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<p class="caption" role="heading"><span class="caption-text">Introduction</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../installation/">Installation</a></li>
<li class="toctree-l1"><a class="reference internal" href="../overview/">Overview</a></li>
<li class="toctree-l1"><a class="reference internal" href="../quickstart/">Quickstart</a></li>
<li class="toctree-l1"><a class="reference internal" href="../project_setup/">Setting up a Project</a></li>
<li class="toctree-l1"><a class="reference internal" href="../datasets_and_val/">Datasets</a></li>
<li class="toctree-l1"><a class="reference internal" href="../slide_processing/">Slide Processing</a></li>
<li class="toctree-l1"><a class="reference internal" href="../training/">Training</a></li>
<li class="toctree-l1"><a class="reference internal" href="../evaluation/">Evaluation</a></li>
<li class="toctree-l1"><a class="reference internal" href="../posthoc/">Layer Activations</a></li>
<li class="toctree-l1"><a class="reference internal" href="../uq/">Uncertainty Quantification</a></li>
<li class="toctree-l1"><a class="reference internal" href="../features/">Generating Features</a></li>
<li class="toctree-l1"><a class="reference internal" href="../mil/">Multiple-Instance Learning (MIL)</a></li>
<li class="toctree-l1"><a class="reference internal" href="../ssl/">Self-Supervised Learning (SSL)</a></li>
<li class="toctree-l1"><a class="reference internal" href="../stylegan/">Generative Networks (GANs)</a></li>
<li class="toctree-l1"><a class="reference internal" href="../saliency/">Saliency Maps</a></li>
<li class="toctree-l1"><a class="reference internal" href="../segmentation/">Tissue Segmentation</a></li>
<li class="toctree-l1"><a class="reference internal" href="../cellseg/">Cell Segmentation</a></li>
<li class="toctree-l1"><a class="reference internal" href="../custom_loops/">Custom Training Loops</a></li>
<li class="toctree-l1"><a class="reference internal" href="../studio/">Slideflow Studio: Live Visualization</a></li>
<li class="toctree-l1"><a class="reference internal" href="../troubleshooting/">Troubleshooting</a></li>
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<p class="caption" role="heading"><span class="caption-text">Developer Notes</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../tfrecords/">TFRecords: Reading and Writing</a></li>
<li class="toctree-l1"><a class="reference internal" href="../dataloaders/">Dataloaders: Sampling and Augmentation</a></li>
<li class="toctree-l1"><a class="reference internal" href="../custom_extractors/">Custom Feature Extractors</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tile_labels/">Strong Supervision with Tile Labels</a></li>
<li class="toctree-l1"><a class="reference internal" href="../plugins/">Creating a Slideflow Plugin</a></li>
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<p class="caption" role="heading"><span class="caption-text">API</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../slideflow/">slideflow</a></li>
<li class="toctree-l1"><a class="reference internal" href="../project/">slideflow.Project</a></li>
<li class="toctree-l1"><a class="reference internal" href="../dataset/">slideflow.Dataset</a></li>
<li class="toctree-l1"><a class="reference internal" href="../dataset_features/">slideflow.DatasetFeatures</a></li>
<li class="toctree-l1"><a class="reference internal" href="../heatmap/">slideflow.Heatmap</a></li>
<li class="toctree-l1"><a class="reference internal" href="../model_params/">slideflow.ModelParams</a></li>
<li class="toctree-l1"><a class="reference internal" href="../mosaic/">slideflow.Mosaic</a></li>
<li class="toctree-l1"><a class="reference internal" href="../slidemap/">slideflow.SlideMap</a></li>
<li class="toctree-l1"><a class="reference internal" href="../biscuit/">slideflow.biscuit</a></li>
<li class="toctree-l1"><a class="reference internal" href="../slideflow_cellseg/">slideflow.cellseg</a></li>
<li class="toctree-l1"><a class="reference internal" href="../io/">slideflow.io</a></li>
<li class="toctree-l1"><a class="reference internal" href="../io_tensorflow/">slideflow.io.tensorflow</a></li>
<li class="toctree-l1"><a class="reference internal" href="../io_torch/">slideflow.io.torch</a></li>
<li class="toctree-l1"><a class="reference internal" href="../gan/">slideflow.gan</a></li>
<li class="toctree-l1"><a class="reference internal" href="../grad/">slideflow.grad</a></li>
<li class="toctree-l1"><a class="reference internal" href="../mil_module/">slideflow.mil</a></li>
<li class="toctree-l1 current"><a class="current reference internal" href="#">slideflow.model</a></li>
<li class="toctree-l1"><a class="reference internal" href="../model_tensorflow/">slideflow.model.tensorflow</a></li>
<li class="toctree-l1"><a class="reference internal" href="../model_torch/">slideflow.model.torch</a></li>
<li class="toctree-l1"><a class="reference internal" href="../norm/">slideflow.norm</a></li>
<li class="toctree-l1"><a class="reference internal" href="../simclr/">slideflow.simclr</a></li>
<li class="toctree-l1"><a class="reference internal" href="../slide/">slideflow.slide</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../studio_module/">slideflow.studio</a></li>
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<p class="caption" role="heading"><span class="caption-text">Tutorials</span></p>
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<li class="toctree-l1"><a class="reference internal" href="../tutorial1/">Tutorial 1: Model training (simple)</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial2/">Tutorial 2: Model training (advanced)</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial3/">Tutorial 3: Using a custom architecture</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial4/">Tutorial 4: Model evaluation & heatmaps</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial5/">Tutorial 5: Creating a mosaic map</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial6/">Tutorial 6: Custom slide filtering</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial7/">Tutorial 7: Training with custom augmentations</a></li>
<li class="toctree-l1"><a class="reference internal" href="../tutorial8/">Tutorial 8: Multiple-Instance Learning</a></li>
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<section id="slideflow-model">
<h1>slideflow.model<a class="headerlink" href="#slideflow-model" title="Permalink to this heading">¶</a></h1>
<p>This module provides the <code class="xref py py-class docutils literal notranslate"><span class="pre">ModelParams</span></code> class to organize model and training
parameters/hyperparameters and assist with model building, as well as the <a class="reference internal" href="#slideflow.model.Trainer" title="slideflow.model.Trainer"><code class="xref py py-class docutils literal notranslate"><span class="pre">Trainer</span></code></a> class that
executes model training and evaluation. <a class="reference internal" href="#slideflow.model.RegressionTrainer" title="slideflow.model.RegressionTrainer"><code class="xref py py-class docutils literal notranslate"><span class="pre">RegressionTrainer</span></code></a> and <a class="reference internal" href="#slideflow.model.SurvivalTrainer" title="slideflow.model.SurvivalTrainer"><code class="xref py py-class docutils literal notranslate"><span class="pre">SurvivalTrainer</span></code></a>
are extensions of this class, supporting regression and Cox Proportional Hazards outcomes, respectively. The function
<a class="reference internal" href="#slideflow.model.build_trainer" title="slideflow.model.build_trainer"><code class="xref py py-func docutils literal notranslate"><span class="pre">build_trainer()</span></code></a> can choose and return the correct model instance based on the provided
hyperparameters.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>In order to support both Tensorflow and PyTorch backends, the <code class="xref py py-mod docutils literal notranslate"><span class="pre">slideflow.model</span></code> module will import either
<code class="xref py py-mod docutils literal notranslate"><span class="pre">slideflow.model.tensorflow</span></code> or <code class="xref py py-mod docutils literal notranslate"><span class="pre">slideflow.model.torch</span></code> according to the currently active backend,
indicated by the environmental variable <code class="docutils literal notranslate"><span class="pre">SF_BACKEND</span></code>.</p>
</div>
<p>See <a class="reference internal" href="../training/#training"><span class="std std-ref">Training</span></a> for a detailed look at how to train models.</p>
<section id="trainer">
