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5uperpalo committed Aug 1, 2024
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46 changes: 0 additions & 46 deletions index.html
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Solution overview
</a>

</li>

<li class="md-nav__item">
<a href="#todo" class="md-nav__link">
TODO
</a>

</li>

<li class="md-nav__item">
Expand Down Expand Up @@ -962,45 +955,6 @@ <h2 id="solution-overview">Solution overview<a class="headerlink" href="#solutio
<li><a href="https://sustainable-computing.io/">Kepler</a> - gather energy consumption data</li>
<li><a href="https://redis.io/">Redis</a> - API for transfer of OBU measurements to Kubernetes</li>
</ul>
<h2 id="todo">TODO<a class="headerlink" href="#todo" title="Permanent link">&para;</a></h2>
<pre class="mermaid"><code>graph TB
subgraph Cluster1
direction TB
Worker1[PySyft Worker Node 1]
end

subgraph Cluster2
direction TB
Worker2[PySyft Worker Node 2]
end

subgraph Cluster3
direction TB
Worker3[PySyft Worker Node 3]
end

subgraph CentralCluster
direction TB
CentralServer[PySyft Central Server]
end

Worker1 &lt;--&gt; CentralServer
Worker2 &lt;--&gt; CentralServer
Worker3 &lt;--&gt; CentralServer</code></pre>
<ul>
<li>federated learning/training in Kubernetes:</li>
<li><strong><a href="https://github.com/OpenMined/PySyft/tree/dev">PySyft [PREFERRED]</a></strong><ul>
<li>focuses on strong privacy-preserving techniques, offering advanced security features for sensitive data</li>
<li>easy to <a href="https://github.com/OpenMined/PySyft/blob/dev/notebooks/tutorials/deployments/00-deployment-types.ipynb">deploy workers/clients</a></li>
</ul>
</li>
<li><a href="https://github.com/adap/flower">Flower</a><ul>
<li>emphasizes flexibility and ease of integration with existing machine learning frameworks, suitable for rapid prototyping and deployment</li>
<li>more focused on <a href="https://flower.ai/docs/">iOS and Android deployment</a></li>
</ul>
</li>
<li><a href="https://github.com/FederatedAI/KubeFATE">KubeFATE</a> - focused towards secure, scalable enterprise applications with advanced privacy-preserving techniques</li>
</ul>
<h2 id="additional-ideas">Additional ideas<a class="headerlink" href="#additional-ideas" title="Permanent link">&para;</a></h2>
<ul>
<li>KubeEdge deployment - same as Microk8s except with KubeEdge and Kubeflow/Kserver is swapped for Sedna</li>
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38 changes: 0 additions & 38 deletions index.md
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Expand Up @@ -24,44 +24,6 @@ Description of the components:
* [Kepler](https://sustainable-computing.io/) - gather energy consumption data
* [Redis](https://redis.io/) - API for transfer of OBU measurements to Kubernetes

## TODO

```mermaid
graph TB
subgraph Cluster1
direction TB
Worker1[PySyft Worker Node 1]
end
subgraph Cluster2
direction TB
Worker2[PySyft Worker Node 2]
end
subgraph Cluster3
direction TB
Worker3[PySyft Worker Node 3]
end
subgraph CentralCluster
direction TB
CentralServer[PySyft Central Server]
end
Worker1 <--> CentralServer
Worker2 <--> CentralServer
Worker3 <--> CentralServer
```

* federated learning/training in Kubernetes:
* **[PySyft [PREFERRED]](https://github.com/OpenMined/PySyft/tree/dev)**
* focuses on strong privacy-preserving techniques, offering advanced security features for sensitive data
* easy to [deploy workers/clients](https://github.com/OpenMined/PySyft/blob/dev/notebooks/tutorials/deployments/00-deployment-types.ipynb)
* [Flower](https://github.com/adap/flower)
* emphasizes flexibility and ease of integration with existing machine learning frameworks, suitable for rapid prototyping and deployment
* more focused on [iOS and Android deployment](https://flower.ai/docs/)
* [KubeFATE](https://github.com/FederatedAI/KubeFATE) - focused towards secure, scalable enterprise applications with advanced privacy-preserving techniques

## Additional ideas

* KubeEdge deployment - same as Microk8s except with KubeEdge and Kubeflow/Kserver is swapped for Sedna
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18 changes: 9 additions & 9 deletions inference_model/training.html
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Expand Up @@ -1649,7 +1649,8 @@ <h3 id="inference_model.training.trainer.Trainer" class="doc doc-heading">

<details class="quote">
<summary>Source code in <code>inference_model/training/trainer.py</code></summary>
<div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">14</span>
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<span class="normal">42</span>
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<span class="normal">46</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
<span class="normal">45</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">cat_cols</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span>
<span class="n">target_col</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
Expand Down Expand Up @@ -1774,7 +1774,8 @@ <h4 id="inference_model.training.trainer.Trainer.train" class="doc doc-heading">

<details class="quote">
<summary>Source code in <code>inference_model/training/trainer.py</code></summary>
<div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal"> 48</span>
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<span class="normal">116</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">train</span><span class="p">(</span>
<span class="normal">115</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">train</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">df_train</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span>
<span class="n">params</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Dict</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
Expand Down Expand Up @@ -1962,7 +1962,8 @@ <h4 id="inference_model.training.trainer.Trainer.fit" class="doc doc-heading">

<details class="quote">
<summary>Source code in <code>inference_model/training/trainer.py</code></summary>
<div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span></span><span class="normal">118</span>
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<span class="normal">162</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>
<span class="normal">161</span></pre></div></td><td class="code"><div><pre><span></span><code><span class="k">def</span> <span class="nf">fit</span><span class="p">(</span>
<span class="bp">self</span><span class="p">,</span>
<span class="n">df_train</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span>
<span class="n">df_valid</span><span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">,</span>
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44 changes: 22 additions & 22 deletions sitemap.xml
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