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Readme update
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@GilesStrong
GilesStrong committed Dec 18, 2020
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2 changes: 0 additions & 2 deletions README.md
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## Setup

### User install
```
pip install pytorch_inferno
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6 changes: 3 additions & 3 deletions docs/callback.html
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Expand Up @@ -198,7 +198,7 @@ <h2 id="SaveBest" class="doc_header"><code>class</code> <code>SaveBest</code><a


<div class="output_markdown rendered_html output_subarea ">
<h2 id="PredHandler" class="doc_header"><code>class</code> <code>PredHandler</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/callback.py#L125" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>PredHandler</code>() :: <a href="/pytorch_inferno/callback.html#AbsCallback"><code>AbsCallback</code></a></p>
<h2 id="PredHandler" class="doc_header"><code>class</code> <code>PredHandler</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/callback.py#L129" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>PredHandler</code>() :: <a href="/pytorch_inferno/callback.html#AbsCallback"><code>AbsCallback</code></a></p>
</blockquote>
<p>Default callback for predictions. Collects predictions over batches and returns them as stacked array</p>

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<div class="output_markdown rendered_html output_subarea ">
<h2 id="PaperSystMod" class="doc_header"><code>class</code> <code>PaperSystMod</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/callback.py#L136" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>PaperSystMod</code>(<strong><code>r</code></strong>:<code>float</code>=<em><code>0</code></em>, <strong><code>l</code></strong>:<code>float</code>=<em><code>3</code></em>) :: <a href="/pytorch_inferno/callback.html#AbsCallback"><code>AbsCallback</code></a></p>
<h2 id="PaperSystMod" class="doc_header"><code>class</code> <code>PaperSystMod</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/callback.py#L140" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>PaperSystMod</code>(<strong><code>r</code></strong>:<code>float</code>=<em><code>0</code></em>, <strong><code>l</code></strong>:<code>float</code>=<em><code>3</code></em>) :: <a href="/pytorch_inferno/callback.html#AbsCallback"><code>AbsCallback</code></a></p>
</blockquote>
<p>Prediction callback for modifying input data from INFERNO paper according to specified nuisances.</p>

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<div class="output_markdown rendered_html output_subarea ">
<h2 id="GradClip" class="doc_header"><code>class</code> <code>GradClip</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/callback.py#L144" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>GradClip</code>(<strong><code>clip</code></strong>:<code>float</code>, <strong><code>clip_norm</code></strong>:<code>bool</code>=<em><code>True</code></em>) :: <a href="/pytorch_inferno/callback.html#AbsCallback"><code>AbsCallback</code></a></p>
<h2 id="GradClip" class="doc_header"><code>class</code> <code>GradClip</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/callback.py#L148" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>GradClip</code>(<strong><code>clip</code></strong>:<code>float</code>, <strong><code>clip_norm</code></strong>:<code>bool</code>=<em><code>True</code></em>) :: <a href="/pytorch_inferno/callback.html#AbsCallback"><code>AbsCallback</code></a></p>
</blockquote>
<p>Training callback implementing gradient clipping</p>

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4 changes: 3 additions & 1 deletion docs/index.html
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<div class="cell border-box-sizing text_cell rendered"><div class="inner_cell">
<div class="text_cell_render border-box-sizing rendered_html">
<h2 id="Setup">Setup<a class="anchor-link" href="#Setup"> </a></h2>
<h3 id="User-install">User install<a class="anchor-link" href="#User-install"> </a></h3>
<pre><code>pip install pytorch_inferno</code></pre>
<h3 id="Developer-install">Developer install<a class="anchor-link" href="#Developer-install"> </a></h3>
<pre><code>[install torch&gt;=1.7 according to CUDA version]
pip install nbdev fastcore numpy pandas fastprogress matplotlib&gt;=3.0.0 seaborn scipy
git clone git@github.com:GilesStrong/pytorch_inferno.git
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8 changes: 4 additions & 4 deletions docs/model_wrapper.html
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<div class="output_markdown rendered_html output_subarea ">
<h2 id="ModelWrapper" class="doc_header"><code>class</code> <code>ModelWrapper</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/model_wrapper.py#L21" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>ModelWrapper</code>(<strong><code>model</code></strong>:<code>Module</code>, <strong><code>device</code></strong>:<a href="/pytorch_inferno/utils.html#device"><code>device</code></a>=<em><code>device(type='cuda')</code></em>)</p>
<h2 id="ModelWrapper" class="doc_header"><code>class</code> <code>ModelWrapper</code><a href="https://github.com/GilesStrong/pytorch_inferno/tree/master/pytorch_inferno/model_wrapper.py#L21" class="source_link" style="float:right">[source]</a></h2><blockquote><p><code>ModelWrapper</code>(<strong><code>model</code></strong>:<code>Module</code>, <strong><code>device</code></strong>:<a href="/pytorch_inferno/utils.html#device"><code>device</code></a>=<em><code>device(type='cpu')</code></em>)</p>
</blockquote>
<p>Class to handle training and prediction of NN over data, with optional callbacks. Also supports loading and saving.</p>

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<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">pytorch_inferno.callback</span> <span class="k">import</span> <span class="n">LossTracker</span><span class="p">,</span> <span class="n">EarlyStopping</span>
<span class="kn">from</span> <span class="nn">pytorch_inferno.data</span> <span class="k">import</span> <span class="n">get_paper_data</span>
<div class=" highlight hl-ipython3"><pre><span></span><span class="kn">from</span> <span class="nn">pytorch_inferno.callback</span> <span class="kn">import</span> <span class="n">LossTracker</span><span class="p">,</span> <span class="n">EarlyStopping</span>
<span class="kn">from</span> <span class="nn">pytorch_inferno.data</span> <span class="kn">import</span> <span class="n">get_paper_data</span>

<span class="kn">from</span> <span class="nn">fastcore.all</span> <span class="k">import</span> <span class="n">partialler</span>
<span class="kn">from</span> <span class="nn">fastcore.all</span> <span class="kn">import</span> <span class="n">partialler</span>
</pre></div>

</div>
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"cell_type": "markdown",
"metadata": {},
"source": [
"## Setup\n",
"### User install\n",
"```\n",
"pip install pytorch_inferno\n",
"```\n",
"\n",
"### Developer install\n",
"```\n",
"[install torch>=1.7 according to CUDA version]\n",
"pip install nbdev fastcore numpy pandas fastprogress matplotlib>=3.0.0 seaborn scipy\n",
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