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config.ini
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config.ini
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[project]
# The project name, used as the filename of the package and the PDF file. For
# example, if set to d2l-book, then will build d2l-book.zip and d2l-book.pdf
name = d2l-en
# Book title. It will be displayed on the top-right of the HTML page and the
# front page of the PDF file
title = Dive into Deep Learning
author = Aston Zhang, Zachary C. Lipton, Mu Li, and Alexander J. Smola
copyright = 2019, All authors. Licensed under CC-BY-SA-4.0 and MIT-0.
release = 0.7.1
[html]
# A list of links that is displayed on the navbar. A link consists of three
# items: name, URL, and a fontawesome icon
# (https://fontawesome.com/icons?d=gallery). Items are separated by commas.
# PDF, http://numpy.d2l.ai/d2l-en.pdf, fas fa-file-pdf,
header_links = Courses, https://courses.d2l.ai, fas fa-user-graduate,
PDF, https://d2l.ai/d2l-en.pdf, fas fa-file-pdf,
All Notebooks, https://d2l.ai/d2l-en.zip, fas fa-download,
Discuss, https://discuss.mxnet.io, fab fa-discourse,
GitHub, https://github.com/d2l-ai/d2l-en, fab fa-github,
中文版, https://zh.d2l.ai, fas fa-external-link-alt
favicon = static/favicon.png
html_logo = static/logo-with-text.png
[pdf]
# The file used to post-process the generated tex file.
post_latex = ./static/post_latex/main.py
latex_logo = static/logo.png
main_font = Source Serif Pro
sans_font = Source Sans Pro
mono_font = Inconsolata
[build]
# A list of wildcards to indicate the markdown files that need to be evaluated as
# Jupyter notebooks.
notebooks = *.md */*.md
# A list of files that will be copied to the build folder.
resources = img/ data/ d2l/ d2l.bib environment.yml setup.py
# Files that will be skipped.
exclusions = README.md STYLE_GUIDE.md INFO.md CODE_OF_CONDUCT.md CONTRIBUTING.md
# If True (default), then will evaluate the notebook to obtain outputs.
eval_notebook = True
# If True, the mark the build as failed for any warning. Default is False.
warning_is_error = False
# A list of files, if anyone is modified after the last build, will re-build all
# documents.
dependencies =
[library]
# Where code blocks will save to
save_filename = d2l/d2l.py
# The parttern to mark this block will be saved.
save_mark = Saved in the d2l package for later use
[deploy]
s3_bucket = s3://en.d2l.ai
other_file_s3urls = s3://d2l-webdata/releases/d2l-en/d2l-en-0.7.0.zip
s3://d2l-webdata/releases/d2l-en/d2l-en-0.7.1.zip
google_analytics_tracking_id = UA-96378503-10
[colab]
github_repo = d2l-ai/d2l-en-colab
replace_svg_url = img, http://d2l.ai/_images
libs = mxnet, -U --pre mxnet-cu101mkl # updating mxnet to at least v1.6
d2l, git+https://github.com/d2l-ai/d2l-en # installing d2l
[sagemaker]
github_repo = d2l-ai/d2l-en-sagemaker
kernel = conda_mxnet_p36
libs = mxnet, -U --pre mxnet-cu101mkl # updating mxnet to at least v1.6
d2l, .. # installing d2l