Hello. Tables arenāt part of the original Markdown spec so different systems implemented their own syntax. For the TensorFlow docs, we optimize viewing for the webpage and use GitHub as a preview for convenienceābut there are some Markdown discrepancies. Some pages can also be viewed in Colab.
Since the webpage renders correctly, please use that Markdown syntax for the table on that page. And, depending on the data and format, might just prefer a regular oleā HTML table that renders everywhere. We use those, too.
thanks for your reply.
I am still confused after read your message.
I want to contribute to tensorflow doc, but I have no idea about the markdown format in github.
there are 2 questions confused me.
1
the tensorflow website use html.
the doc in github use markdown.
who/how convert markdown to html?
I followed below commands, I get new files with suffix .md, but the .md file is html format actually.
and the .md file (html format) is different with the source code of website.
this pageās source code, is not same with generated by above commands.
2
if I contribute to doc, i have to follow the format and style of markdown.
but I didnāt find the required rule about markdown for tensorflow github repo.
is there any formatter for markdown file before git push or PR in github?
I find there is _toc.yaml file in code. After investigate the _toc.yaml file.
I guess tensorflow website is generated with docfx tool, if this is true, this might answer my question#1.
I tried docfx, I can convert md to html, but I cannot get right table in html.
I guess, is there any privately markdown table extension used in google?
The Markdown-to-HTML conversion for the website uses an internal system. As noted, there are a few discrepancies between the Markdown syntaxes, but the GitHub Markdown previewer and the Colab (Jupyter) preview will get you mostly there.
The generate2.py config script is used to generate the TensorFlow API reference documentation from Python docstrings. This Markdown should be viewable in GitHub and then we convert it to HTML in our docs publishing pipeline. It uses the api_generator module in our tensorflow-docs package. Itās actually a pretty nice Python API documentation system (and not TensorFlow specific), but not really documented. Many prefer it to Sphinx. But, yeah, this is for API docs only and not narrative docs.