diff --git a/API_reference.html b/API_reference.html
index ea8b513..9ad15b3 100644
--- a/API_reference.html
+++ b/API_reference.html
@@ -18,7 +18,7 @@
     <script src="_static/js/theme.js"></script>
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
-    <link rel="next" title="besskge.dataset" href="generated/besskge.dataset.html" />
+    <link rel="next" title="besskge.pipeline" href="generated/besskge.pipeline.html" />
     <link rel="prev" title="BESS overview" href="bess.html" /> 
 </head>
 
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="user_guide.html">User guide</a></li>
 <li class="toctree-l1"><a class="reference internal" href="bess.html">BESS overview</a></li>
 <li class="toctree-l1 current"><a class="current reference internal" href="#">API reference</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="generated/besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="generated/besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="generated/besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="generated/besskge.batch_sampler.html">besskge.batch_sampler</a></li>
@@ -90,34 +91,37 @@
 <h1>BESS-KGE API Reference<a class="headerlink" href="#bess-kge-api-reference" title="Permalink to this heading"></a></h1>
 <table class="autosummary longtable docutils align-default">
 <tbody>
-<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.dataset.html#module-besskge.dataset" title="besskge.dataset"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.dataset</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.pipeline.html#module-besskge.pipeline" title="besskge.pipeline"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.pipeline</span></code></a></p></td>
+<td><p>High-level APIs for training/inference with BESS.</p></td>
+</tr>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.dataset.html#module-besskge.dataset" title="besskge.dataset"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.dataset</span></code></a></p></td>
 <td><p>Utilities for building and storing knowledge graph datasets as collections of (h,r,t) triples.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.sharding.html#module-besskge.sharding" title="besskge.sharding"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.sharding</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.sharding.html#module-besskge.sharding" title="besskge.sharding"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.sharding</span></code></a></p></td>
 <td><p>Sharding of embedding tables and triple sets for distributed execution.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.batch_sampler.html#module-besskge.batch_sampler" title="besskge.batch_sampler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.batch_sampler</span></code></a></p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.batch_sampler.html#module-besskge.batch_sampler" title="besskge.batch_sampler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.batch_sampler</span></code></a></p></td>
 <td><p>Classes for sampling batches of positive and negative triples for each processing device, according to the BESS distribution scheme.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.negative_sampler.html#module-besskge.negative_sampler" title="besskge.negative_sampler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.negative_sampler</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.negative_sampler.html#module-besskge.negative_sampler" title="besskge.negative_sampler"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.negative_sampler</span></code></a></p></td>
 <td><p>Classes for sampling entities to use as corrupted heads/tails when constructing negative samples.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.bess.html#module-besskge.bess" title="besskge.bess"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.bess</span></code></a></p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.bess.html#module-besskge.bess" title="besskge.bess"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.bess</span></code></a></p></td>
 <td><p>PyTorch modules implementing the BESS distribution scheme <span id="id1">[<a class="reference internal" href="bibliography.html#id11" title="Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jerome Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew Fitzgibbon, Blazej Banaszewski, and Carlo Luschi. BESS: balanced entity sampling and sharing for large-scale knowledge graph completion. arXiv preprint arXiv:2211.12281, 2022.">CJM+22</a>]</span> for KGE training and inference on multiple IPUs.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.scoring.html#module-besskge.scoring" title="besskge.scoring"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.scoring</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.scoring.html#module-besskge.scoring" title="besskge.scoring"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.scoring</span></code></a></p></td>
 <td><p>Functions for scoring positive and negative triples, specific to each KGE model.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.loss.html#module-besskge.loss" title="besskge.loss"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.loss</span></code></a></p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.loss.html#module-besskge.loss" title="besskge.loss"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.loss</span></code></a></p></td>
 <td><p>Functions for computing the batch loss based on the scores of positive and negative samples.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.metric.html#module-besskge.metric" title="besskge.metric"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.metric</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.metric.html#module-besskge.metric" title="besskge.metric"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.metric</span></code></a></p></td>
 <td><p>Utilities for computing metrics to evaluate the predictions of KGE models.</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.embedding.html#module-besskge.embedding" title="besskge.embedding"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.embedding</span></code></a></p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.embedding.html#module-besskge.embedding" title="besskge.embedding"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.embedding</span></code></a></p></td>
 <td><p>Utilities for initializing and managing entity/relation embedding tables.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="generated/besskge.utils.html#module-besskge.utils" title="besskge.utils"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.utils</span></code></a></p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="generated/besskge.utils.html#module-besskge.utils" title="besskge.utils"><code class="xref py py-obj docutils literal notranslate"><span class="pre">besskge.utils</span></code></a></p></td>
 <td><p>General purpose utilities.</p></td>
 </tr>
 </tbody>
@@ -129,7 +133,7 @@ <h1>BESS-KGE API Reference<a class="headerlink" href="#bess-kge-api-reference" t
           </div>
           <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
         <a href="bess.html" class="btn btn-neutral float-left" title="BESS overview" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
-        <a href="generated/besskge.dataset.html" class="btn btn-neutral float-right" title="besskge.dataset" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
+        <a href="generated/besskge.pipeline.html" class="btn btn-neutral float-right" title="besskge.pipeline" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
     </div>
 
   <hr/>
diff --git a/_modules/besskge/bess.html b/_modules/besskge/bess.html
index 32f0e60..37c0b17 100644
--- a/_modules/besskge/bess.html
+++ b/_modules/besskge/bess.html
@@ -781,22 +781,22 @@ <h1>Source code for besskge.bess</h1><div class="highlight"><pre>
 <span class="sd">        and respective scores are kept to be used in the next iteration, while</span>
 <span class="sd">        the rest are discarded.</span>
 
-<span class="sd">        :param relation: shape: (shard_bs,)</span>
+<span class="sd">        :param relation: shape: (1, shard_bs,)</span>
 <span class="sd">            Relation indices.</span>
-<span class="sd">        :param head: shape: (shard_bs,)</span>
+<span class="sd">        :param head: shape: (1, shard_bs,)</span>
 <span class="sd">            Head indices, if known. Default: None.</span>
-<span class="sd">        :param tail: shape: (shard_bs,)</span>
+<span class="sd">        :param tail: shape: (1, shard_bs,)</span>
 <span class="sd">            Tail indices, if known. Default: None.</span>
-<span class="sd">        :param negative: shape: (n_shard, B, padded_negative)</span>
+<span class="sd">        :param negative: shape: (1, n_shard, B, padded_negative)</span>
 <span class="sd">            Candidates to score against the queries.</span>
 <span class="sd">            It can be the same set for all queries (B=1),</span>
 <span class="sd">            or specific for each query in the batch (B=shard_bs).</span>
 <span class="sd">            If None, score each query against all entities in the knowledge</span>
 <span class="sd">            graph. Default: None.</span>
-<span class="sd">        :param triple_mask: shape: (shard_bs,)</span>
+<span class="sd">        :param triple_mask: shape: (1, shard_bs,)</span>
 <span class="sd">            Mask to filter the triples in the micro-batch</span>
 <span class="sd">            before computing metrics. Default: None.</span>
-<span class="sd">        :param negative_mask: shape: (n_shard, B, padded_negative)</span>
+<span class="sd">        :param negative_mask: shape: (1, n_shard, B, padded_negative)</span>
 <span class="sd">            If candidates are provided, mask to discard padding</span>
 <span class="sd">            negatives when computing best completions.</span>
 <span class="sd">            Requires the use of :code:`mask_on_gather=True` in the candidate</span>
@@ -993,6 +993,147 @@ <h1>Source code for besskge.bess</h1><div class="highlight"><pre>
                 <span class="p">)</span>
 
         <span class="k">return</span> <span class="n">out_dict</span></div></div>
+
+
+<div class="viewcode-block" id="AllScoresBESS"><a class="viewcode-back" href="../../generated/besskge.bess.AllScoresBESS.html#besskge.bess.AllScoresBESS">[docs]</a><span class="k">class</span> <span class="nc">AllScoresBESS</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Distributed scoring of (h, r, ?) or (?, r, t) queries against</span>
+<span class="sd">    the entities in the knowledge graph, returning all scores to</span>
+<span class="sd">    host in blocks, based on the BESS :cite:p:`BESS`</span>
+<span class="sd">    inference scheme.</span>
