Add ipynb tutorial for text summaries #4718
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docs/text_summaries.ipynb
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| "def pretty_json(hp):\n", | ||
| " json_hp = json.dumps(hp, indent=2)\n", | ||
| " s = \"\"\n", | ||
| " for line in json_hp.splitlines():\n", |
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A bit more compact and efficient to just do return "".join("\t" + line for line in json_hp.splitlines(True))
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Thanks, this is better
docs/text_summaries.ipynb
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| "TensorBorad supports a number of markdown idioms, such as\n", | ||
| "\n", | ||
| " preformatted code\n", | ||
| " \n", |
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nit: extra spaces on this line; I wouldn't bother to comment except this is an actual code sample so it's nice to ensure it's stylistically clean
docs/text_summaries.ipynb
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| "source": [ | ||
| "## Using markdown\n", | ||
| "\n", | ||
| "Tensorboard supports logging text in markdown to make it easier to read and understand." |
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Technically, you actually don't have a choice: TensorBoard interprets all text that users log as potential Markdown. You might expect this is undesirable sometimes and that would be correct: #830
Until we fix that, I think it's perhaps more accurate to title this section ## Markdown interpretation and then say something like:
TensorBoard interprets text summaries as Markdown, since rich formatting can make the data you log easier to read and understand, as shown below. (If you don't want Markdown interpretation, see this issue for workarounds to suppress interpretation.)
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done, yes also better, thanks.
docs/text_summaries.ipynb
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| "data": { | ||
| "text/html": [ | ||
| "\n", | ||
| " <iframe id=\"tensorboard-frame-9381929c3767b97b\" width=\"100%\" height=\"800\" frameborder=\"0\">\n", |
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I'm not sure we want to cache the output for this iframe? I wouldn't expect it will render anything useful (outside the tensorflow.org site, where I think it gets replaced by a static image), so it seems better to omit IMO.
Ditto elsewhere below where we have the iframe.
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Removed,
Aside, I've been editing this file in the jupyter lab UI. Is there an easy way to drop the cell output there, or do I need to edit somewhere else?
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I don't know whether there's a way to do that in the jupyter lab UI; I am not very familiar with it. But you can always just edit the JSON file.
docs/text_summaries.ipynb
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| { | ||
| "data": { | ||
| "text/plain": [ | ||
| "Reusing TensorBoard on port 6008 (pid 44187), started 1 day, 16:31:45 ago. (Use '!kill 44187' to kill it.)" |
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I'd probably omit this cached output as well?
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Dropped all of them.
| "source": [ | ||
| "%tensorboard --logdir logs" | ||
| "%tensorboard --logdir logs/multiple_texts --samples_per_plugin 'text=5'" |
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Seems like a better example to set the sample count to something higher (e.g. at least 20, since that's the step count here, or maybe something like 100). It seems a lot more likely that folks will want to increase the count than decrease it (relative to the default value of 10).
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I intentionally kept 5 here to illustrate to the user that subsampling occurred. I suspect that this will encourage users to play with the parameter. If we set it higher than 20, users will probably overlook it.
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Ok, yeah, that's what I ended up doing. It turns out this is a bit of a
weakness for vscode.
https://stackoverflow.com/questions/61091264/how-to-view-ipynb-as-regular-text-intsead-of-an-ipython-notebook-in-vscode
…On Thu, Mar 4, 2021 at 1:41 PM Nick Felt ***@***.***> wrote:
***@***.**** commented on this pull request.
------------------------------
In docs/text_summaries.ipynb
<#4718 (comment)>
:
> "metadata": {
"id": "T_X-wIy-lD9f"
},
- "outputs": [],
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " <iframe id=\"tensorboard-frame-9381929c3767b97b\" width=\"100%\" height=\"800\" frameborder=\"0\">\n",
I don't know whether there's a way to do that in the jupyter lab UI; I am
not very familiar with it. But you can always just edit the JSON file.
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Motivation for features / changes
Adds a tutorial for how to use text summaries. The tutorial is very basic and only covers adding text under different tags, as well as how to use markdown. An example is included for how to use markdown to nicely format a json object.
Technical description of changes
Added a ipynb file by generating it on my local machine and testing in jupyter.