<h2>Trainer<a class="headerlink" href="#trainer" title="Permalink to this heading">¶</a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="slideflow.model.Trainer">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Trainer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">hp</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.model.torch.ModelParams"><span class="pre">ModelParams</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">outdir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">slide_input</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'Trainer'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">feature_sizes</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">feature_names</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">outcome_names</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mixed_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_tf32</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">config</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_neptune</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">neptune_api</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">neptune_workspace</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">load_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'weights'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">custom_objects</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">transform</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Callable" title="(in Python v3.12)"><span class="pre">Callable</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Callable" title="(in Python v3.12)"><span class="pre">Callable</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pin_memory</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">num_workers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">4</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">chunk_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">8</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/model/torch/#Trainer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.Trainer" title="Permalink to this definition">¶</a></dt>
<dd><p>Base trainer class containing functionality for model building, input
processing, training, and evaluation.</p>
<p>This base class requires categorical outcome(s). Additional outcome types
are supported by <a class="reference internal" href="#slideflow.model.RegressionTrainer" title="slideflow.model.RegressionTrainer"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.model.RegressionTrainer</span></code></a> and
<a class="reference internal" href="#slideflow.model.SurvivalTrainer" title="slideflow.model.SurvivalTrainer"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.model.SurvivalTrainer</span></code></a>.</p>
<p>Slide-level (e.g. clinical) features can be used as additional model input
by providing slide labels in the slide annotations dictionary, under
the key ‘input’.</p>
<p>Sets base configuration, preparing model inputs and outputs.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>hp</strong> (<a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.ModelParams"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.ModelParams</span></code></a>) – ModelParams object.</p></li>
<li><p><strong>outdir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Destination for event logs and checkpoints.</p></li>
<li><p><strong>labels</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to outcome labels (int or
float format).</p></li>
<li><p><strong>slide_input</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to additional
slide-level input, concatenated after post-conv.</p></li>
<li><p><strong>name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Optional name describing the model, used for
model saving. Defaults to None.</p></li>
<li><p><strong>feature_sizes</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of sizes of input features.
Required if providing additional input features as model input.</p></li>
<li><p><strong>feature_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of names for input features.
Used when permuting feature importance.</p></li>
<li><p><strong>outcome_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – Name of each outcome. Defaults to
“Outcome {X}” for each outcome.</p></li>
<li><p><strong>mixed_precision</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use FP16 mixed precision (rather
than FP32). Defaults to True.</p></li>
<li><p><strong>allow_tf32</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Allow internal use of Tensorfloat-32 format.
Defaults to False.</p></li>
<li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Training configuration dictionary, used
for logging and image format verification. Defaults to None.</p></li>
<li><p><strong>use_neptune</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use Neptune API logging.
Defaults to False</p></li>
<li><p><strong>neptune_api</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune API token, used for logging.
Defaults to None.</p></li>
<li><p><strong>neptune_workspace</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune workspace.
Defaults to None.</p></li>
<li><p><strong>load_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Loading method to use when reading model.
This argument is ignored in the PyTorch backend, as all models
are loaded by first building the model with hyperparameters
detected in <code class="docutils literal notranslate"><span class="pre">params.json</span></code>, then loading weights with
<code class="docutils literal notranslate"><span class="pre">torch.nn.Module.load_state_dict()</span></code>. Defaults to
‘full’ (ignored).</p></li>
<li><p><strong>transform</strong> (<em>callable</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Optional transform to
apply to input images. If dict, must have the keys ‘train’
and/or ‘val’, mapping to callables that takes a single
image Tensor as input and returns a single image Tensor.
If None, no transform is applied. If a single callable is
provided, it will be applied to both training and validation
data. If a dict is provided, the ‘train’ transform will be
applied to training data and the ‘val’ transform will be
applied to validation data. If a dict is provided and either
‘train’ or ‘val’ is None, no transform will be applied to
that data. Defaults to None.</p></li>
<li><p><strong>pin_memory</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Set the <code class="docutils literal notranslate"><span class="pre">pin_memory</span></code> attribute for dataloaders.
Defaults to True.</p></li>
<li><p><strong>num_workers</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Set the number of workers for dataloaders.
Defaults to 4.</p></li>
<li><p><strong>chunk_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Set the chunk size for TFRecord reading.
Defaults to 8.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.Trainer.load">
<span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">training</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span></span><a class="headerlink" href="#slideflow.model.Trainer.load" title="Permalink to this definition">¶</a></dt>
<dd><p>Loads a state dict at the given model location. Requires that the
Trainer’s hyperparameters (Trainer.hp)
match the hyperparameters of the model to be loaded.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.Trainer.evaluate">
<span class="sig-name descname"><span class="pre">evaluate</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_predictions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'parquet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reduce_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Callable" title="(in Python v3.12)"><span class="pre">Callable</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'average'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm_fit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">uq</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">from_wsi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">roi_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.model.Trainer.evaluate" title="Permalink to this definition">¶</a></dt>
<dd><p>Evaluate model, saving metrics and predictions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>dataset</strong> (<a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.dataset.Dataset</span></code></a>) – Dataset to evaluate.</p></li>
<li><p><strong>batch_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Evaluation batch size. Defaults to the
same as training (per self.hp)</p></li>
<li><p><strong>save_predictions</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Save tile, slide, and
patient-level predictions at each evaluation. May be ‘csv’,
‘feather’, or ‘parquet’. If False, will not save predictions.