+<span class="sd">    To be used in combination with a batch sampler based on a</span>
+<span class="sd">    &quot;h_shard&quot;/&quot;t_shard&quot;-partitioned triple set.</span>
+<span class="sd">    Since each iteration on IPU computes only part of the scores</span>
+<span class="sd">    (based on the size of the sliding window), metrics should be</span>
+<span class="sd">    computed on host after aggregating data (see</span>
+<span class="sd">    :class:`besskge.pipeline.AllScoresPipeline`).</span>
+
+<span class="sd">    Only to be used for inference.</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+
+    <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">candidate_sampler</span><span class="p">:</span> <span class="n">PlaceholderNegativeSampler</span><span class="p">,</span>
+        <span class="n">score_fn</span><span class="p">:</span> <span class="n">BaseScoreFunction</span><span class="p">,</span>
+        <span class="n">window_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1000</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Initialize AllScores BESS-KGE module.</span>
+
+<span class="sd">        :param candidate_sampler:</span>
+<span class="sd">            :class:`besskge.negative_sampler.PlaceholderNegativeSampler` class,</span>
+<span class="sd">            specifying corruption scheme.</span>
+<span class="sd">        :param score_fn:</span>
+<span class="sd">            Scoring function.</span>
+<span class="sd">        :param window_size:</span>
+<span class="sd">            Size of the sliding window, namely the number of negative entities</span>
+<span class="sd">            scored against each query at each step on IPU and returned to host.</span>
+<span class="sd">            Should be decreased with large batch sizes, to avoid an OOM error.</span>
+<span class="sd">            Default: 1000.</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">sharding</span> <span class="o">=</span> <span class="n">score_fn</span><span class="o">.</span><span class="n">sharding</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">score_fn</span> <span class="o">=</span> <span class="n">score_fn</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">negative_sampler</span> <span class="o">=</span> <span class="n">candidate_sampler</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">window_size</span> <span class="o">=</span> <span class="n">window_size</span>
+
+        <span class="k">if</span> <span class="ow">not</span> <span class="n">score_fn</span><span class="o">.</span><span class="n">negative_sample_sharing</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;AllScoresBESS requires using negative sample sharing&quot;</span><span class="p">)</span>
+
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">negative_sampler</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;h&quot;</span><span class="p">,</span> <span class="s2">&quot;t&quot;</span><span class="p">]:</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;AllScoresBESS only support &#39;h&#39;, &#39;t&#39; corruption scheme&quot;</span><span class="p">)</span>
+
+        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">negative_sampler</span><span class="p">,</span> <span class="n">PlaceholderNegativeSampler</span><span class="p">):</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
+                <span class="s2">&quot;AllScoresBESS requires a `PlaceholderNegativeSampler`&quot;</span>
+                <span class="s2">&quot; candidate_sampler&quot;</span>
+            <span class="p">)</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">entity_embedding</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">score_fn</span><span class="o">.</span><span class="n">entity_embedding</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">entity_embedding_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">entity_embedding</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">candidate</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">window_size</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">n_step</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span>
+            <span class="n">np</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">max_entity_per_shard</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_size</span><span class="p">)</span>
+        <span class="p">)</span>
+
+<div class="viewcode-block" id="AllScoresBESS.forward"><a class="viewcode-back" href="../../generated/besskge.bess.AllScoresBESS.html#besskge.bess.AllScoresBESS.forward">[docs]</a>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span>
+        <span class="bp">self</span><span class="p">,</span>
+        <span class="n">step</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span>
+        <span class="n">relation</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span>
+        <span class="n">head</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">tail</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Forward step.</span>
+
+<span class="sd">        Similarly to :class:`ScoreMovingBessKGE`, candidates are scored on the</span>
+<span class="sd">        device where they are gathered, then scores for the same query against</span>
+<span class="sd">        candidates in different shards are collected together via an AllToAll.</span>
+
+<span class="sd">        :param step:</span>
+<span class="sd">            The index of the block (of size self.window_size) of entities</span>
+<span class="sd">            on each IPU to score against queries.</span>
+<span class="sd">        :param relation: shape: (1, shard_bs,)</span>
+<span class="sd">            Relation indices.</span>
+<span class="sd">        :param head: shape: (1, shard_bs,)</span>
+<span class="sd">            Head indices, if known. Default: None.</span>
+<span class="sd">        :param tail: shape: (1, shard_bs,)</span>
+<span class="sd">            Tail indices, if known. Default: None.</span>
+
+<span class="sd">        :return:</span>
+<span class="sd">            The scores for the completions.</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+
+        <span class="n">relation</span> <span class="o">=</span> <span class="n">relation</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">head</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">head</span> <span class="o">=</span> <span class="n">head</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">tail</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">tail</span> <span class="o">=</span> <span class="n">tail</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
+
+        <span class="n">n_shard</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">n_shard</span>
+        <span class="n">shard_bs</span> <span class="o">=</span> <span class="n">relation</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+
+        <span class="n">relation_all</span> <span class="o">=</span> <span class="n">all_gather</span><span class="p">(</span><span class="n">relation</span><span class="p">,</span> <span class="n">n_shard</span><span class="p">)</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">negative_sampler</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;h&quot;</span><span class="p">:</span>
+            <span class="n">tail_embedding</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">entity_embedding</span><span class="p">[</span><span class="n">tail</span><span class="p">]</span>
+            <span class="n">tail_embedding_all</span> <span class="o">=</span> <span class="n">all_gather</span><span class="p">(</span><span class="n">tail_embedding</span><span class="p">,</span> <span class="n">n_shard</span><span class="p">)</span>
+        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">negative_sampler</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;t&quot;</span><span class="p">:</span>
+            <span class="n">head_embedding</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">entity_embedding</span><span class="p">[</span><span class="n">head</span><span class="p">]</span>
+            <span class="n">head_embedding_all</span> <span class="o">=</span> <span class="n">all_gather</span><span class="p">(</span><span class="n">head_embedding</span><span class="p">,</span> <span class="n">n_shard</span><span class="p">)</span>
+
+        <span class="c1"># Local indices of the entities to score against queries</span>
+        <span class="n">ent_slice</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">minimum</span><span class="p">(</span>
+            <span class="n">step</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_size</span>
+            <span class="o">+</span> <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">window_size</span><span class="p">,</span> <span class="n">device</span><span class="o">=</span><span class="n">relation</span><span class="o">.</span><span class="n">device</span><span class="p">),</span>
+            <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">max_entity_per_shard</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
+        <span class="p">)</span>
+        <span class="n">negative_embedding</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">entity_embedding</span><span class="p">[</span><span class="n">ent_slice</span><span class="p">]</span>
+
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">negative_sampler</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;h&quot;</span><span class="p">:</span>
+            <span class="n">scores</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">score_fn</span><span class="o">.</span><span class="n">score_heads</span><span class="p">(</span>
+                <span class="n">negative_embedding</span><span class="p">,</span>
+                <span class="n">relation_all</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="n">end_dim</span><span class="o">=</span><span class="mi">1</span><span class="p">),</span>
+                <span class="n">tail_embedding_all</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="n">end_dim</span><span class="o">=</span><span class="mi">1</span><span class="p">),</span>
+            <span class="p">)</span>
+        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">negative_sampler</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;t&quot;</span><span class="p">:</span>
+            <span class="n">scores</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">score_fn</span><span class="o">.</span><span class="n">score_tails</span><span class="p">(</span>
+                <span class="n">head_embedding_all</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="n">end_dim</span><span class="o">=</span><span class="mi">1</span><span class="p">),</span>
