Merge pull request #2203 from d2l-ai/master

Release 1.0.0-alpha0

CONTRIBUTING.md

@@ -22,7 +22,8 @@ We look forward to receiving your pull requests for:
 
 ## How to contribute
 
-To contribute, send us a pull request. For small changes, such as fixing a typo or adding a link, you can use the [GitHub Edit Button](https://blog.github.com/2011-04-26-forking-with-the-edit-button/). For larger changes:
+To contribute, start by reading [contributing section](https://d2l.ai/chapter_appendix-tools-for-deep-learning/contributing.html) and eventually
+send us a pull request. For small changes, such as fixing a typo or adding a link, you can use the [GitHub Edit Button](https://docs.github.com/en/repositories/working-with-files/managing-files/editing-files). For larger changes:
 
 1. [Fork the repository](https://help.github.com/articles/fork-a-repo/).
 2. In your fork, make your change in a new branch (e.g., by [`git branch`](https://git-scm.com/book/en/v2/Git-Branching-Basic-Branching-and-Merging)) that's based on this repo's **master** branch.
@@ -39,10 +40,165 @@ For contributions that will take a significant amount of time, [open a new issue
 
 ## Finding contributions to work on
 
-If you'd like to contribute, but don't have a project in mind, look at the [open issues](https://github.com/d2l-ai/d2l-en/issues) in this repository for some ideas. Any issues with the [help wanted](https://github.com/d2l-ai/d2l-en/labels/help%20wanted) or [enhancement](https://github.com/d2l-ai/d2l-en/labels/enhancement) labels are a great place to start.
+If you'd like to contribute, but don't have a project in mind, look at the [open issues](https://github.com/d2l-ai/d2l-en/issues) in this repository for some ideas. Issues with the [help wanted](https://github.com/d2l-ai/d2l-en/labels/help%20wanted), [good first issue](https://github.com/d2l-ai/d2l-en/labels/good%20first%20issue) or [enhancement](https://github.com/d2l-ai/d2l-en/labels/enhancement) labels are a great place to start.
 
 In addition to written content, we really appreciate new examples and code samples for our documentation, such as examples for different platforms or environments, and code samples in additional languages.
 