Defaults to ‘parquet’.</p></li>
<li><p><strong>reduce_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Reduction method for calculating
slide-level and patient-level predictions for categorical
outcomes. Options include ‘average’, ‘mean’, ‘proportion’,
‘median’, ‘sum’, ‘min’, ‘max’, or a callable function.
‘average’ and ‘mean’ are synonymous, with both options kept
for backwards compatibility. If ‘average’ or ‘mean’, will
reduce with average of each logit across tiles. If
‘proportion’, will convert tile predictions into onehot encoding
then reduce by averaging these onehot values. For all other
values, will reduce with the specified function, applied via
the pandas <code class="docutils literal notranslate"><span class="pre">DataFrame.agg()</span></code> function. Defaults to ‘average’.</p></li>
<li><p><strong>norm_fit</strong> (<em>Dict</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>np.ndarray</em><em>]</em>) – Normalizer fit, mapping fit
parameters (e.g. target_means, target_stds) to values
(np.ndarray). If not provided, will fit normalizer using
model params (if applicable). Defaults to None.</p></li>
<li><p><strong>uq</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Enable UQ estimation (for
applicable models). Defaults to ‘auto’.</p></li>
<li><p><strong>from_wsi</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Generate predictions from tiles dynamically
extracted from whole-slide images, rather than TFRecords.
Defaults to False (use TFRecords).</p></li>
<li><p><strong>roi_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – ROI method to use if from_wsi=True (ignored if
from_wsi=False). Either ‘inside’, ‘outside’, ‘auto’, ‘ignore’.
If ‘inside’ or ‘outside’, will extract tiles in/out of an ROI,
and raise errors.MissingROIError if an ROI is not available.
If ‘auto’, will extract tiles inside an ROI if available,
and across the whole-slide if no ROI is found.
If ‘ignore’, will extract tiles across the whole-slide
regardless of whether an ROI is available.
Defaults to ‘auto’.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Dictionary of evaluation metrics.</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.Trainer.predict">
<span class="sig-name descname"><span class="pre">predict</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dataset</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm_fit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">format</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'parquet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">from_wsi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">roi_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reduce_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Callable" title="(in Python v3.12)"><span class="pre">Callable</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'average'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">DataFrame</span><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#slideflow.model.Trainer.predict" title="Permalink to this definition">¶</a></dt>
<dd><p>Perform inference on a model, saving predictions.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>dataset</strong> (<a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.dataset.Dataset</span></code></a>) – Dataset containing
TFRecords to evaluate.</p></li>
<li><p><strong>batch_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Evaluation batch size. Defaults to the
same as training (per self.hp)</p></li>
<li><p><strong>norm_fit</strong> (<em>Dict</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>np.ndarray</em><em>]</em>) – Normalizer fit, mapping fit
parameters (e.g. target_means, target_stds) to values
(np.ndarray). If not provided, will fit normalizer using
model params (if applicable). Defaults to None.</p></li>
<li><p><strong>format</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Format in which to save predictions. Either
‘csv’, ‘feather’, or ‘parquet’. Defaults to ‘parquet’.</p></li>
<li><p><strong>from_wsi</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Generate predictions from tiles dynamically
extracted from whole-slide images, rather than TFRecords.
Defaults to False (use TFRecords).</p></li>
<li><p><strong>roi_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – ROI method to use if from_wsi=True (ignored if
from_wsi=False). Either ‘inside’, ‘outside’, ‘auto’, ‘ignore’.
If ‘inside’ or ‘outside’, will extract tiles in/out of an ROI,
and raise errors.MissingROIError if an ROI is not available.
If ‘auto’, will extract tiles inside an ROI if available,
and across the whole-slide if no ROI is found.
If ‘ignore’, will extract tiles across the whole-slide
regardless of whether an ROI is available.
Defaults to ‘auto’.</p></li>
<li><p><strong>reduce_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Reduction method for calculating
slide-level and patient-level predictions for categorical
outcomes. Options include ‘average’, ‘mean’, ‘proportion’,
‘median’, ‘sum’, ‘min’, ‘max’, or a callable function.
‘average’ and ‘mean’ are synonymous, with both options kept
for backwards compatibility. If ‘average’ or ‘mean’, will
reduce with average of each logit across tiles. If
‘proportion’, will convert tile predictions into onehot encoding
then reduce by averaging these onehot values. For all other
values, will reduce with the specified function, applied via
the pandas <code class="docutils literal notranslate"><span class="pre">DataFrame.agg()</span></code> function. Defaults to ‘average’.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Dictionary with keys ‘tile’, ‘slide’, and
‘patient’, and values containing DataFrames with tile-, slide-,
and patient-level predictions.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Dict[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)">str</a>, pd.DataFrame]</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.Trainer.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">train_dts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">val_dts</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><span class="pre">Dataset</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">log_frequency</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validate_on_batch</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_batch_size</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">validation_steps</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">50</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">starting_epoch</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ema_observations</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">20</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">ema_smoothing</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">2</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_tensorboard</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">steps_per_epoch_override</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_predictions</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'parquet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">resume_training</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pretrain</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'imagenet'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">checkpoint</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">save_checkpoints</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">multi_gpu</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">norm_fit</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">reduce_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Callable" title="(in Python v3.12)"><span class="pre">Callable</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'average'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">seed</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">from_wsi</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">roi_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'auto'</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="headerlink" href="#slideflow.model.Trainer.train" title="Permalink to this definition">¶</a></dt>
<dd><p>Builds and trains a model from hyperparameters.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>train_dts</strong> (<a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.dataset.Dataset</span></code></a>) – Training dataset.</p></li>
<li><p><strong>val_dts</strong> (<a class="reference internal" href="../dataset/#slideflow.Dataset" title="slideflow.dataset.Dataset"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.dataset.Dataset</span></code></a>) – Validation dataset.</p></li>
<li><p><strong>log_frequency</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – How frequent to update Tensorboard
logs, in batches. Defaults to 100.</p></li>
<li><p><strong>validate_on_batch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Validation will be performed
every N batches. Defaults to 0.</p></li>
<li><p><strong>validation_batch_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Validation batch size.
Defaults to same as training (per self.hp).</p></li>
<li><p><strong>validation_steps</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Number of batches to use for each
instance of validation. Defaults to 200.</p></li>
<li><p><strong>starting_epoch</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Starts training at this epoch.
Defaults to 0.</p></li>
<li><p><strong>ema_observations</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Number of observations over which
to perform exponential moving average smoothing.