+                <span class="n">relation_all</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="n">end_dim</span><span class="o">=</span><span class="mi">1</span><span class="p">),</span>
+                <span class="n">negative_embedding</span><span class="p">,</span>
+            <span class="p">)</span>
+
+        <span class="c1"># Send back queries to original shard</span>
+        <span class="n">scores</span> <span class="o">=</span> <span class="p">(</span>
+            <span class="n">all_to_all</span><span class="p">(</span>
+                <span class="n">scores</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="n">n_shard</span><span class="p">,</span> <span class="n">shard_bs</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_size</span><span class="p">),</span>
+                <span class="n">n_shard</span><span class="p">,</span>
+            <span class="p">)</span>
+            <span class="o">.</span><span class="n">transpose</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
+            <span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="n">start_dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+        <span class="p">)</span>  <span class="c1"># shape (bs, n_shard * ws)</span>
+
+        <span class="k">return</span> <span class="n">scores</span></div></div>
 </pre></div>
 
            </div>
diff --git a/_modules/besskge/pipeline.html b/_modules/besskge/pipeline.html
new file mode 100644
index 0000000..6314b2b
--- /dev/null
+++ b/_modules/besskge/pipeline.html
@@ -0,0 +1,402 @@
+<!DOCTYPE html>
+<html class="writer-html5" lang="en" >
+<head>
+  <meta charset="utf-8" />
+  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
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+        </div><div class="wy-menu wy-menu-vertical" data-spy="affix" role="navigation" aria-label="Navigation menu">
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+<li class="toctree-l1"><a class="reference internal" href="../../user_guide.html">User guide</a></li>
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+      <li><a href="../../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../index.html">Module code</a></li>
+      <li class="breadcrumb-item active">besskge.pipeline</li>
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+      </li>
+  </ul>
+  <hr/>
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+          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
+           <div itemprop="articleBody">
+             
+  <h1>Source code for besskge.pipeline</h1><div class="highlight"><pre>
+<span></span><span class="c1"># Copyright (c) 2023 Graphcore Ltd. All rights reserved.</span>
+
+<span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">High-level APIs for training/inference with BESS.</span>
+<span class="sd">&quot;&quot;&quot;</span>
+
+<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Any</span><span class="p">,</span> <span class="n">Dict</span><span class="p">,</span> <span class="n">List</span><span class="p">,</span> <span class="n">Optional</span><span class="p">,</span> <span class="n">Union</span>
+
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">poptorch</span>
+<span class="kn">import</span> <span class="nn">torch</span>
+<span class="kn">from</span> <span class="nn">numpy.typing</span> <span class="kn">import</span> <span class="n">NDArray</span>
+<span class="kn">from</span> <span class="nn">tqdm</span> <span class="kn">import</span> <span class="n">tqdm</span>
+
+<span class="kn">from</span> <span class="nn">besskge.batch_sampler</span> <span class="kn">import</span> <span class="n">ShardedBatchSampler</span>
+<span class="kn">from</span> <span class="nn">besskge.bess</span> <span class="kn">import</span> <span class="n">AllScoresBESS</span>
+<span class="kn">from</span> <span class="nn">besskge.metric</span> <span class="kn">import</span> <span class="n">Evaluation</span>
+<span class="kn">from</span> <span class="nn">besskge.negative_sampler</span> <span class="kn">import</span> <span class="n">PlaceholderNegativeSampler</span>
+<span class="kn">from</span> <span class="nn">besskge.scoring</span> <span class="kn">import</span> <span class="n">BaseScoreFunction</span>
+<span class="kn">from</span> <span class="nn">besskge.utils</span> <span class="kn">import</span> <span class="n">get_entity_filter</span>
+
+
+<div class="viewcode-block" id="AllScoresPipeline"><a class="viewcode-back" href="../../generated/besskge.pipeline.AllScoresPipeline.html#besskge.pipeline.AllScoresPipeline">[docs]</a><span class="k">class</span> <span class="nc">AllScoresPipeline</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">nn</span><span class="o">.</span><span class="n">Module</span><span class="p">):</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Pipeline to compute scores of (h, r, ?) / (?, r, t) queries against all entities</span>
+<span class="sd">    in the KG, and related prediction metrics.</span>
+<span class="sd">    It supports filtering out the scores of specific completions that appear in a given</span>
+<span class="sd">    set of triples.</span>
+
+<span class="sd">    To be used in combination with a batch sampler based on a</span>
+<span class="sd">    &quot;h_shard&quot;/&quot;t_shard&quot;-partitioned triple set.</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+
+    <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">batch_sampler</span><span class="p">:</span> <span class="n">ShardedBatchSampler</span><span class="p">,</span>
+        <span class="n">corruption_scheme</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
+        <span class="n">score_fn</span><span class="p">:</span> <span class="n">BaseScoreFunction</span><span class="p">,</span>
+        <span class="n">evaluation</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">Evaluation</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">filter_triples</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">List</span><span class="p">[</span><span class="n">Union</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">NDArray</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">]]]]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
+        <span class="n">return_scores</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+        <span class="n">return_topk</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+        <span class="n">k</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">10</span><span class="p">,</span>
+        <span class="n">window_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1000</span><span class="p">,</span>
+        <span class="n">use_ipu_model</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
+    <span class="p">)</span> <span class="o">-&gt;</span> <span class="kc">None</span><span class="p">:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Initialize pipeline.</span>
+
+<span class="sd">        :param batch_sampler:</span>
+<span class="sd">            Batch sampler, based on a</span>
+<span class="sd">            &quot;h_shard&quot;/&quot;t_shard&quot;-partitioned triple set.</span>
+<span class="sd">        :param corruption_scheme:</span>
+<span class="sd">            Set to &quot;t&quot; to score (h, r, ?) completions, or to</span>
+<span class="sd">            &quot;h&quot; to score (?, r, t) completions.</span>
+<span class="sd">        :param score_fn:</span>
+<span class="sd">            The trained scoring function.</span>
+<span class="sd">        :param evaluation:</span>
+<span class="sd">            Evaluation module, for computing metrics.</span>
+<span class="sd">            Default: None.</span>
+<span class="sd">        :param filter_triples:</span>
+<span class="sd">            The set of all triples whose scores need to be filtered.</span>
+<span class="sd">            The triples passed here must have GLOBAL IDs for head/tail</span>
+<span class="sd">            entities. Default: None.</span>
+<span class="sd">        :param return_scores:</span>
+<span class="sd">            If True, store and return scores of all queries&#39; completions</span>
+<span class="sd">            (with filters applied, if specified).</span>
+<span class="sd">            For large number of queries/entities, this can cause the host</span>
+<span class="sd">            to go OOM.</span>
+<span class="sd">            Default: False.</span>
+<span class="sd">        :param return_topk:</span>
+<span class="sd">            If True, return for each query the global IDs of the most likely</span>
+<span class="sd">            completions, after filtering out the scores of `filter_triples`.</span>
+<span class="sd">            Default: False.</span>
+<span class="sd">        :param k:</span>
+<span class="sd">            If `return_topk` is set to True, for each query return the</span>
+<span class="sd">            top-k most likely predictions (after filtering). Default: 10.</span>
+<span class="sd">        :param window_size:</span>
+<span class="sd">            Size of the sliding window, namely the number of negative entities</span>
+<span class="sd">            scored against each query at each step on IPU and returned to host.</span>
+<span class="sd">            Should be decreased with large batch sizes, to avoid an OOM error.</span>
+<span class="sd">            Default: 1000.</span>
+<span class="sd">        :param use_ipu_model:</span>
+<span class="sd">            Run pipeline on IPU Model instead of actual hardware. Default: False.</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="nb">super</span><span class="p">()</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span> <span class="o">=</span> <span class="n">batch_sampler</span>
+        <span class="k">if</span> <span class="ow">not</span> <span class="p">(</span><span class="n">evaluation</span> <span class="ow">or</span> <span class="n">return_scores</span><span class="p">):</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
+                <span class="s2">&quot;Nothing to return. Provide `evaluation` or set `return_scores=True`&quot;</span>
+            <span class="p">)</span>
+        <span class="k">if</span> <span class="n">corruption_scheme</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s2">&quot;h&quot;</span><span class="p">,</span> <span class="s2">&quot;t&quot;</span><span class="p">]:</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;corruption_scheme needs to be either &#39;h&#39; or &#39;t&#39;&quot;</span><span class="p">)</span>
+        <span class="k">if</span> <span class="p">(</span>
+            <span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;h&quot;</span>
+            <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">triple_partition_mode</span> <span class="o">!=</span> <span class="s2">&quot;t_shard&quot;</span>
