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| <!DOCTYPE html> | ||
| <html class="writer-html5" lang="en" data-content_root="../../"> | ||
| <head> | ||
| <meta charset="utf-8" /> | ||
| <meta name="viewport" content="width=device-width, initial-scale=1.0" /> | ||
| <title>torchdr.base — TorchDR 0.0.0-alpha documentation</title> | ||
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| <li class="breadcrumb-item active">torchdr.base</li> | ||
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| <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article"> | ||
| <div itemprop="articleBody"> | ||
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| <h1>Source code for torchdr.base</h1><div class="highlight"><pre> | ||
| <span></span><span class="c1"># -*- coding: utf-8 -*-</span> | ||
| <span class="sd">"""</span> | ||
| <span class="sd">Base classes for DR methods</span> | ||
| <span class="sd">"""</span> | ||
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| <span class="c1"># Author: Hugues Van Assel <[email protected]></span> | ||
| <span class="c1">#</span> | ||
| <span class="c1"># License: BSD 3-Clause License</span> | ||
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| <span class="kn">from</span> <span class="nn">abc</span> <span class="kn">import</span> <span class="n">ABC</span><span class="p">,</span> <span class="n">abstractmethod</span> | ||
| <span class="kn">from</span> <span class="nn">sklearn.base</span> <span class="kn">import</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">TransformerMixin</span> | ||
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| <span class="kn">from</span> <span class="nn">torchdr.utils</span> <span class="kn">import</span> <span class="n">to_torch</span> | ||
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| <div class="viewcode-block" id="DRModule"> | ||
| <a class="viewcode-back" href="../../stubs/torchdr.base.DRModule.html#torchdr.base.DRModule">[docs]</a> | ||
| <span class="k">class</span> <span class="nc">DRModule</span><span class="p">(</span><span class="n">TransformerMixin</span><span class="p">,</span> <span class="n">BaseEstimator</span><span class="p">,</span> <span class="n">ABC</span><span class="p">):</span> | ||
| <span class="w"> </span><span class="sd">"""</span> | ||
| <span class="sd"> Base class for DR methods.</span> | ||
| <span class="sd"> Each children class should implement the fit method.</span> | ||
| <span class="sd"> """</span> | ||
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| <span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span> | ||
| <span class="bp">self</span><span class="p">,</span> | ||
| <span class="n">n_components</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span> | ||
| <span class="n">device</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> | ||
| <span class="n">keops</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> | ||
| <span class="n">verbose</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span> | ||
| <span class="p">):</span> | ||
| <span class="bp">self</span><span class="o">.</span><span class="n">n_components</span> <span class="o">=</span> <span class="n">n_components</span> | ||
| <span class="bp">self</span><span class="o">.</span><span class="n">device</span> <span class="o">=</span> <span class="n">device</span> | ||
| <span class="bp">self</span><span class="o">.</span><span class="n">keops</span> <span class="o">=</span> <span class="n">keops</span> | ||
| <span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span> | ||
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| <span class="k">def</span> <span class="nf">_process_input</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">):</span> | ||
| <span class="bp">self</span><span class="o">.</span><span class="n">data_</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">input_backend_</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">input_device_</span> <span class="o">=</span> <span class="n">to_torch</span><span class="p">(</span> | ||
| <span class="n">X</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">device</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">verbose</span><span class="p">,</span> <span class="n">return_backend_device</span><span class="o">=</span><span class="kc">True</span> | ||
| <span class="p">)</span> | ||
| <span class="bp">self</span><span class="o">.</span><span class="n">n_features_</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> | ||
| <span class="k">return</span> <span class="bp">self</span> | ||
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| <span class="nd">@abstractmethod</span> | ||
| <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span> | ||
| <span class="w"> </span><span class="sd">"""Projects input data X onto a low-dimensional space.</span> | ||
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| <span class="sd"> Parameters</span> | ||
| <span class="sd"> ----------</span> | ||
| <span class="sd"> X : array-like object of shape (n_samples, n_features)</span> | ||
| <span class="sd"> or (n_samples, n_samples) if precomputed is True</span> | ||
| <span class="sd"> Input data or input affinity matrix if it is precomputed.</span> | ||
| <span class="sd"> y : None</span> | ||
| <span class="sd"> Ignored.</span> | ||
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| <span class="sd"> Returns</span> | ||
| <span class="sd"> -------</span> | ||
| <span class="sd"> self : object</span> | ||
| <span class="sd"> Fitted Estimator.</span> | ||
| <span class="sd"> """</span> | ||
| <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">verbose</span><span class="p">:</span> | ||
| <span class="nb">print</span><span class="p">(</span><span class="s2">"[TorchDR] Fitting DR model ..."</span><span class="p">)</span> | ||
| <span class="k">return</span> <span class="bp">self</span></div> | ||
|
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| </pre></div> | ||
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| </div> | ||
| </div> | ||
| <footer> | ||
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| <hr/> | ||