Defaults to 20.</p></li>
<li><p><strong>ema_smoothing</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Exponential average smoothing value.
Defaults to 2.</p></li>
<li><p><strong>use_tensoboard</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Enable tensorboard callbacks.
Defaults to False.</p></li>
<li><p><strong>steps_per_epoch_override</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a><em>, </em><em>optional</em>) – Manually set the number
of steps per epoch. Defaults to None.</p></li>
<li><p><strong>save_predictions</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Save tile, slide, and
patient-level predictions at each evaluation. May be ‘csv’,
‘feather’, or ‘parquet’. If False, will not save predictions.
Defaults to ‘parquet’.</p></li>
<li><p><strong>save_model</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Save models when evaluating at
specified epochs. Defaults to False.</p></li>
<li><p><strong>resume_training</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Not applicable to PyTorch backend.
Included as argument for compatibility with Tensorflow backend.
Will raise NotImplementedError if supplied.</p></li>
<li><p><strong>pretrain</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Either ‘imagenet’ or path to Tensorflow
model from which to load weights. Defaults to ‘imagenet’.</p></li>
<li><p><strong>checkpoint</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Path to cp.ckpt from which to load
weights. Defaults to None.</p></li>
<li><p><strong>norm_fit</strong> (<em>Dict</em><em>[</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>np.ndarray</em><em>]</em>) – Normalizer fit, mapping fit
parameters (e.g. target_means, target_stds) to values
(np.ndarray). If not provided, will fit normalizer using
model params (if applicable). Defaults to None.</p></li>
<li><p><strong>reduce_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Reduction method for calculating
slide-level and patient-level predictions for categorical
outcomes. Options include ‘average’, ‘mean’, ‘proportion’,
‘median’, ‘sum’, ‘min’, ‘max’, or a callable function.
‘average’ and ‘mean’ are synonymous, with both options kept
for backwards compatibility. If ‘average’ or ‘mean’, will
reduce with average of each logit across tiles. If
‘proportion’, will convert tile predictions into onehot encoding
then reduce by averaging these onehot values. For all other
values, will reduce with the specified function, applied via
the pandas <code class="docutils literal notranslate"><span class="pre">DataFrame.agg()</span></code> function. Defaults to ‘average’.</p></li>
<li><p><strong>seed</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Set numpy random seed. Defaults to 0.</p></li>
<li><p><strong>from_wsi</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Generate predictions from tiles dynamically
extracted from whole-slide images, rather than TFRecords.
Defaults to False (use TFRecords).</p></li>
<li><p><strong>roi_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – ROI method to use if from_wsi=True (ignored if
from_wsi=False). Either ‘inside’, ‘outside’, ‘auto’, ‘ignore’.
If ‘inside’ or ‘outside’, will extract tiles in/out of an ROI,
and raise errors.MissingROIError if an ROI is not available.
If ‘auto’, will extract tiles inside an ROI if available,
and across the whole-slide if no ROI is found.
If ‘ignore’, will extract tiles across the whole-slide
regardless of whether an ROI is available.
Defaults to ‘auto’.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Nested dict containing metrics for each evaluated epoch.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Dict</p>
</dd>
</dl>
</dd></dl>
</section>
<section id="regressiontrainer">
<h2>RegressionTrainer<a class="headerlink" href="#regressiontrainer" title="Permalink to this heading">¶</a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="slideflow.model.RegressionTrainer">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">RegressionTrainer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/model/torch/#RegressionTrainer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.RegressionTrainer" title="Permalink to this definition">¶</a></dt>
<dd><p>Extends the base <a class="reference internal" href="#slideflow.model.Trainer" title="slideflow.model.Trainer"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.model.Trainer</span></code></a> class to add support
for continuous outcomes. Requires that all outcomes be continuous, with appropriate
regression loss function. Uses R-squared as the evaluation metric, rather
than AUROC.</p>
<p>In this case, for the PyTorch backend, the continuous outcomes support is
already baked into the base Trainer class, so no additional modifications
are required. This class is written to inherit the Trainer class without
modification to maintain consistency with the Tensorflow backend.</p>
<p>Sets base configuration, preparing model inputs and outputs.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>hp</strong> (<a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.ModelParams"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.ModelParams</span></code></a>) – ModelParams object.</p></li>
<li><p><strong>outdir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Destination for event logs and checkpoints.</p></li>
<li><p><strong>labels</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to outcome labels (int or
float format).</p></li>
<li><p><strong>slide_input</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to additional
slide-level input, concatenated after post-conv.</p></li>
<li><p><strong>name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Optional name describing the model, used for
model saving. Defaults to None.</p></li>
<li><p><strong>feature_sizes</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of sizes of input features.
Required if providing additional input features as model input.</p></li>
<li><p><strong>feature_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of names for input features.
Used when permuting feature importance.</p></li>
<li><p><strong>outcome_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – Name of each outcome. Defaults to
“Outcome {X}” for each outcome.</p></li>
<li><p><strong>mixed_precision</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use FP16 mixed precision (rather
than FP32). Defaults to True.</p></li>
<li><p><strong>allow_tf32</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Allow internal use of Tensorfloat-32 format.
Defaults to False.</p></li>
<li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Training configuration dictionary, used
for logging and image format verification. Defaults to None.</p></li>
<li><p><strong>use_neptune</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use Neptune API logging.
Defaults to False</p></li>
<li><p><strong>neptune_api</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune API token, used for logging.
Defaults to None.</p></li>
<li><p><strong>neptune_workspace</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune workspace.
Defaults to None.</p></li>
<li><p><strong>load_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Loading method to use when reading model.
This argument is ignored in the PyTorch backend, as all models
are loaded by first building the model with hyperparameters
detected in <code class="docutils literal notranslate"><span class="pre">params.json</span></code>, then loading weights with
<code class="docutils literal notranslate"><span class="pre">torch.nn.Module.load_state_dict()</span></code>. Defaults to
‘full’ (ignored).</p></li>
<li><p><strong>transform</strong> (<em>callable</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Optional transform to
apply to input images. If dict, must have the keys ‘train’
and/or ‘val’, mapping to callables that takes a single
image Tensor as input and returns a single image Tensor.
If None, no transform is applied. If a single callable is
provided, it will be applied to both training and validation
data. If a dict is provided, the ‘train’ transform will be
applied to training data and the ‘val’ transform will be
applied to validation data. If a dict is provided and either
‘train’ or ‘val’ is None, no transform will be applied to
that data. Defaults to None.</p></li>
<li><p><strong>pin_memory</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Set the <code class="docutils literal notranslate"><span class="pre">pin_memory</span></code> attribute for dataloaders.