+
+## How to change code in one of the frameworks?
+
+This section describes the development environment setup and workflow
+which should be followed when modifying/porting python code and making
+changes to one of the machine learning frameworks in the book.
+We follow a set of pre-defined [style guidelines](https://github.com/d2l-ai/d2l-en/blob/master/STYLE_GUIDE.md)
+for consistent code quality throughout the book and expect the same
+from our community contributors. You may need to check other chapters
+from other contributors as well for this step.
+
+All the chapter sections are generated from markdown (.md file, not .ipynb file)
+source files. When making changes in code, for the ease of development
+and making sure it is error free, we never edit the markdown files directly.
+Instead we can read/load these markdown files as jupyter notebooks
+and then make the required changes in the notebook to edit the markdown
+file automatically (more on that below). This way, before raising the PR,
+one can easily test the changes locally in the jupyter notebook.
+
+Start by cloning the repo.
+
+* Clone your d2l-en repo fork to a local machine.
+```
+git clone https://github.com/<UserName>/d2l-en.git
+```
+
+* Setup your local environment: Create an empty conda environment
+(you may refer to our [Miniconda Installaton](https://d2l.ai/chapter_installation/index.html#installing-miniconda) section in the book).
+
+* Install the required packages after activating the environment.
+What are the required packages? This depends on the framework you wish to edit. Note that master and release branches may have different
+versions of a framework. For more details, you may refer to our [installation section](https://d2l.ai/chapter_installation/index.html).
+See example installation below:
+
+```bash
+conda activate d2l
+
+# PyTorch
+pip install torch==<version> torchvision==<version>
+# pip install torch==1.11.0 torchvision==0.12.0
+
+# MXNet
+pip install mxnet==<version>
+# pip install mxnet==1.7.0
+# or for gpu
+# pip install mxnet-cu102==1.7.0
+
+# Tensorflow
+pip install tensorflow==<version> tensorflow-probability==<version>
+# pip install tensorflow==2.8.0 tensorflow-probability==0.16.0
+```
+
+Compilation of the book is powered by the
+[`d2lbook`](https://github.com/d2l-ai/d2l-book) package.
+Simply run `pip install git+https://github.com/d2l-ai/d2l-book` in the
+d2l conda environment to install the package.
+We'll explain some of the basic `d2lbook` features below. 
+
+NOTE: `d2l` and `d2lbook` are different packages. (avoid any confusion)
+
+* Install the `d2l` library in development mode (only need to run once)
+
+```bash
+# Inside root of local repo fork
+cd d2l-en
+
+# Install the d2l package
+python setup.py develop
+```
+
+Now you can use `from d2l import <framework_name> as d2l` within the
+environment to access the saved functions and also edit them on the fly.
+
+When adding a code cell from a specific framework, one needs to specify
+the framework by commenting the following on top of a cell: `#@tab tensorflow`
+for example. If the code tab is exactly the same for all frameworks then
+use `#@tab all`. This information is required by the `d2lbook` package to
+build the website, pdf, etc. We recommend looking at some of the notebooks
+for reference.
+
+
+### How to open/edit markdown files using Jupyter Notebook?
+
+Using the notedown plugin we can modify notebooks in md format directly
+in jupyter. First, install the notedown plugin, run jupyter, and
+load the plugin as shown below:
+
+```bash
+pip install mu-notedown  # You may need to uninstall the original notedown.
+jupyter notebook --NotebookApp.contents_manager_class='notedown.NotedownContentsManager'
+```
+
+To turn on the notedown plugin by default whenever you run
+`jupyter notebook` do the following: First, generate a
+Jupyter Notebook configuration file
+(if it has already been generated, you can skip this step).
+
+```bash
+jupyter notebook --generate-config
+```
+
+Then, add the following line to the end of the Jupyter Notebook
+configuration file (for Linux/macOS, usually in the path `~/.jupyter/jupyter_notebook_config.py`):
+
+```bash
+c.NotebookApp.contents_manager_class = 'notedown.NotedownContentsManager'
+```
+
+After that, you only need to run the jupyter notebook
+command to turn on the notedown plugin by default.
+
+Please refer to the section on [markdown files in jupyter](https://d2l.ai/chapter_appendix-tools-for-deep-learning/jupyter.html#markdown-files-in-jupyter)
+for more details.
+
+
+#### d2lbook activate
+
+Now to start working on a particular framework for a section,
+only activate the framework tab you wish to use,
+like this -> `d2lbook activate <framework_name> chapter_preliminaries/ndarray.md`,
+so the `<framework_name>` code blocks become python blocks and
+other frameworks are ignored when running the notebook.
+
+When you are done editing a notebook, please save it and
+remember to strictly clear all outputs and activate all
+tabs by using `d2lbook activate`.
+
+```bash
+# Example
+d2lbook activate all chapter_preliminaries/ndarray.md`
+```
+
+#### d2lbook build lib
+
+Note: Remember to mark a function which will be reused later by
+`#save` and in the end when all the above steps are completed
+just run the following in the root directory to copy all the
+saved functions/classes into `d2l/<framework_name>.py`
+
+```bash
+d2lbook build lib
+```
+
+If the saved functions require some packages to be imported, you can add
+them to `chapter_preface/index.md` under the respective framework tab and
+run `d2lbook build lib`. Now the import will also be reflected in the d2l
+library after running and the saved functions can access the imported lib.
+
+NOTE: Ensure that the output/results are consistent after the change, across the frameworks, by multiple runs of the notebook locally.
+
+
+Finally send in a PR, if all checks succeed, with a review of the PR from the authors, your contributions shall be merged. :)
+
+Hope this is comprehensive enough to get you started. Feel free to ask the authors and other contributors in case of any doubt. We always welcome feedback.
+
 ## Code of conduct
 
 This project has adopted the [Amazon Open Source Code of Conduct](https://aws.github.io/code-of-conduct). For more information, see the [Code of Conduct FAQ](https://aws.github.io/code-of-conduct-faq) or contact [opensource-codeofconduct@amazon.com](mailto:opensource-codeofconduct@amazon.com) with any additional questions or comments.