+        <span class="p">):</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
+                <span class="s2">&quot;Corruption scheme &#39;h&#39; requires &#39;t-shard&#39;-partitioned triples&quot;</span>
+            <span class="p">)</span>
+        <span class="k">elif</span> <span class="p">(</span>
+            <span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;t&quot;</span>
+            <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">triple_partition_mode</span> <span class="o">!=</span> <span class="s2">&quot;h_shard&quot;</span>
+        <span class="p">):</span>
+            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span>
+                <span class="s2">&quot;Corruption scheme &#39;t&#39; requires &#39;h-shard&#39;-partitioned triples&quot;</span>
+            <span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">candidate_sampler</span> <span class="o">=</span> <span class="n">PlaceholderNegativeSampler</span><span class="p">(</span>
+            <span class="n">corruption_scheme</span><span class="o">=</span><span class="n">corruption_scheme</span>
+        <span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">score_fn</span> <span class="o">=</span> <span class="n">score_fn</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">evaluation</span> <span class="o">=</span> <span class="n">evaluation</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">return_scores</span> <span class="o">=</span> <span class="n">return_scores</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">return_topk</span> <span class="o">=</span> <span class="n">return_topk</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">k</span> <span class="o">=</span> <span class="n">k</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">window_size</span> <span class="o">=</span> <span class="n">window_size</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="o">=</span> <span class="n">corruption_scheme</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span> <span class="o">=</span> <span class="n">AllScoresBESS</span><span class="p">(</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">candidate_sampler</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">score_fn</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_size</span>
+        <span class="p">)</span>
+
+        <span class="n">inf_options</span> <span class="o">=</span> <span class="n">poptorch</span><span class="o">.</span><span class="n">Options</span><span class="p">()</span>
+        <span class="n">inf_options</span><span class="o">.</span><span class="n">replication_factor</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">n_shard</span>
+        <span class="n">inf_options</span><span class="o">.</span><span class="n">deviceIterations</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">batches_per_step</span><span class="p">)</span>
+        <span class="n">inf_options</span><span class="o">.</span><span class="n">outputMode</span><span class="p">(</span><span class="n">poptorch</span><span class="o">.</span><span class="n">OutputMode</span><span class="o">.</span><span class="n">All</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">use_ipu_model</span><span class="p">:</span>
+            <span class="n">inf_options</span><span class="o">.</span><span class="n">useIpuModel</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">dl</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">get_dataloader</span><span class="p">(</span><span class="n">options</span><span class="o">=</span><span class="n">inf_options</span><span class="p">,</span> <span class="n">shuffle</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">poptorch_module</span> <span class="o">=</span> <span class="n">poptorch</span><span class="o">.</span><span class="n">inferenceModel</span><span class="p">(</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="p">,</span> <span class="n">options</span><span class="o">=</span><span class="n">inf_options</span>
+        <span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">poptorch_module</span><span class="o">.</span><span class="n">entity_embedding</span><span class="o">.</span><span class="n">replicaGrouping</span><span class="p">(</span>
+            <span class="n">poptorch</span><span class="o">.</span><span class="n">CommGroupType</span><span class="o">.</span><span class="n">NoGrouping</span><span class="p">,</span>
+            <span class="mi">0</span><span class="p">,</span>
+            <span class="n">poptorch</span><span class="o">.</span><span class="n">VariableRetrievalMode</span><span class="o">.</span><span class="n">OnePerGroup</span><span class="p">,</span>
+        <span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">filter_triples</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="k">if</span> <span class="n">filter_triples</span><span class="p">:</span>
+            <span class="c1"># Reconstruct global IDs for all entities in triples</span>
+            <span class="n">local_id_col</span> <span class="o">=</span> <span class="p">(</span>
+                <span class="mi">0</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">triple_partition_mode</span> <span class="o">==</span> <span class="s2">&quot;h_shard&quot;</span> <span class="k">else</span> <span class="mi">2</span>
+            <span class="p">)</span>
+            <span class="n">triple_shard_offset</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span>
+                <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">0</span><span class="p">]),</span> <span class="n">np</span><span class="o">.</span><span class="n">cumsum</span><span class="p">(</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">triple_counts</span><span class="p">)]</span>
+            <span class="p">)</span>
+            <span class="n">global_id_triples</span> <span class="o">=</span> <span class="p">[]</span>
+            <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">triple_shard_offset</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span>
+                <span class="n">shard_triples</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span>
+                    <span class="n">batch_sampler</span><span class="o">.</span><span class="n">triples</span><span class="p">[</span>
+                        <span class="n">triple_shard_offset</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="p">:</span> <span class="n">triple_shard_offset</span><span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span>
+                    <span class="p">]</span>
+                <span class="p">)</span>
+                <span class="n">shard_triples</span><span class="p">[</span>
+                    <span class="p">:,</span> <span class="n">local_id_col</span>
+                <span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">shard_and_idx_to_entity</span><span class="p">[</span><span class="n">i</span><span class="p">][</span>
+                    <span class="n">shard_triples</span><span class="p">[:,</span> <span class="n">local_id_col</span><span class="p">]</span>
+                <span class="p">]</span>
+                <span class="n">global_id_triples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">shard_triples</span><span class="p">)</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">triples</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">global_id_triples</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">))</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">filter_triples</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span>
+                <span class="p">[</span>
+                    <span class="n">tr</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tr</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span> <span class="k">else</span> <span class="n">torch</span><span class="o">.</span><span class="n">from_numpy</span><span class="p">(</span><span class="n">tr</span><span class="p">)</span>
+                    <span class="k">for</span> <span class="n">tr</span> <span class="ow">in</span> <span class="n">filter_triples</span>
+                <span class="p">],</span>
+                <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
+            <span class="p">)</span>
+
+<div class="viewcode-block" id="AllScoresPipeline.forward"><a class="viewcode-back" href="../../generated/besskge.pipeline.AllScoresPipeline.html#besskge.pipeline.AllScoresPipeline.forward">[docs]</a>    <span class="k">def</span> <span class="nf">forward</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">Dict</span><span class="p">[</span><span class="nb">str</span><span class="p">,</span> <span class="n">Any</span><span class="p">]:</span>
+<span class="w">        </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Compute scores of all completions and (possibly) metrics.</span>
+
+<span class="sd">        :return:</span>
+<span class="sd">            Scores, metrics, and (if provided in batch sampler) IDs</span>
+<span class="sd">            of inference triples (wrt partitioned_triple_set.triples)</span>
+<span class="sd">            to order results.</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="n">scores</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="n">ids</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="n">metrics</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="n">ranks</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="n">topk_ids</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="n">n_triple</span> <span class="o">=</span> <span class="mi">0</span>
+        <span class="k">for</span> <span class="n">batch</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="nb">iter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">dl</span><span class="p">)):</span>
+            <span class="n">triple_mask</span> <span class="o">=</span> <span class="n">batch</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;triple_mask&quot;</span><span class="p">)</span>
+            <span class="k">if</span> <span class="p">(</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">candidate_sampler</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;h&quot;</span>
+                <span class="ow">and</span> <span class="s2">&quot;head&quot;</span> <span class="ow">in</span> <span class="n">batch</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span>
+            <span class="p">):</span>
+                <span class="n">ground_truth</span> <span class="o">=</span> <span class="n">batch</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;head&quot;</span><span class="p">)</span>