Defaults to True.</p></li>
<li><p><strong>num_workers</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Set the number of workers for dataloaders.
Defaults to 4.</p></li>
<li><p><strong>chunk_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Set the chunk size for TFRecord reading.
Defaults to 8.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</section>
<section id="survivaltrainer">
<h2>SurvivalTrainer<a class="headerlink" href="#survivaltrainer" title="Permalink to this heading">¶</a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="slideflow.model.SurvivalTrainer">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">SurvivalTrainer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/model/torch/#SurvivalTrainer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.SurvivalTrainer" title="Permalink to this definition">¶</a></dt>
<dd><p>Cox proportional hazards (CPH) models are not yet implemented, but are
planned for a future update.</p>
<p>Sets base configuration, preparing model inputs and outputs.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>hp</strong> (<a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.ModelParams"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.ModelParams</span></code></a>) – ModelParams object.</p></li>
<li><p><strong>outdir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Destination for event logs and checkpoints.</p></li>
<li><p><strong>labels</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to outcome labels (int or
float format).</p></li>
<li><p><strong>slide_input</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to additional
slide-level input, concatenated after post-conv.</p></li>
<li><p><strong>name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Optional name describing the model, used for
model saving. Defaults to None.</p></li>
<li><p><strong>feature_sizes</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of sizes of input features.
Required if providing additional input features as model input.</p></li>
<li><p><strong>feature_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of names for input features.
Used when permuting feature importance.</p></li>
<li><p><strong>outcome_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – Name of each outcome. Defaults to
“Outcome {X}” for each outcome.</p></li>
<li><p><strong>mixed_precision</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use FP16 mixed precision (rather
than FP32). Defaults to True.</p></li>
<li><p><strong>allow_tf32</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Allow internal use of Tensorfloat-32 format.
Defaults to False.</p></li>
<li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Training configuration dictionary, used
for logging and image format verification. Defaults to None.</p></li>
<li><p><strong>use_neptune</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use Neptune API logging.
Defaults to False</p></li>
<li><p><strong>neptune_api</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune API token, used for logging.
Defaults to None.</p></li>
<li><p><strong>neptune_workspace</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune workspace.
Defaults to None.</p></li>
<li><p><strong>load_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Loading method to use when reading model.
This argument is ignored in the PyTorch backend, as all models
are loaded by first building the model with hyperparameters
detected in <code class="docutils literal notranslate"><span class="pre">params.json</span></code>, then loading weights with
<code class="docutils literal notranslate"><span class="pre">torch.nn.Module.load_state_dict()</span></code>. Defaults to
‘full’ (ignored).</p></li>
<li><p><strong>transform</strong> (<em>callable</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Optional transform to
apply to input images. If dict, must have the keys ‘train’
and/or ‘val’, mapping to callables that takes a single
image Tensor as input and returns a single image Tensor.
If None, no transform is applied. If a single callable is
provided, it will be applied to both training and validation
data. If a dict is provided, the ‘train’ transform will be
applied to training data and the ‘val’ transform will be
applied to validation data. If a dict is provided and either
‘train’ or ‘val’ is None, no transform will be applied to
that data. Defaults to None.</p></li>
<li><p><strong>pin_memory</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Set the <code class="docutils literal notranslate"><span class="pre">pin_memory</span></code> attribute for dataloaders.
Defaults to True.</p></li>
<li><p><strong>num_workers</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Set the number of workers for dataloaders.
Defaults to 4.</p></li>
<li><p><strong>chunk_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Set the chunk size for TFRecord reading.
Defaults to 8.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
</section>
<section id="features">
<h2>Features<a class="headerlink" href="#features" title="Permalink to this heading">¶</a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="slideflow.model.Features">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">Features</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">layers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'postconv'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_preds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mixed_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">channels_last</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">device</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">device</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">apply_softmax</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pooling</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">load_method</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'weights'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/model/torch/#Features"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.Features" title="Permalink to this definition">¶</a></dt>
<dd><p>Interface for obtaining predictions and features from intermediate layer
activations from Slideflow models.</p>
<p>Use by calling on either a batch of images (returning outputs for a single
batch), or by calling on a <code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.WSI</span></code> object, which will
generate an array of spatially-mapped activations matching the slide.</p>
<dl>
<dt>Examples</dt><dd><p><em>Calling on batch of images:</em></p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">interface</span> <span class="o">=</span> <span class="n">Features</span><span class="p">(</span><span class="s1">'/model/path'</span><span class="p">,</span> <span class="n">layers</span><span class="o">=</span><span class="s1">'postconv'</span><span class="p">)</span>
<span class="k">for</span> <span class="n">image_batch</span> <span class="ow">in</span> <span class="n">train_data</span><span class="p">:</span>
<span class="c1"># Return shape: (batch_size, num_features)</span>
<span class="n">batch_features</span> <span class="o">=</span> <span class="n">interface</span><span class="p">(</span><span class="n">image_batch</span><span class="p">)</span>
</pre></div>
</div>
<p><em>Calling on a slide:</em></p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">slide</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">slide</span><span class="o">.</span><span class="n">WSI</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="n">interface</span> <span class="o">=</span> <span class="n">Features</span><span class="p">(</span><span class="s1">'/model/path'</span><span class="p">,</span> <span class="n">layers</span><span class="o">=</span><span class="s1">'postconv'</span><span class="p">)</span>
<span class="c1"># Return shape:</span>
<span class="c1"># (slide.grid.shape[0], slide.grid.shape[1], num_features)</span>
<span class="n">activations_grid</span> <span class="o">=</span> <span class="n">interface</span><span class="p">(</span><span class="n">slide</span><span class="p">)</span>
</pre></div>
</div>
</dd>
</dl>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>When this interface is called on a batch of images, no image processing
or stain normalization will be performed, as it is assumed that
normalization will occur during data loader image processing. When the
interface is called on a <cite>slideflow.WSI</cite>, the normalization strategy
will be read from the model configuration file, and normalization will
be performed on image tiles extracted from the WSI. If this interface
was created from an existing model and there is no model configuration
file to read, a slideflow.norm.StainNormalizer object may be passed
during initialization via the argument <cite>wsi_normalizer</cite>.</p>
</div>
<p>Creates an activations interface from a saved slideflow model which
outputs feature activations at the designated layers.</p>
<p>Intermediate layers are returned in the order of layers.
predictions are returned last.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>path</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Path to saved Slideflow model.</p></li>
<li><p><strong>layers</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>(</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>)</em><em>, </em><em>optional</em>) – Layers from which to generate
activations. The post-convolution activation layer is accessed
via ‘postconv’. Defaults to ‘postconv’.</p></li>
<li><p><strong>include_preds</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Include predictions in output. Will be
returned last. Defaults to False.</p></li>
<li><p><strong>mixed_precision</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use mixed precision.
