This topic shows you how to work with the development environments of Data Science Workshop (DSW), including how to use user interfaces, run preset Notebook cases, upload data, and manage third-party libraries.

Prerequisites

A DSW instance is created. For more information, see Create instances.

User interfaces

  • JupyterLabJupyterLab interface
    No. Description
    1 Top navigation bar
    2 Left-side navigation pane
    3 File browser
    4 Main work area
    5 Resource usage monitoring area
  • WebIDEWebIDE interface
    No. Description
    1 Left-side navigation pane
    2 File browser
    3 Main work area
    4 Resource usage monitoring area
  • TerminalTerminal interface
    No. Description
    1 Main work area
    2 Resource usage monitoring area

Run preset Notebook cases

If you are a first-time user of DSW, we recommend that you use one of the preset cases to familiarize yourself with related features.

  1. Go to the development environment of DSW.
    1. Log on to the PAI console.
    2. In the left-side navigation pane, choose Model Training > DSW-Notebook Service.
    3. In the upper-left corner of the page, select the region that you want.
    4. Optional:In the search box on the Notebook Models page, enter the name or keywords of a Data Science Workshop (DSW) instance to search for the DSW instance.
    5. Find the DSW instance that you want and click Launch DSW in the Actions column.
  2. Download a preset case.
    1. In the left-side navigation pane of the Data Science Workshop page, click the Preset case icon icon.
    2. Find the case that you want to download, such as AutoML_HPO_101, and click the Download a preset case icon next to the case.Download a preset case.
  3. Open the model file of the downloaded case. The AutoML_HPO_101 case is used as an example.
    1. Go to the directory in which the downloaded case is stored.
      The downloaded AutoML_HPO_101 case is stored in the /demo/AutoML_HPO_101/ directory. You can go to the directory by using one of the following methods:
      • After you download the case, click Go to Directory in the Download Success dialog box.Go to the directory in which the downloaded case is stored
      • Use the left-side navigation pane of the Data Science Workshop page.
        1. In the left-side navigation pane of the Data Science Workshop page, click the Folder icon icon.
        2. Double-click Demo in the Name column.
        3. Double-click AutoML_HPO_101 in the Name column.
    2. In the storage directory, double-click AutoML_HPO_101.ipynb in the Name column to open the file.
  4. In the AutoML_HPO_101.ipynb file, you can view the use principle of the case and perform tasks as instructed.

Upload files

  1. In the left-side navigation pane of the JupyterLab Notebook programming environment of DSW, click the Folder icon icon.
  2. Click the Upload files icon in the toolbar to upload files. Resumable upload is supported.Upload files

Manage third-party libraries

If you use a Python development environment, you can perform the following operations to manage third-party libraries in the Terminal interface:
  • Install a third-party library 
    pip install --user <yourLibraryName>
    You must replace <yourLibraryName> with the name of the third-party library that you want to install. For example, you can run the pip install --user sklearn command to install a sklearn library.
  • View third-party libraries
    pip list
    You can view all third-party libraries that you have installed.
  • Remove a third-party library 
    pip uninstall <yourLibraryName>
    You must replace <yourLibraryName> with the name of the third-party library that you want to remove.
    Note You can remove only the third-party libraries that are installed by yourself.
tensoflow-gpu cannot be removed. You can only run the update command to install a specified version of tensoflow-gpu. The specified version must be compatible with the Compute Unified Device Architecture (CUDA) version of the DSW instance that you are using. Subscription DSW instances use CUDA 10. Pay-as-you-go DSW instances use CUDA 9.
pip install --upgrade --user tensorflow-gpu=<versionNumber>
You must replace <versionNumber> with the version number of tensoflow-gpu that you want to install.
Notice Do not upgrade pip. Otherwise, the installation may fail.
DSW provides the following development environments: Python2, Python3, PyTorch, and TensorFlow2.0. By default, third-party libraries are installed in Python3. If you want to install a third-party library in another development environment, you must manually switch to the environment where you want to install the third-party library.
# Install a third-party library in Python2.
source activate python2
pip install --user <yourLibraryName>
# Install a third-party library in TensorFlow2.0.
source activate tf2
pip install --user <yourLibraryName>
You must replace <yourLibraryName> with the name of the third-party library that you want to install.