+            <span class="k">elif</span> <span class="p">(</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">candidate_sampler</span><span class="o">.</span><span class="n">corruption_scheme</span> <span class="o">==</span> <span class="s2">&quot;t&quot;</span>
+                <span class="ow">and</span> <span class="s2">&quot;tail&quot;</span> <span class="ow">in</span> <span class="n">batch</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span>
+            <span class="p">):</span>
+                <span class="n">ground_truth</span> <span class="o">=</span> <span class="n">batch</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;tail&quot;</span><span class="p">)</span>
+            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">return_triple_idx</span><span class="p">:</span>
+                <span class="n">triple_id</span> <span class="o">=</span> <span class="n">batch</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;triple_idx&quot;</span><span class="p">)</span>
+                <span class="n">ids</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">triple_id</span><span class="p">[</span><span class="n">triple_mask</span><span class="p">])</span>
+            <span class="n">n_triple</span> <span class="o">+=</span> <span class="n">triple_mask</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span>
+
+            <span class="n">batch_res</span> <span class="o">=</span> <span class="p">[]</span>
+            <span class="n">batch_idx</span> <span class="o">=</span> <span class="p">[]</span>
+            <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">n_step</span><span class="p">):</span>
+                <span class="n">step</span> <span class="o">=</span> <span class="p">(</span>
+                    <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">([</span><span class="n">i</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="n">torch</span><span class="o">.</span><span class="n">int32</span><span class="p">)</span>
+                    <span class="o">.</span><span class="n">broadcast_to</span><span class="p">(</span>
+                        <span class="p">(</span>
+                            <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">n_shard</span>
+                            <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_sampler</span><span class="o">.</span><span class="n">batches_per_step</span><span class="p">,</span>
+                            <span class="mi">1</span><span class="p">,</span>
+                        <span class="p">)</span>
+                    <span class="p">)</span>
+                    <span class="o">.</span><span class="n">contiguous</span><span class="p">()</span>
+                <span class="p">)</span>
+                <span class="n">ent_slice</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">minimum</span><span class="p">(</span>
+                    <span class="n">i</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">window_size</span>
+                    <span class="o">+</span> <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">window_size</span><span class="p">),</span>
+                    <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">max_entity_per_shard</span> <span class="o">-</span> <span class="mi">1</span><span class="p">),</span>
+                <span class="p">)</span>
+                <span class="c1"># Global indices of entities scored in the step</span>
+                <span class="n">batch_idx</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
+                    <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">shard_and_idx_to_entity</span><span class="p">[</span>
+                        <span class="p">:,</span> <span class="n">ent_slice</span>
+                    <span class="p">]</span><span class="o">.</span><span class="n">flatten</span><span class="p">()</span>
+                <span class="p">)</span>
+                <span class="n">inp</span> <span class="o">=</span> <span class="p">{</span><span class="n">k</span><span class="p">:</span> <span class="n">v</span><span class="o">.</span><span class="n">flatten</span><span class="p">(</span><span class="n">end_dim</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">batch</span><span class="o">.</span><span class="n">items</span><span class="p">()}</span>
+                <span class="n">inp</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="nb">dict</span><span class="p">(</span><span class="n">step</span><span class="o">=</span><span class="n">step</span><span class="p">))</span>
+                <span class="n">batch_res</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">poptorch_module</span><span class="p">(</span><span class="o">**</span><span class="n">inp</span><span class="p">))</span>
+            <span class="n">batch_scores</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">batch_res</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
+            <span class="c1"># Filter out padding scores</span>
+            <span class="n">batch_scores_filt</span> <span class="o">=</span> <span class="n">batch_scores</span><span class="p">[</span><span class="n">triple_mask</span><span class="o">.</span><span class="n">flatten</span><span class="p">()][</span>
+                <span class="p">:,</span> <span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">(</span><span class="n">batch_idx</span><span class="p">),</span> <span class="n">return_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)[</span><span class="mi">1</span><span class="p">]</span>
+            <span class="p">][:,</span> <span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">bess_module</span><span class="o">.</span><span class="n">sharding</span><span class="o">.</span><span class="n">n_entity</span><span class="p">]</span>
+            <span class="k">if</span> <span class="n">ground_truth</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+                <span class="c1"># Scores of positive triples</span>
+                <span class="n">true_scores</span> <span class="o">=</span> <span class="n">batch_scores_filt</span><span class="p">[</span>
+                    <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">batch_scores_filt</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span>
+                    <span class="n">ground_truth</span><span class="p">[</span><span class="n">triple_mask</span><span class="p">],</span>
+                <span class="p">]</span>
+            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">filter_triples</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+                <span class="c1"># Filter for triples in batch</span>
+                <span class="n">batch_filter</span> <span class="o">=</span> <span class="n">get_entity_filter</span><span class="p">(</span>
+                    <span class="bp">self</span><span class="o">.</span><span class="n">triples</span><span class="p">[</span><span class="n">triple_id</span><span class="p">[</span><span class="n">triple_mask</span><span class="p">]],</span>
+                    <span class="bp">self</span><span class="o">.</span><span class="n">filter_triples</span><span class="p">,</span>
+                    <span class="n">filter_mode</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">corruption_scheme</span><span class="p">,</span>
+                <span class="p">)</span>
+                <span class="n">batch_scores_filt</span><span class="p">[</span><span class="n">batch_filter</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">batch_filter</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]]</span> <span class="o">=</span> <span class="o">-</span><span class="n">torch</span><span class="o">.</span><span class="n">inf</span>
+
+            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">evaluation</span><span class="p">:</span>
+                <span class="k">assert</span> <span class="p">(</span>
+                    <span class="n">ground_truth</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span>
+                <span class="p">),</span> <span class="s2">&quot;Evaluation requires providing ground truth entities&quot;</span>
+                <span class="c1"># If not already masked, mask scores of true triples</span>
+                <span class="c1"># to compute metrics</span>
+                <span class="n">batch_scores_filt</span><span class="p">[</span>
+                    <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">batch_scores_filt</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span>
+                    <span class="n">ground_truth</span><span class="p">[</span><span class="n">triple_mask</span><span class="p">],</span>
+                <span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="n">torch</span><span class="o">.</span><span class="n">inf</span>
+                <span class="n">batch_ranks</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">evaluation</span><span class="o">.</span><span class="n">ranks_from_scores</span><span class="p">(</span>
+                    <span class="n">true_scores</span><span class="p">,</span> <span class="n">batch_scores_filt</span>
+                <span class="p">)</span>
+                <span class="n">metrics</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">evaluation</span><span class="o">.</span><span class="n">dict_metrics_from_ranks</span><span class="p">(</span><span class="n">batch_ranks</span><span class="p">))</span>
+                <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">evaluation</span><span class="o">.</span><span class="n">return_ranks</span><span class="p">:</span>
+                    <span class="n">ranks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">batch_ranks</span><span class="p">)</span>
+            <span class="k">if</span> <span class="n">ground_truth</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+                <span class="c1"># Restore positive scores in the returned scores</span>
+                <span class="n">batch_scores_filt</span><span class="p">[</span>
+                    <span class="n">torch</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">batch_scores_filt</span><span class="o">.</span><span class="n">shape</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span>
+                    <span class="n">ground_truth</span><span class="p">[</span><span class="n">triple_mask</span><span class="p">],</span>
+                <span class="p">]</span> <span class="o">=</span> <span class="n">true_scores</span>
+            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">return_scores</span><span class="p">:</span>
+                <span class="n">scores</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">batch_scores_filt</span><span class="p">)</span>