Defaults to True.</p></li>
<li><p><strong>device</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">torch.device</span></code>, optional) – Device for model.
Defaults to torch.device(‘cuda’)</p></li>
<li><p><strong>apply_softmax</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Apply softmax transformation to model output.
Defaults to True for classification models, False for regression models.</p></li>
<li><p><strong>pooling</strong> (<em>Callable</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – PyTorch pooling function to use
on feature layers. May be a string (‘avg’ or ‘max’) or a
callable PyTorch function.</p></li>
<li><p><strong>load_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Loading method to use when reading model.
This argument is ignored in the PyTorch backend, as all models
are loaded by first building the model with hyperparameters
detected in <code class="docutils literal notranslate"><span class="pre">params.json</span></code>, then loading weights with
<code class="docutils literal notranslate"><span class="pre">torch.nn.Module.load_state_dict()</span></code>. Defaults to
‘full’ (ignored).</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.Features.from_model">
<span class="sig-name descname"><span class="pre">from_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Module</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tile_px</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><span class="pre">int</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">layers</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'postconv'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">include_preds</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mixed_precision</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">channels_last</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">wsi_normalizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../norm/#slideflow.norm.StainNormalizer" title="slideflow.norm.StainNormalizer"><span class="pre">StainNormalizer</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">apply_softmax</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">pooling</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#slideflow.model.Features.from_model" title="Permalink to this definition">¶</a></dt>
<dd><p>Creates an activations interface from a loaded slideflow model which
outputs feature activations at the designated layers.</p>
<p>Intermediate layers are returned in the order of layers.
predictions are returned last.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>model</strong> (<code class="xref py py-class docutils literal notranslate"><span class="pre">tensorflow.keras.models.Model</span></code>) – Loaded model.</p></li>
<li><p><strong>tile_px</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Width/height of input image size.</p></li>
<li><p><strong>layers</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>(</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>)</em><em>, </em><em>optional</em>) – Layers from which to generate
activations. The post-convolution activation layer is accessed
via ‘postconv’. Defaults to ‘postconv’.</p></li>
<li><p><strong>include_preds</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Include predictions in output. Will be
returned last. Defaults to False.</p></li>
<li><p><strong>mixed_precision</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use mixed precision.
Defaults to True.</p></li>
<li><p><strong>wsi_normalizer</strong> (<a class="reference internal" href="../norm/#slideflow.norm.StainNormalizer" title="slideflow.norm.StainNormalizer"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.norm.StainNormalizer</span></code></a>) – Stain
normalizer to use on whole-slide images. Is not used on
individual tile datasets via __call__. Defaults to None.</p></li>
<li><p><strong>apply_softmax</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Apply softmax transformation to model output.
Defaults to True.</p></li>
<li><p><strong>pooling</strong> (<em>Callable</em><em> or </em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – PyTorch pooling function to use
on feature layers. May be a string (‘avg’ or ‘max’) or a
callable PyTorch function.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.Features.__call__">
<span class="sig-name descname"><span class="pre">__call__</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">self</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">inp</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tensor</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference internal" href="../slide/#slideflow.slide.WSI" title="slideflow.slide.wsi.WSI"><span class="pre">WSI</span></a></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">[</span></span><span class="pre">Tensor</span><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><span class="pre">ndarray</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span></span><a class="headerlink" href="#slideflow.model.Features.__call__" title="Permalink to this definition">¶</a></dt>
<dd><p>Process a given input and return activations and/or predictions. Expects
either a batch of images or a <a class="reference internal" href="../slide/#slideflow.slide.WSI" title="slideflow.slide.WSI"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.slide.WSI</span></code></a> object.</p>
<p>When calling on a <cite>WSI</cite> object, keyword arguments are passed to
<a class="reference internal" href="../slide/#slideflow.WSI.build_generator" title="slideflow.WSI.build_generator"><code class="xref py py-meth docutils literal notranslate"><span class="pre">slideflow.WSI.build_generator()</span></code></a>.</p>
</dd></dl>
</section>
<section id="other-functions">
<h2>Other functions<a class="headerlink" href="#other-functions" title="Permalink to this heading">¶</a></h2>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.build_trainer">
<span class="sig-name descname"><span class="pre">build_trainer</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">hp</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.model.torch.ModelParams"><span class="pre">ModelParams</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">outdir</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">labels</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a><span class="p"><span class="pre">]</span></span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference internal" href="#slideflow.model.Trainer" title="slideflow.model.torch.Trainer"><span class="pre">Trainer</span></a></span></span><a class="reference internal" href="../_modules/slideflow/model/#build_trainer"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.build_trainer" title="Permalink to this definition">¶</a></dt>
<dd><p>From the given <a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.ModelParams"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.ModelParams</span></code></a> object, returns
the appropriate instance of <a class="reference internal" href="#slideflow.model.Trainer" title="slideflow.model.Trainer"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.model.Trainer</span></code></a>.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>hp</strong> (<a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.ModelParams"><code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.ModelParams</span></code></a>) – ModelParams object.</p></li>
<li><p><strong>outdir</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Path for event logs and checkpoints.</p></li>
<li><p><strong>labels</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to outcome labels (int or
float format).</p></li>
</ul>
</dd>
<dt class="field-even">Keyword Arguments<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>slide_input</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a>) – Dict mapping slide names to additional
slide-level input, concatenated after post-conv.</p></li>
<li><p><strong>name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Optional name describing the model, used for
model saving. Defaults to ‘Trainer’.</p></li>
<li><p><strong>feature_sizes</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of sizes of input features.
Required if providing additional input features as input to
the model.</p></li>
<li><p><strong>feature_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – List of names for input features.
Used when permuting feature importance.</p></li>
<li><p><strong>outcome_names</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>, </em><em>optional</em>) – Name of each outcome. Defaults to
“Outcome {X}” for each outcome.</p></li>
<li><p><strong>mixed_precision</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use FP16 mixed precision (rather
than FP32). Defaults to True.</p></li>
<li><p><strong>allow_tf32</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – Allow internal use of Tensorfloat-32 format.
Defaults to False.</p></li>
<li><p><strong>config</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>optional</em>) – Training configuration dictionary, used
for logging. Defaults to None.</p></li>
<li><p><strong>use_neptune</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Use Neptune API logging.
