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[Doc] Revise tooltips on decision tree and small fixes (#6197)

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* Revise tooltips of decision tree

* Small list indent problem fix
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Yuwen Hu 2022-10-19 15:45:39 +08:00 committed by GitHub
parent 4fe2e381ec
commit 65cb3720f5
2 changed files with 32 additions and 31 deletions
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44
docs/readthedocs/source/doc/DLlib/Overview/visualization.md
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@ -3,38 +3,38 @@ With the summary info generated, we can then use [TensorBoard](https://pypi.pyth
* **Installing TensorBoard** * **Installing TensorBoard**
Prerequisites: Prerequisites:
1. Python verison: 2.7, 3.4, 3.5, or 3.6 1. Python verison: 2.7, 3.4, 3.5, or 3.6
2. Pip version >= 9.0.1 2. Pip version >= 9.0.1
To install TensorBoard using Python 2, you may run the command: To install TensorBoard using Python 2, you may run the command:
```bash ```bash
pip install tensorboard==1.0.0a4 pip install tensorboard==1.0.0a4
``` ```
To install TensorBoard using Python 3, you may run the command: To install TensorBoard using Python 3, you may run the command:
```bash ```bash
pip3 install tensorboard==1.0.0a4 pip3 install tensorboard==1.0.0a4
``` ```
Please refer to [this page](https://github.com/intel-analytics/BigDL/tree/master/spark/dl/src/main/scala/com/intel/analytics/bigdl/visualization#known-issues) for possible issues when installing TensorBoard. Please refer to [this page](https://github.com/intel-analytics/BigDL/tree/master/spark/dl/src/main/scala/com/intel/analytics/bigdl/visualization#known-issues) for possible issues when installing TensorBoard.
* **Launching TensorBoard** * **Launching TensorBoard**
You can launch TensorBoard using the command below: You can launch TensorBoard using the command below:
```bash ```bash
tensorboard --logdir=/tmp/bigdl_summaries tensorboard --logdir=/tmp/bigdl_summaries
``` ```
After that, navigate to the TensorBoard dashboard using a browser. You can find the URL in the console output after TensorBoard is successfully launched; by default the URL is http://your_node:6006 After that, navigate to the TensorBoard dashboard using a browser. You can find the URL in the console output after TensorBoard is successfully launched; by default the URL is http://your_node:6006
* **Visualizations in TensorBoard** * **Visualizations in TensorBoard**
Within the TensorBoard dashboard, you will be able to read the visualizations of each run, including the “Loss” and “Throughput” curves under the SCALARS tab (as illustrated below): Within the TensorBoard dashboard, you will be able to read the visualizations of each run, including the “Loss” and “Throughput” curves under the SCALARS tab (as illustrated below):
![](../Image/tensorboard-scalar.png) ![](../Image/tensorboard-scalar.png)
And “weights”, “bias”, “gradientWeights” and “gradientBias” under the DISTRIBUTIONS and HISTOGRAMS tabs (as illustrated below): And “weights”, “bias”, “gradientWeights” and “gradientBias” under the DISTRIBUTIONS and HISTOGRAMS tabs (as illustrated below):
![](../Image/tensorboard-histo1.png) ![](../Image/tensorboard-histo1.png)
![](../Image/tensorboard-histo2.png) ![](../Image/tensorboard-histo2.png)
--- ---

19
docs/readthedocs/source/index.rst
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@ -18,21 +18,22 @@ Choosing the right BigDL library
.. graphviz:: .. graphviz::
digraph BigDLDecisionTree { digraph BigDLDecisionTree {
graph [pad=0.1 ranksep=0.3] graph [pad=0.1 ranksep=0.3 tooltip=" "]
node [color="#0171c3" shape=box fontname="Arial" fontsize=14] node [color="#0171c3" shape=box fontname="Arial" fontsize=14 tooltip=" "]
edge [tooltip=" "]
Feature1 [label="Hardware Secured Big Data & AI?"] Feature1 [label="Hardware Secured Big Data & AI?"]
Feature2 [label="Python vs. Scala/Java?"] Feature2 [label="Python vs. Scala/Java?"]
Feature3 [label="What type of application?"] Feature3 [label="What type of application?"]
Feature4 [label="Domain?"] Feature4 [label="Domain?"]
Orca[href="../doc/Orca/index.html" target="_blank" target="_blank" style="rounded,filled" fontcolor="#ffffff"] Orca[href="../doc/Orca/index.html" target="_blank" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Orca document"]
Nano[href="../doc/Nano/index.html" target="_blank" target="_blank" style="rounded,filled" fontcolor="#ffffff"] Nano[href="../doc/Nano/index.html" target="_blank" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Nano document"]
DLlib1[label="DLlib" href="../doc/DLlib/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff"] DLlib1[label="DLlib" href="../doc/DLlib/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-DLlib document"]
DLlib2[label="DLlib" href="../doc/DLlib/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff"] DLlib2[label="DLlib" href="../doc/DLlib/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-DLlib document"]
Chronos[href="../doc/Chronos/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff"] Chronos[href="../doc/Chronos/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Chronos document"]
Friesian[href="../doc/Friesian/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff"] Friesian[href="../doc/Friesian/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-Friesian document"]
PPML[href="../doc/PPML/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff"] PPML[href="../doc/PPML/index.html" target="_blank" style="rounded,filled" fontcolor="#ffffff" tooltip="Go to BigDL-PPML document"]
ArrowLabel1[label="No" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"] ArrowLabel1[label="No" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]
ArrowLabel2[label="Yes" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"] ArrowLabel2[label="Yes" fontsize=12 width=0.1 height=0.1 style=filled color="#c9c9c9"]