+            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">return_topk</span><span class="p">:</span>
+                <span class="n">topk_ids</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">topk</span><span class="p">(</span><span class="n">batch_scores_filt</span><span class="p">,</span> <span class="n">k</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">k</span><span class="p">,</span> <span class="n">dim</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">indices</span><span class="p">)</span>
+
+        <span class="n">out</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">()</span>
+        <span class="k">if</span> <span class="n">scores</span><span class="p">:</span>
+            <span class="n">out</span><span class="p">[</span><span class="s2">&quot;scores&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">scores</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">topk_ids</span><span class="p">:</span>
+            <span class="n">out</span><span class="p">[</span><span class="s2">&quot;topk_global_id&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">topk_ids</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">ids</span><span class="p">:</span>
+            <span class="n">out</span><span class="p">[</span><span class="s2">&quot;triple_idx&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">ids</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">evaluation</span><span class="p">:</span>
+            <span class="n">final_metrics</span> <span class="o">=</span> <span class="nb">dict</span><span class="p">()</span>
+            <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">metrics</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
+                <span class="c1"># Reduce metrics over all batches</span>
+                <span class="n">final_metrics</span><span class="p">[</span><span class="n">m</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">evaluation</span><span class="o">.</span><span class="n">reduction</span><span class="p">(</span>
+                    <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">([</span><span class="n">met</span><span class="p">[</span><span class="n">m</span><span class="p">]</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="k">for</span> <span class="n">met</span> <span class="ow">in</span> <span class="n">metrics</span><span class="p">])</span>
+                <span class="p">)</span>
+            <span class="n">out</span><span class="p">[</span><span class="s2">&quot;metrics&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">final_metrics</span>  <span class="c1"># type: ignore</span>
+            <span class="c1"># Average metrics over all triples</span>
+            <span class="n">out</span><span class="p">[</span><span class="s2">&quot;metrics_avg&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span>
+                <span class="n">m</span><span class="p">:</span> <span class="n">v</span><span class="o">.</span><span class="n">sum</span><span class="p">()</span> <span class="o">/</span> <span class="n">n_triple</span> <span class="k">for</span> <span class="n">m</span><span class="p">,</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">final_metrics</span><span class="o">.</span><span class="n">items</span><span class="p">()</span>
+            <span class="p">}</span>  <span class="c1"># type: ignore</span>
+            <span class="k">if</span> <span class="n">ranks</span><span class="p">:</span>
+                <span class="n">out</span><span class="p">[</span><span class="s2">&quot;ranks&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">concat</span><span class="p">(</span><span class="n">ranks</span><span class="p">,</span> <span class="n">dim</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
+
+        <span class="k">return</span> <span class="n">out</span></div></div>
+</pre></div>
+
+           </div>
+          </div>
+          <footer>
+
+  <hr/>
+
+  <div role="contentinfo">
+    <p>&#169; Copyright (c) 2023 Graphcore Ltd. All rights reserved.</p>
+  </div>
+
+  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>.
+   
+
+</footer>
+        </div>
+      </div>
+    </section>
+  </div>
+  <script>
+      jQuery(function () {
+          SphinxRtdTheme.Navigation.enable(true);
+      });
+  </script> 
+
+</body>
+</html>
\ No newline at end of file
diff --git a/_modules/besskge/utils.html b/_modules/besskge/utils.html
index 28b723d..1253d23 100644
--- a/_modules/besskge/utils.html
+++ b/_modules/besskge/utils.html
@@ -107,6 +107,42 @@ <h1>Source code for besskge.utils</h1><div class="highlight"><pre>
     <span class="k">return</span> <span class="n">x</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">mask_size</span><span class="p">)</span></div>
 
 
+<div class="viewcode-block" id="get_entity_filter"><a class="viewcode-back" href="../../generated/besskge.utils.get_entity_filter.html#besskge.utils.get_entity_filter">[docs]</a><span class="k">def</span> <span class="nf">get_entity_filter</span><span class="p">(</span>
+    <span class="n">triples</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">filter_triples</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">filter_mode</span><span class="p">:</span> <span class="nb">str</span>
+<span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
+<span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Compare two sets of triples: for each triple (h,r,t) in the first set, find</span>
+<span class="sd">    the entities `e` such that (e,r,t) (or (h,r,e), depending on `filter_mode`)</span>
+<span class="sd">    appears in the second set of triples.</span>
+
+<span class="sd">    :param triples: shape (x, 3)</span>
+<span class="sd">        The set of triples to construct filters for.</span>
+<span class="sd">    :param filter_triples: shape (y, 3)</span>
+<span class="sd">        The set of triples determining the head/tail entities to filter.</span>
+<span class="sd">    :param filter_mode:</span>
+<span class="sd">        Set to &quot;h&quot; to look for entities appearing as heads of the same (r,t) pair,</span>
+<span class="sd">        or to &quot;t&quot; to look for entities appearing as tails of the same (h,r) pair.</span>
+
+<span class="sd">    :return: shape (z, 2)</span>
+<span class="sd">        The sparse filters. Each row is given by a tuple (i, j), with i the index</span>
+<span class="sd">        of the triple in `triples` to which the filter applies to and j the global</span>
+<span class="sd">        ID of the entity to filter.</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="k">if</span> <span class="n">filter_mode</span> <span class="o">==</span> <span class="s2">&quot;t&quot;</span><span class="p">:</span>
+        <span class="n">ent_col</span> <span class="o">=</span> <span class="mi">0</span>
+    <span class="k">elif</span> <span class="n">filter_mode</span> <span class="o">==</span> <span class="s2">&quot;h&quot;</span><span class="p">:</span>
+        <span class="n">ent_col</span> <span class="o">=</span> <span class="mi">2</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;`filter_mode` needs to be either &#39;h&#39; or &#39;t&#39;&quot;</span><span class="p">)</span>
+    <span class="n">relation_filter</span> <span class="o">=</span> <span class="p">(</span><span class="n">filter_triples</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">])</span> <span class="o">==</span> <span class="n">triples</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
+    <span class="n">entity_filter</span> <span class="o">=</span> <span class="p">(</span><span class="n">filter_triples</span><span class="p">[:,</span> <span class="n">ent_col</span><span class="p">])</span> <span class="o">==</span> <span class="n">triples</span><span class="p">[:,</span> <span class="n">ent_col</span><span class="p">]</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
+
+    <span class="nb">filter</span> <span class="o">=</span> <span class="p">(</span><span class="n">entity_filter</span> <span class="o">&amp;</span> <span class="n">relation_filter</span><span class="p">)</span><span class="o">.</span><span class="n">nonzero</span><span class="p">(</span><span class="n">as_tuple</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
+    <span class="nb">filter</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">filter_triples</span><span class="p">[:,</span> <span class="mi">2</span> <span class="o">-</span> <span class="n">ent_col</span><span class="p">]</span><span class="o">.</span><span class="n">view</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">)[:,</span> <span class="nb">filter</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]]</span>
+
+    <span class="k">return</span> <span class="nb">filter</span></div>
+
+
 <div class="viewcode-block" id="complex_multiplication"><a class="viewcode-back" href="../../generated/besskge.utils.complex_multiplication.html#besskge.utils.complex_multiplication">[docs]</a><span class="k">def</span> <span class="nf">complex_multiplication</span><span class="p">(</span><span class="n">v1</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">,</span> <span class="n">v2</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">torch</span><span class="o">.</span><span class="n">Tensor</span><span class="p">:</span>
 <span class="w">    </span><span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Batched complex multiplication.</span>
diff --git a/_modules/index.html b/_modules/index.html
index 91c44c7..b782b5d 100644
--- a/_modules/index.html
+++ b/_modules/index.html
@@ -78,6 +78,7 @@ <h1>All modules for which code is available</h1>
 <li><a href="besskge/loss.html">besskge.loss</a></li>
 <li><a href="besskge/metric.html">besskge.metric</a></li>
 <li><a href="besskge/negative_sampler.html">besskge.negative_sampler</a></li>
+<li><a href="besskge/pipeline.html">besskge.pipeline</a></li>
 <li><a href="besskge/scoring.html">besskge.scoring</a></li>
 <li><a href="besskge/sharding.html">besskge.sharding</a></li>
 <li><a href="besskge/utils.html">besskge.utils</a></li>
diff --git a/_sources/API_reference.rst.txt b/_sources/API_reference.rst.txt
index 563839f..5179b0a 100644
--- a/_sources/API_reference.rst.txt
+++ b/_sources/API_reference.rst.txt
@@ -6,6 +6,7 @@ BESS-KGE API Reference
    :template: module.rst
    :recursive:
 
+   besskge.pipeline
    besskge.dataset
    besskge.sharding
    besskge.batch_sampler
diff --git a/_sources/generated/besskge.bess.AllScoresBESS.rst.txt b/_sources/generated/besskge.bess.AllScoresBESS.rst.txt
new file mode 100644
index 0000000..952f713
--- /dev/null
+++ b/_sources/generated/besskge.bess.AllScoresBESS.rst.txt
@@ -0,0 +1,12 @@
+..