Defaults to False</p></li>
<li><p><strong>neptune_api</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune API token, used for logging.
Defaults to None.</p></li>
<li><p><strong>neptune_workspace</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>, </em><em>optional</em>) – Neptune workspace.
Defaults to None.</p></li>
<li><p><strong>load_method</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Either ‘full’ or ‘weights’. Method to use
when loading a Tensorflow model. If ‘full’, loads the model with
<code class="docutils literal notranslate"><span class="pre">tf.keras.models.load_model()</span></code>. If ‘weights’, will read the
<code class="docutils literal notranslate"><span class="pre">params.json</span></code> configuration file, build the model architecture,
and then load weights from the given model with
<code class="docutils literal notranslate"><span class="pre">Model.load_weights()</span></code>. Loading with ‘full’ may improve
compatibility across Slideflow versions. Loading with ‘weights’
may improve compatibility across hardware & environments.</p></li>
<li><p><strong>custom_objects</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.12)"><em>dict</em></a><em>, </em><em>Optional</em>) – Dictionary mapping names
(strings) to custom classes or functions. Defaults to None.</p></li>
<li><p><strong>num_workers</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Number of dataloader workers. Only used for PyTorch.
Defaults to 4.</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.build_feature_extractor">
<span class="sig-name descname"><span class="pre">build_feature_extractor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">backend</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">BaseFeatureExtractor</span></span></span><a class="reference internal" href="../_modules/slideflow/model/extractors/_factory/#build_feature_extractor"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.build_feature_extractor" title="Permalink to this definition">¶</a></dt>
<dd><p>Build a feature extractor.</p>
<p>The returned feature extractor is a callable object, which returns
features (often layer activations) for either a batch of images or a
<code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.WSI</span></code> object.</p>
<p>If generating features for a batch of images, images are expected to be in
(B, W, H, C) format and non-standardized (scaled 0-255) with dtype uint8.
The feature extractors perform all needed preprocessing on the fly.</p>
<p>If generating features for a slide, the slide is expected to be a
<code class="xref py py-class docutils literal notranslate"><span class="pre">slideflow.WSI</span></code> object. The feature extractor will generate features
for each tile in the slide, returning a numpy array of shape (W, H, F),
where F is the number of features.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>name</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Name of the feature extractor to build. Available
feature extractors are listed with
<a class="reference internal" href="#slideflow.model.list_extractors" title="slideflow.model.list_extractors"><code class="xref py py-func docutils literal notranslate"><span class="pre">slideflow.model.list_extractors()</span></code></a>.</p>
</dd>
<dt class="field-even">Keyword Arguments<span class="colon">:</span></dt>
<dd class="field-even"><ul class="simple">
<li><p><strong>tile_px</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><em>int</em></a>) – Tile size (input image size), in pixels.</p></li>
<li><p><strong>**kwargs</strong> (<em>Any</em>) – All remaining keyword arguments are passed
to the feature extractor factory function, and may be different
for each extractor.</p></li>
</ul>
</dd>
<dt class="field-odd">Returns<span class="colon">:</span></dt>
<dd class="field-odd"><p>A callable object which accepts a batch of images (B, W, H, C) of dtype
uint8 and returns a batch of features (dtype float32).</p>
</dd>
</dl>
<dl>
<dt>Examples</dt><dd><p>Create an extractor that calculates post-convolutional layer activations
from an imagenet-pretrained Resnet50 model.</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">slideflow</span> <span class="k">as</span> <span class="nn">sf</span>
<span class="n">extractor</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">build_feature_extractor</span><span class="p">(</span>
<span class="s1">'resnet50_imagenet'</span>
<span class="p">)</span>
</pre></div>
</div>
</div></blockquote>
<p>Create an extractor that calculates ‘conv4_block4_2_relu’ activations
from an imagenet-pretrained Resnet50 model.</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">extractor</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">build_feature_extractor</span><span class="p">(</span>
<span class="s1">'resnet50_imagenet'</span><span class="p">,</span>
<span class="n">layers</span><span class="o">=</span><span class="s1">'conv4_block4_2_relu</span>
<span class="p">)</span>
</pre></div>
</div>
</div></blockquote>
<p>Create a pretrained “CTransPath” extractor.</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">extractor</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">build_feature_extractor</span><span class="p">(</span><span class="s1">'ctranspath'</span><span class="p">)</span>
</pre></div>
</div>
</div></blockquote>
<p>Use an extractor to calculate layer activations for an entire dataset.</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">slideflow</span> <span class="k">as</span> <span class="nn">sf</span>
<span class="c1"># Load a project and dataset</span>
<span class="n">P</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">load_project</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="n">dataset</span> <span class="o">=</span> <span class="n">P</span><span class="o">.</span><span class="n">dataset</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="c1"># Create a feature extractor</span>
<span class="n">resnet</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">build_feature_extractor</span><span class="p">(</span>
<span class="s1">'resnet50_imagenet'</span>
<span class="p">)</span>
<span class="c1"># Calculate features for the entire dataset</span>
<span class="n">features</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">DatasetFeatures</span><span class="p">(</span>
<span class="n">resnet</span><span class="p">,</span>
<span class="n">dataset</span><span class="o">=</span><span class="n">dataset</span>
<span class="p">)</span>
</pre></div>
</div>
</div></blockquote>
<p>Generate a map of features across a slide.</p>
<blockquote>
<div><div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">slideflow</span> <span class="k">as</span> <span class="nn">sf</span>
<span class="c1"># Load a slide</span>
<span class="n">wsi</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">WSI</span><span class="p">(</span><span class="o">...</span><span class="p">)</span>
<span class="c1"># Create a feature extractor</span>
<span class="n">retccl</span> <span class="o">=</span> <span class="n">sf</span><span class="o">.</span><span class="n">build_feature_extractor</span><span class="p">(</span>
<span class="s1">'retccl'</span><span class="p">,</span>
<span class="n">resize</span><span class="o">=</span><span class="kc">True</span>
<span class="p">)</span>
<span class="c1"># Create a feature map, a 2D array of shape</span>
<span class="c1"># (W, H, F), where F is the number of features.</span>
<span class="n">features</span> <span class="o">=</span> <span class="n">retccl</span><span class="p">(</span><span class="n">wsi</span><span class="p">)</span>
</pre></div>
</div>
</div></blockquote>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.list_extractors">
<span class="sig-name descname"><span class="pre">list_extractors</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/slideflow/model/extractors/_registry/#list_extractors"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.list_extractors" title="Permalink to this definition">¶</a></dt>
<dd><p>Return a list of all available feature extractors.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.load">
<span class="sig-name descname"><span class="pre">load</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">path</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><span class="pre">Module</span></span></span><a class="reference internal" href="../_modules/slideflow/model/torch/#load"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.load" title="Permalink to this definition">¶</a></dt>
