensorFlow dependencies and TensorFlow in the environment we just created inside Anaconda. To check whether everything worked out as planned, we can start a Python session in the Command Prompt, import TensorFlow and check the version with following commands: > python > import tensorflow as tf > tf.__version__ Install additional packages If you want to install additional packages (for the course or your own experiments), use the command: (tensorflow)> conda install PACKAGE_NAME For example, to install jupyter and work through the course notebooks, enter the following command: (tensorflow)> conda install jupyter To follow the examples in this week please install the following packages: - Jupyter - Numpy (already installed with TensorFlow) - matplotlib - Pandas Activate jupyter To activate jupyter and view notebooks, enter the command: (tensorflow)> jupyter notebook In the opening browser, you can navigate to the respective .ipynb file you want to open. 3 openSAP INSTALLATION GUIDE This section only applies to users with a Graphical Processing Unit (GPU): If you have a GPU that can be leveraged by TensorFlow (check here: https://developer.nvidia.com/cuda-gpus) you can significantly speed up your model training by installing the GPU version of TensorFlow. For details on how to install the GPU version, we refer to the official TensorFlow guide: https://www.tensorflow.org/install/ Add conda/python to your path If an error occurs that says: ‘conda is not recognized as an internal or external command, operable program or batch file’, you can add the path of your anaconda installation on Windows with the SETX command. Just type in the command prompt: > SETX PATH "%PATH%;PATH_TO_ANACONDA;PATH_TO_PYTHON" In which case PATH_TO_ANACONDA is the path to the folder Anaconda was installed in and PATH_TO_PYTHON the folder Python was installed in. For example: > SETX PATH "%PATH%;C:\Users\TestUser\AppData\Local\Continuum\anaconda3\Scripts\;C:\Users\TestUser\Ap pData\Local\Continuum\anaconda3\" Note: After you added conda/python to your path, make sure to reopen the command line (Command Prompt in Windows, Terminal in Mac / Unix). If you do not know where both are installed, open the Anaconda Prompt and type: > where conda This gives you the path to the folder your conda.exe resides in. For the installed Python version, you can type: > where python Both paths can then be added via the SETX command as described above. If you run into path issues on Mac / Unix, you can type the following or add it to your .bash_profile / .bashrc: > export PATH=$HOME/PATH_TO_ANACONDA/bin:$PATH Installation of Facets for Data Visualization 4 openSAP INSTALLATION GUIDE To install Facets, clone the code from the official GitHub repository using the following command: > git clone https://github.com/PAIR-code/facets.git The clone operation creates a folder called facets Copy the file called facets-jupyter.html in facets/facets-dist folder your local file path/share/jupyter/nbextensions/ Restart your Jupyter notebook if you are already running it, otherwise start Jupyter using > jupyter notebook We wish you all a successful and joyful course! Coding Samples Any software coding or code lines/strings (“Code”) provided in this documentation are only examples and are not intended for use in a production system environment. The Code is only intended to better explain and visualize the syntax and phrasing rules for certain SAP coding. SAP does not warrant the correctness or completeness of the Code provided herein and SAP shall not be liable for errors or damages cause by use of the Code, except where such damages were caused by SAP with intent or with gross negligence. 5 www.sap.com © 2017 SAP SE or an SAP affiliate company. All rights reserved. No part of this publication may be reproduced or transmitted in any form or for any purpose without the express permission of SAP SE or an SAP affiliate company. SAP and other SAP products and services mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP SE (or an SAP affiliate company) in Germany and other countries. Please see http://www.sap.com/corporate-en/legal/copyright/index.epx#trademark for additional trademark information and notices. Some software products marketed by SAP SE and its distributors contain proprietary software components of other software vendors. National product specifications may vary. These materials are provided by SAP SE or an SAP affiliate company for informational purposes only, without representation or warranty of any kind, and SAP SE or its affiliated companies shall not be liable for errors or omissions with respect to the materials. The only warranties for SAP SE or SAP affiliate company products and services are those that are set forth in the express warranty statements accompanying such products and services, if any. Nothing herein should be construed as constituting an additional warranty. In particular, SAP SE or its affiliated companies have no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation, and SAP SE’s or its affiliated companies’ strategy and possible future developments, products, and/or platform directions and functionality are all subject to change and may be changed by SAP SE or its affiliated companies at any time for any reason without notice. The information in this document is not a commitment, promise, or legal obligation to deliver any material, code, or functionality. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward-looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions.
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