+   # Copyright (c) 2023 Graphcore Ltd. All rights reserved.
+   # Copyright (c) 2007-2023 by the Sphinx team. All rights reserved.
+
+besskge.bess.AllScoresBESS
+==========================
+
+.. currentmodule:: besskge.bess
+
+.. autoclass:: AllScoresBESS
+   :members:
+   :inherited-members: Module
\ No newline at end of file
diff --git a/_sources/generated/besskge.bess.rst.txt b/_sources/generated/besskge.bess.rst.txt
index b7a5ff6..c50ca92 100644
--- a/_sources/generated/besskge.bess.rst.txt
+++ b/_sources/generated/besskge.bess.rst.txt
@@ -23,6 +23,7 @@ besskge.bess
       :toctree:
       :template: class.rst
    
+      AllScoresBESS
       BessKGE
       EmbeddingMovingBessKGE
       ScoreMovingBessKGE
diff --git a/_sources/generated/besskge.pipeline.AllScoresPipeline.rst.txt b/_sources/generated/besskge.pipeline.AllScoresPipeline.rst.txt
new file mode 100644
index 0000000..685562e
--- /dev/null
+++ b/_sources/generated/besskge.pipeline.AllScoresPipeline.rst.txt
@@ -0,0 +1,12 @@
+..
+   # Copyright (c) 2023 Graphcore Ltd. All rights reserved.
+   # Copyright (c) 2007-2023 by the Sphinx team. All rights reserved.
+
+besskge.pipeline.AllScoresPipeline
+==================================
+
+.. currentmodule:: besskge.pipeline
+
+.. autoclass:: AllScoresPipeline
+   :members:
+   :inherited-members: Module
\ No newline at end of file
diff --git a/_sources/generated/besskge.pipeline.rst.txt b/_sources/generated/besskge.pipeline.rst.txt
new file mode 100644
index 0000000..fa3fa87
--- /dev/null
+++ b/_sources/generated/besskge.pipeline.rst.txt
@@ -0,0 +1,31 @@
+..
+   # Copyright (c) 2023 Graphcore Ltd. All rights reserved.
+   # Copyright (c) 2007-2023 by the Sphinx team. All rights reserved.
+
+besskge.pipeline
+================
+
+.. automodule:: besskge.pipeline
+
+   
+   
+   
+
+   
+   
+   
+
+   
+   
+   .. rubric:: Classes
+
+   .. autosummary::
+      :toctree:
+      :template: class.rst
+   
+      AllScoresPipeline
+   
+   
+
+
+
diff --git a/_sources/generated/besskge.utils.get_entity_filter.rst.txt b/_sources/generated/besskge.utils.get_entity_filter.rst.txt
new file mode 100644
index 0000000..731a2c2
--- /dev/null
+++ b/_sources/generated/besskge.utils.get_entity_filter.rst.txt
@@ -0,0 +1,6 @@
+besskge.utils.get\_entity\_filter
+=================================
+
+.. currentmodule:: besskge.utils
+
+.. autofunction:: get_entity_filter
\ No newline at end of file
diff --git a/_sources/generated/besskge.utils.rst.txt b/_sources/generated/besskge.utils.rst.txt
index 1398d0e..79964cb 100644
--- a/_sources/generated/besskge.utils.rst.txt
+++ b/_sources/generated/besskge.utils.rst.txt
@@ -21,6 +21,7 @@ besskge.utils
       complex_multiplication
       complex_rotation
       gather_indices
+      get_entity_filter
    
    
 
diff --git a/dev_guide.html b/dev_guide.html
index cec9e82..9ac2b6b 100644
--- a/dev_guide.html
+++ b/dev_guide.html
@@ -19,7 +19,7 @@
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
     <link rel="next" title="Bibliography" href="bibliography.html" />
-    <link rel="prev" title="besskge.utils.gather_indices" href="generated/besskge.utils.gather_indices.html" /> 
+    <link rel="prev" title="besskge.utils.get_entity_filter" href="generated/besskge.utils.get_entity_filter.html" /> 
 </head>
 
 <body class="wy-body-for-nav"> 
@@ -138,7 +138,7 @@ <h2>Development tips<a class="headerlink" href="#development-tips" title="Permal
            </div>
           </div>
           <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
-        <a href="generated/besskge.utils.gather_indices.html" class="btn btn-neutral float-left" title="besskge.utils.gather_indices" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
+        <a href="generated/besskge.utils.get_entity_filter.html" class="btn btn-neutral float-left" title="besskge.utils.get_entity_filter" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
         <a href="bibliography.html" class="btn btn-neutral float-right" title="Bibliography" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
     </div>
 
diff --git a/generated/besskge.batch_sampler.RandomShardedBatchSampler.html b/generated/besskge.batch_sampler.RandomShardedBatchSampler.html
index fd4c3c3..6833065 100644
--- a/generated/besskge.batch_sampler.RandomShardedBatchSampler.html
+++ b/generated/besskge.batch_sampler.RandomShardedBatchSampler.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../bess.html">BESS overview</a></li>
 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.batch_sampler.RigidShardedBatchSampler.html b/generated/besskge.batch_sampler.RigidShardedBatchSampler.html
index bb04c28..58bfedf 100644
--- a/generated/besskge.batch_sampler.RigidShardedBatchSampler.html
+++ b/generated/besskge.batch_sampler.RigidShardedBatchSampler.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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 <li class="toctree-l2 current"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a><ul class="current">
diff --git a/generated/besskge.batch_sampler.ShardedBatchSampler.html b/generated/besskge.batch_sampler.ShardedBatchSampler.html
index 130c293..552315e 100644
--- a/generated/besskge.batch_sampler.ShardedBatchSampler.html
+++ b/generated/besskge.batch_sampler.ShardedBatchSampler.html
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diff --git a/generated/besskge.batch_sampler.html b/generated/besskge.batch_sampler.html
index 9596bdb..c78431d 100644
--- a/generated/besskge.batch_sampler.html
+++ b/generated/besskge.batch_sampler.html
@@ -46,6 +46,7 @@
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new file mode 100644
index 0000000..80e6a33
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+  <section id="besskge-bess-allscoresbess">
+<h1>besskge.bess.AllScoresBESS<a class="headerlink" href="#besskge-bess-allscoresbess" title="Permalink to this heading"></a></h1>
+<dl class="py class">
+<dt class="sig sig-object py" id="besskge.bess.AllScoresBESS">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">besskge.bess.</span></span><span class="sig-name descname"><span class="pre">AllScoresBESS</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">candidate_sampler</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">score_fn</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/besskge/bess.html#AllScoresBESS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#besskge.bess.AllScoresBESS" title="Permalink to this definition"></a></dt>
+<dd><p>Distributed scoring of (h, r, ?) or (?, r, t) queries against
+the entities in the knowledge graph, returning all scores to
+host in blocks, based on the BESS <span id="id1">[<a class="reference internal" href="../bibliography.html#id11" title="Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jerome Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew Fitzgibbon, Blazej Banaszewski, and Carlo Luschi. BESS: balanced entity sampling and sharing for large-scale knowledge graph completion. arXiv preprint arXiv:2211.12281, 2022.">CJM+22</a>]</span>
+inference scheme.
+To be used in combination with a batch sampler based on a
+“h_shard”/”t_shard”-partitioned triple set.