<dd><p>Load a model trained with Slideflow.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><p><strong>path</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Path to saved model. Must be a model trained in Slideflow.</p>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>Loaded model.</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>torch.nn.Module</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.is_tensorflow_model">
<span class="sig-name descname"><span class="pre">is_tensorflow_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span></span><a class="reference internal" href="../_modules/slideflow/model/#is_tensorflow_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.is_tensorflow_model" title="Permalink to this definition">¶</a></dt>
<dd><p>Checks if the object is a Tensorflow Model or path to Tensorflow model.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.is_tensorflow_tensor">
<span class="sig-name descname"><span class="pre">is_tensorflow_tensor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span></span><a class="reference internal" href="../_modules/slideflow/model/#is_tensorflow_tensor"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.is_tensorflow_tensor" title="Permalink to this definition">¶</a></dt>
<dd><p>Checks if the given object is a Tensorflow Tensor.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.is_torch_model">
<span class="sig-name descname"><span class="pre">is_torch_model</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span></span><a class="reference internal" href="../_modules/slideflow/model/#is_torch_model"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.is_torch_model" title="Permalink to this definition">¶</a></dt>
<dd><p>Checks if the object is a PyTorch Module or path to PyTorch model.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.is_torch_tensor">
<span class="sig-name descname"><span class="pre">is_torch_tensor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">arg</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><span class="pre">Any</span></a></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span></span><a class="reference internal" href="../_modules/slideflow/model/#is_torch_tensor"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.is_torch_tensor" title="Permalink to this definition">¶</a></dt>
<dd><p>Checks if the given object is a Tensorflow Tensor.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.read_hp_sweep">
<span class="sig-name descname"><span class="pre">read_hp_sweep</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">models</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><span class="pre">List</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">]</span></span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><span class="pre">Dict</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="../model_params/#slideflow.ModelParams" title="slideflow.model.torch.ModelParams"><span class="pre">ModelParams</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/slideflow/model/#read_hp_sweep"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.read_hp_sweep" title="Permalink to this definition">¶</a></dt>
<dd><p>Organizes a list of hyperparameters ojects and associated models names.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>filename</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Path to hyperparameter sweep JSON file.</p></li>
<li><p><strong>models</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.12)"><em>list</em></a><em>(</em><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a><em>)</em>) – List of model names. Defaults to None.
If not supplied, returns all valid models from batch file.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p>List of (Hyperparameter, model_name) for each HP combination</p>
</dd>
</dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="slideflow.model.rebuild_extractor">
<span class="sig-name descname"><span class="pre">rebuild_extractor</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">bags_or_model</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><span class="pre">str</span></a></span></em>, <em class="sig-param"><span class="n"><span class="pre">allow_errors</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">native_normalizer</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><span class="pre">bool</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span> <span class="sig-return"><span class="sig-return-icon">→</span> <span class="sig-return-typehint"><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Tuple" title="(in Python v3.12)"><span class="pre">Tuple</span></a><span class="p"><span class="pre">[</span></span><span class="pre">BaseFeatureExtractor</span><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a><span class="p"><span class="pre">,</span></span><span class="w"> </span><a class="reference internal" href="../norm/#slideflow.norm.StainNormalizer" title="slideflow.norm.StainNormalizer"><span class="pre">StainNormalizer</span></a><span class="w"> </span><span class="p"><span class="pre">|</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><span class="pre">None</span></a><span class="p"><span class="pre">]</span></span></span></span><a class="reference internal" href="../_modules/slideflow/model/extractors/_factory/#rebuild_extractor"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#slideflow.model.rebuild_extractor" title="Permalink to this definition">¶</a></dt>
<dd><p>Recreate the extractor used to generate features stored in bags.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>bags_or_model</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><em>str</em></a>) – Either a path to directory containing feature bags,
or a path to a trained MIL model. If a path to a trained MIL model,
the extractor used to generate features will be recreated.</p></li>
<li><p><strong>allow_errors</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a>) – If True, return None if the extractor
cannot be rebuilt. If False, raise an error. Defaults to False.</p></li>
<li><p><strong>native_normalizer</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><em>bool</em></a><em>, </em><em>optional</em>) – Whether to use PyTorch/Tensorflow-native
stain normalization, if applicable. If False, will use the OpenCV/Numpy
implementations. Defaults to True.</p></li>
</ul>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><p><dl class="simple">
<dt>Extractor function, or None if <code class="docutils literal notranslate"><span class="pre">allow_errors</span></code> is</dt><dd><p>True and the extractor cannot be rebuilt.</p>
</dd>
<dt>Optional[StainNormalizer]: Stain normalizer used when generating</dt><dd><p>feature bags, or None if no stain normalization was used.</p>
</dd>
</dl>
</p>
</dd>
<dt class="field-odd">Return type<span class="colon">:</span></dt>
<dd class="field-odd"><p>Optional[BaseFeatureExtractor]</p>
</dd>
</dl>
</dd></dl>
</section>
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<li><a class="reference internal" href="#trainer">Trainer</a><ul>
<li><a class="reference internal" href="#slideflow.model.Trainer"><code class="docutils literal notranslate"><span class="pre">Trainer</span></code></a></li>
<li><a class="reference internal" href="#slideflow.model.Trainer.load"><code class="docutils literal notranslate"><span class="pre">load()</span></code></a></li>
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<li><a class="reference internal" href="#other-functions">Other functions</a><ul>
<li><a class="reference internal" href="#slideflow.model.build_trainer"><code class="docutils literal notranslate"><span class="pre">build_trainer()</span></code></a></li>
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<li><a class="reference internal" href="#slideflow.model.is_tensorflow_tensor"><code class="docutils literal notranslate"><span class="pre">is_tensorflow_tensor()</span></code></a></li>
<li><a class="reference internal" href="#slideflow.model.is_torch_model"><code class="docutils literal notranslate"><span class="pre">is_torch_model()</span></code></a></li>
<li><a class="reference internal" href="#slideflow.model.is_torch_tensor"><code class="docutils literal notranslate"><span class="pre">is_torch_tensor()</span></code></a></li>
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<li><a class="reference internal" href="#slideflow.model.rebuild_extractor"><code class="docutils literal notranslate"><span class="pre">rebuild_extractor()</span></code></a></li>
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Datasets
Models
