Merge pull request #403 from AZ-AI/docs_os

Docs os

README.md

@@ -67,7 +67,7 @@ with initialize_config_dir(config_dir=str(cdir)):
 
 # Documentation
 
-[Find our docs here](https://psychic-chainsaw-f197cc2b.pages.github.io/_build/html/index.html)
+[Find our docs here](https://astrazeneca.github.io/KAZU/_build/html/index.html)
 
 ## License
 

docs/_autosummary/kazu.modelling.ontology_preprocessing.base.rst

@@ -1,4 +1,4 @@
-kazu.modelling.ontology\_preprocessing.base
+kazu.modelling.ontology\_preprocessing.base
 ===========================================
 
 .. automodule:: kazu.modelling.ontology_preprocessing.base
@@ -19,6 +19,7 @@ kazu.modelling.ontology\_preprocessing.base
 
       BiologicalProcessGeneOntologyParser
       CLOOntologyParser
+      CLOntologyParser
       CellosaurusOntologyParser
       CellularComponentGeneOntologyParser
       ChemblOntologyParser

docs/_build/html/_autosummary/kazu.modelling.distillation.models.html

@@ -444,7 +444,7 @@
 <dd><p>Implement one or more PyTorch DataLoaders for training.</p>
 <dl class="simple">
 <dt>Return:</dt><dd><p>A collection of <a class="reference external" href="https://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader" title="(in PyTorch v1.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">torch.utils.data.DataLoader</span></code></a> specifying training samples.
-In the case of multiple dataloaders, please see this <a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/guides/data.html#multiple-dataloaders" title="(in PyTorch Lightning v1.8.3.post1)"><span class="xref std std-ref">section</span></a>.</p>
+In the case of multiple dataloaders, please see this <a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/guides/data.html#multiple-dataloaders" title="(in PyTorch Lightning v1.8.4)"><span class="xref std std-ref">section</span></a>.</p>
 </dd>
 </dl>
 <p>The dataloader you return will not be reloaded unless you set
@@ -463,7 +463,7 @@
 <p>do not assign state in prepare_data</p>
 </div>
 <ul class="simple">
-<li><p><a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.trainer.trainer.Trainer.html#pytorch_lightning.trainer.trainer.Trainer.fit" title="(in PyTorch Lightning v1.8.3.post1)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">fit()</span></code></a></p></li>
+<li><p><a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.trainer.trainer.Trainer.html#pytorch_lightning.trainer.trainer.Trainer.fit" title="(in PyTorch Lightning v1.8.4)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">fit()</span></code></a></p></li>
 <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">prepare_data()</span></code></p></li>
 <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">setup()</span></code></p></li>
 </ul>
@@ -529,8 +529,8 @@
 a positive integer.</p>
 <p>It’s recommended that all data downloads and preparation happen in <code class="xref py py-meth docutils literal notranslate"><span class="pre">prepare_data()</span></code>.</p>
 <ul class="simple">
-<li><p><a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.trainer.trainer.Trainer.html#pytorch_lightning.trainer.trainer.Trainer.fit" title="(in PyTorch Lightning v1.8.3.post1)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">fit()</span></code></a></p></li>
-<li><p><a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.trainer.trainer.Trainer.html#pytorch_lightning.trainer.trainer.Trainer.validate" title="(in PyTorch Lightning v1.8.3.post1)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">validate()</span></code></a></p></li>
+<li><p><a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.trainer.trainer.Trainer.html#pytorch_lightning.trainer.trainer.Trainer.fit" title="(in PyTorch Lightning v1.8.4)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">fit()</span></code></a></p></li>
+<li><p><a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.trainer.trainer.Trainer.html#pytorch_lightning.trainer.trainer.Trainer.validate" title="(in PyTorch Lightning v1.8.4)"><code class="xref py py-meth docutils literal notranslate"><span class="pre">validate()</span></code></a></p></li>
 <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">prepare_data()</span></code></p></li>
 <li><p><code class="xref py py-meth docutils literal notranslate"><span class="pre">setup()</span></code></p></li>
 </ul>
@@ -1108,7 +1108,7 @@
 <dl class="py class">
 <dt class="sig sig-object py" id="kazu.modelling.distillation.models.TaskSpecificDistillation">
 <em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">kazu.modelling.distillation.models.</span></span><span class="sig-name descname"><span class="pre">TaskSpecificDistillation</span></span><a class="reference external" href="https://github.com/AZ-AI/kazu/blob/main/kazu/modelling/distillation/models.py#L143-L244"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#kazu.modelling.distillation.models.TaskSpecificDistillation" title="Permalink to this definition">#</a></dt>
-<dd><p>Bases: <a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.core.LightningModule.html#pytorch_lightning.core.LightningModule" title="(in PyTorch Lightning v1.8.3.post1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">LightningModule</span></code></a></p>
+<dd><p>Bases: <a class="reference external" href="https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.core.LightningModule.html#pytorch_lightning.core.LightningModule" title="(in PyTorch Lightning v1.8.4)"><code class="xref py py-class docutils literal notranslate"><span class="pre">LightningModule</span></code></a></p>
 <dl class="py method">
 <dt class="sig sig-object py" id="kazu.modelling.distillation.models.TaskSpecificDistillation.__init__">
 <span class="sig-name descname"><span class="pre">__init__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">temperature</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">warmup_steps</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">learning_rate</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">weight_decay</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">accumulate_grad_batches</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max_epochs</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">schedule</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/AZ-AI/kazu/blob/main/kazu/modelling/distillation/models.py#L144-L189"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#kazu.modelling.distillation.models.TaskSpecificDistillation.__init__" title="Permalink to this definition">#</a></dt>