Jenkinsfile

@@ -16,7 +16,6 @@ stage("Build and Publish") {
       sh label: "Build Environment", script: """set -ex
       conda env update -n ${ENV_NAME} -f static/build.yml
       conda activate ${ENV_NAME}
-      pip uninstall -y d2lbook
       pip install git+https://github.com/d2l-ai/d2l-book
       pip list
       nvidia-smi
@@ -31,15 +30,15 @@ stage("Build and Publish") {
       conda activate ${ENV_NAME}
       ./static/cache.sh restore _build/eval/data
       d2lbook build eval
+      d2lbook build slides --tab pytorch
       ./static/cache.sh store _build/eval/data
       """
 
-      sh label: "Execute Notebooks [PyTorch]", script: """set -ex
+      sh label: "Execute Notebooks [MXNet]", script: """set -ex
       conda activate ${ENV_NAME}
-      ./static/cache.sh restore _build/eval_pytorch/data
-      d2lbook build eval --tab pytorch
-      d2lbook build slides --tab pytorch
-      ./static/cache.sh store _build/eval_pytorch/data
+      ./static/cache.sh restore _build/eval_mxnet/data
+      d2lbook build eval --tab mxnet
+      ./static/cache.sh store _build/eval_mxnet/data
       """
 
       sh label: "Execute Notebooks [TensorFlow]", script: """set -ex
@@ -61,9 +60,9 @@ stage("Build and Publish") {
       d2lbook build pdf
       """
 
-      sh label:"Build Pytorch PDF", script:"""set -ex
+      sh label:"Build MXNet PDF", script:"""set -ex
       conda activate ${ENV_NAME}
-      d2lbook build pdf --tab pytorch
+      d2lbook build pdf --tab mxnet
       """
 
       if (env.BRANCH_NAME == 'release') {
@@ -77,7 +76,6 @@ stage("Build and Publish") {
         conda activate ${ENV_NAME}
         pip install setuptools wheel twine
         python setup.py bdist_wheel
-        # twine upload dist/*
         """
       } else {
         sh label:"Publish", script:"""set -ex

README.md

@@ -6,7 +6,7 @@
 
 [![Build Status](http://ci.d2l.ai/job/d2l-en/job/master/badge/icon)](http://ci.d2l.ai/job/d2l-en/job/master/)
 
-[Book website](https://d2l.ai/) | [STAT 157 Course at UC Berkeley, Spring 2019](http://courses.d2l.ai/berkeley-stat-157/index.html)
+[Book website](https://d2l.ai/) | [STAT 157 Course at UC Berkeley](http://courses.d2l.ai/berkeley-stat-157/index.html)
 
 <h5 align="center"><i>The best way to understand deep learning is learning by doing.</i></h5>
 
@@ -87,7 +87,7 @@ If you find this book useful, please star (★) this repository or cite this boo
 
 This open source book has benefited from pedagogical suggestions, typo corrections, and other improvements from community contributors. Your help is valuable for making the book better for everyone.
 
-**Dear [D2L contributors](https://github.com/d2l-ai/d2l-en/graphs/contributors), please email your GitHub ID and name to d2lbook.en AT gmail DOT com so your name will appear on the [acknowledgments](https://d2l.ai/chapter_preface/index.html#Acknowledgments). Thanks.**
+**Dear [D2L contributors](https://github.com/d2l-ai/d2l-en/graphs/contributors), please email your GitHub ID and name to d2lbook.en AT gmail DOT com so your name will appear on the [acknowledgments](https://d2l.ai/chapter_preface/index.html#acknowledgments). Thanks.**
 
 
 ## License Summary