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| <div role="contentinfo"> | ||
| <p>© Copyright 2024, TorchDR team.</p> | ||
| </div> | ||
|
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| Built with <a href="https://www.sphinx-doc.org/">Sphinx</a> using a | ||
| <a href="https://github.com/readthedocs/sphinx_rtd_theme">theme</a> | ||
| provided by <a href="https://readthedocs.org">Read the Docs</a>. | ||
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| jQuery(function () { | ||
| SphinxRtdTheme.Navigation.enable(true); | ||
| }); | ||
| </script> | ||
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| </body> | ||
| </html> |
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| .. raw:: html | ||
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| <div class="sphx-glr-thumbnails"> | ||
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| .. thumbnail-parent-div-open | ||
| .. thumbnail-parent-div-close | ||
| .. raw:: html | ||
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| </div> | ||
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| .. only:: html | ||
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| .. container:: sphx-glr-footer sphx-glr-footer-gallery | ||
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| .. container:: sphx-glr-download sphx-glr-download-python | ||
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| :download:`Download all examples in Python source code: auto_examples_python.zip </auto_examples/auto_examples_python.zip>` | ||
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| .. only:: html | ||
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| .. rst-class:: sphx-glr-signature | ||
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| `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_ |
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| .. _sphx_glr_auto_examples_sg_execution_times: | ||
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| Computation times | ||
| ================= | ||
| **00:00.000** total execution time for 0 files **from auto_examples**: | ||
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| .. container:: | ||
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| .. raw:: html | ||
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| <style scoped> | ||
| <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" /> | ||
| <link href="https://cdn.datatables.net/1.13.6/css/dataTables.bootstrap5.min.css" rel="stylesheet" /> | ||
| </style> | ||
| <script src="https://code.jquery.com/jquery-3.7.0.js"></script> | ||
| <script src="https://cdn.datatables.net/1.13.6/js/jquery.dataTables.min.js"></script> | ||
| <script src="https://cdn.datatables.net/1.13.6/js/dataTables.bootstrap5.min.js"></script> | ||
| <script type="text/javascript" class="init"> | ||
| $(document).ready( function () { | ||
| $('table.sg-datatable').DataTable({order: [[1, 'desc']]}); | ||
| } ); | ||
| </script> | ||
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| .. list-table:: | ||
| :header-rows: 1 | ||
| :class: table table-striped sg-datatable | ||
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| * - Example | ||
| - Time | ||
| - Mem (MB) | ||
| * - N/A | ||
| - N/A | ||
| - N/A |
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| TorchDR: a Pytorch library for dimensionality reduction | ||
| ================================================================== | ||
|
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| Github repository: `<https://github.com/torchdr/torchdr>`_. | ||
|
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| **TorchDR** provides a simple unified framework for :ref:`dimensionality reduction <overview>` methods. | ||
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| The library offers: | ||
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| * A large collection of :ref:`affinity matrices <affinities>`. | ||
| * A simple and unified interface for :ref:`neighbor embedding <neighbor-embedding>` methods. | ||
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| .. toctree:: | ||
| :maxdepth: 1 | ||
| :caption: Contents | ||
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| torchdr.overview | ||
| torchdr.affinities | ||
| torchdr.neighbor-embedding | ||
| torchdr.notation | ||
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| Finding Help | ||
| ================== | ||
| If you have any questions or suggestions, feel free to open an issue on the | ||
| `issue tracker <https://github.com/torchdr/torchdr/issues>`_ or contact `Hugues Van Assel <https://huguesva.github.io/>`_ directly. | ||
| .. include:: ../../README.rst |
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| .. _sphx_glr_sg_execution_times: | ||
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| Computation times | ||
| ================= | ||
| **00:00.000** total execution time for 0 files **from all galleries**: | ||
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| .. container:: | ||
|
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| .. raw:: html | ||
|
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| <style scoped> | ||
| <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" /> | ||
| <link href="https://cdn.datatables.net/1.13.6/css/dataTables.bootstrap5.min.css" rel="stylesheet" /> | ||
| </style> | ||
| <script src="https://code.jquery.com/jquery-3.7.0.js"></script> | ||
| <script src="https://cdn.datatables.net/1.13.6/js/jquery.dataTables.min.js"></script> | ||
| <script src="https://cdn.datatables.net/1.13.6/js/dataTables.bootstrap5.min.js"></script> | ||
| <script type="text/javascript" class="init"> | ||
| $(document).ready( function () { | ||
| $('table.sg-datatable').DataTable({order: [[1, 'desc']]}); | ||
| } ); | ||
| </script> | ||
|
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| .. list-table:: | ||
| :header-rows: 1 | ||
| :class: table table-striped sg-datatable | ||
|
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| * - Example | ||
| - Time | ||
| - Mem (MB) | ||
| * - N/A | ||
| - N/A | ||
| - N/A |
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