+Since each iteration on IPU computes only part of the scores
+(based on the size of the sliding window), metrics should be
+computed on host after aggregating data (see
+<a class="reference internal" href="besskge.pipeline.AllScoresPipeline.html#besskge.pipeline.AllScoresPipeline" title="besskge.pipeline.AllScoresPipeline"><code class="xref py py-class docutils literal notranslate"><span class="pre">besskge.pipeline.AllScoresPipeline</span></code></a>).</p>
+<p>Only to be used for inference.</p>
+<p>Initialize AllScores BESS-KGE module.</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>candidate_sampler</strong> (<a class="reference internal" href="besskge.negative_sampler.PlaceholderNegativeSampler.html#besskge.negative_sampler.PlaceholderNegativeSampler" title="besskge.negative_sampler.PlaceholderNegativeSampler"><code class="xref py py-class docutils literal notranslate"><span class="pre">PlaceholderNegativeSampler</span></code></a>) – <a class="reference internal" href="besskge.negative_sampler.PlaceholderNegativeSampler.html#besskge.negative_sampler.PlaceholderNegativeSampler" title="besskge.negative_sampler.PlaceholderNegativeSampler"><code class="xref py py-class docutils literal notranslate"><span class="pre">besskge.negative_sampler.PlaceholderNegativeSampler</span></code></a> class,
+specifying corruption scheme.</p></li>
+<li><p><strong>score_fn</strong> (<a class="reference internal" href="besskge.scoring.BaseScoreFunction.html#besskge.scoring.BaseScoreFunction" title="besskge.scoring.BaseScoreFunction"><code class="xref py py-class docutils literal notranslate"><span class="pre">BaseScoreFunction</span></code></a>) – Scoring function.</p></li>
+<li><p><strong>window_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a>) – Size of the sliding window, namely the number of negative entities
+scored against each query at each step on IPU and returned to host.
+Should be decreased with large batch sizes, to avoid an OOM error.
+Default: 1000.</p></li>
+</ul>
+</dd>
+</dl>
+<dl class="py method">
+<dt class="sig sig-object py" id="besskge.bess.AllScoresBESS.forward">
+<span class="sig-name descname"><span class="pre">forward</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">step</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">relation</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">head</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tail</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/besskge/bess.html#AllScoresBESS.forward"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#besskge.bess.AllScoresBESS.forward" title="Permalink to this definition"></a></dt>
+<dd><p>Forward step.</p>
+<p>Similarly to <a class="reference internal" href="besskge.bess.ScoreMovingBessKGE.html#besskge.bess.ScoreMovingBessKGE" title="besskge.bess.ScoreMovingBessKGE"><code class="xref py py-class docutils literal notranslate"><span class="pre">ScoreMovingBessKGE</span></code></a>, candidates are scored on the
+device where they are gathered, then scores for the same query against
+candidates in different shards are collected together via an AllToAll.</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>step</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>) – The index of the block (of size self.window_size) of entities
+on each IPU to score against queries.</p></li>
+<li><p><strong>relation</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>) – shape: (1, shard_bs,)
+Relation indices.</p></li>
+<li><p><strong>head</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (1, shard_bs,)
+Head indices, if known. Default: None.</p></li>
+<li><p><strong>tail</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (1, shard_bs,)
+Tail indices, if known. Default: None.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></p>
+</dd>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
+<dd class="field-odd"><p>The scores for the completions.</p>
+</dd>
+</dl>
+</dd></dl>
+
+</dd></dl>
+
+</section>
+
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diff --git a/generated/besskge.bess.ScoreMovingBessKGE.html b/generated/besskge.bess.ScoreMovingBessKGE.html
index 00cc533..169260b 100644
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diff --git a/generated/besskge.bess.TopKQueryBessKGE.html b/generated/besskge.bess.TopKQueryBessKGE.html
index 9e78de2..061aaca 100644
--- a/generated/besskge.bess.TopKQueryBessKGE.html
+++ b/generated/besskge.bess.TopKQueryBessKGE.html
@@ -46,11 +46,13 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
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 <li class="toctree-l2 current"><a class="reference internal" href="besskge.bess.html">besskge.bess</a><ul class="current">
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 <li class="toctree-l3"><a class="reference internal" href="besskge.bess.ScoreMovingBessKGE.html">besskge.bess.ScoreMovingBessKGE</a></li>
@@ -149,22 +151,22 @@ <h1>besskge.bess.TopKQueryBessKGE<a class="headerlink" href="#besskge-bess-topkq
 <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>relation</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>) – shape: (shard_bs,)
+<li><p><strong>relation</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>) – shape: (1, shard_bs,)
 Relation indices.</p></li>
-<li><p><strong>head</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (shard_bs,)
+<li><p><strong>head</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (1, shard_bs,)
 Head indices, if known. Default: None.</p></li>
-<li><p><strong>tail</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (shard_bs,)
+<li><p><strong>tail</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (1, shard_bs,)
 Tail indices, if known. Default: None.</p></li>
-<li><p><strong>negative</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (n_shard, B, padded_negative)
+<li><p><strong>negative</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (1, n_shard, B, padded_negative)
 Candidates to score against the queries.
 It can be the same set for all queries (B=1),
 or specific for each query in the batch (B=shard_bs).
 If None, score each query against all entities in the knowledge
 graph. Default: None.</p></li>
-<li><p><strong>triple_mask</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (shard_bs,)
+<li><p><strong>triple_mask</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (1, shard_bs,)
 Mask to filter the triples in the micro-batch
 before computing metrics. Default: None.</p></li>
-<li><p><strong>negative_mask</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (n_shard, B, padded_negative)
+<li><p><strong>negative_mask</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>]) – shape: (1, n_shard, B, padded_negative)
 If candidates are provided, mask to discard padding
 negatives when computing best completions.
 Requires the use of <code class="code docutils literal notranslate"><span class="pre">mask_on_gather=True</span></code> in the candidate
diff --git a/generated/besskge.bess.html b/generated/besskge.bess.html
index cc3d5a8..68a0e67 100644
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@@ -46,11 +46,13 @@
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 <li class="toctree-l2 current"><a class="current reference internal" href="#">besskge.bess</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="besskge.bess.AllScoresBESS.html">besskge.bess.AllScoresBESS</a></li>
 <li class="toctree-l3"><a class="reference internal" href="besskge.bess.BessKGE.html">besskge.bess.BessKGE</a></li>
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 <li class="toctree-l3"><a class="reference internal" href="besskge.bess.ScoreMovingBessKGE.html">besskge.bess.ScoreMovingBessKGE</a></li>
@@ -100,17 +102,20 @@
 <p class="rubric">Classes</p>
 <table class="autosummary longtable docutils align-default">
 <tbody>
-<tr class="row-odd"><td><p><a class="reference internal" href="besskge.bess.BessKGE.html#besskge.bess.BessKGE" title="besskge.bess.BessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">BessKGE</span></code></a>(negative_sampler, score_fn[, ...])</p></td>
-<td><p>Base class for distributed training and inference of KGE models, using the distribution framework BESS <span id="id2">[<a class="reference internal" href="../bibliography.html#id11" title="Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jerome Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew Fitzgibbon, Blazej Banaszewski, and Carlo Luschi. BESS: balanced entity sampling and sharing for large-scale knowledge graph completion. arXiv preprint arXiv:2211.12281, 2022.">CJM+22</a>]</span>.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="besskge.bess.AllScoresBESS.html#besskge.bess.AllScoresBESS" title="besskge.bess.AllScoresBESS"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AllScoresBESS</span></code></a>(candidate_sampler, score_fn[, ...])</p></td>
+<td><p>Distributed scoring of (h, r, ?) or (?, r, t) queries against the entities in the knowledge graph, returning all scores to host in blocks, based on the BESS <span id="id2">[<a class="reference internal" href="../bibliography.html#id11" title="Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jerome Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew Fitzgibbon, Blazej Banaszewski, and Carlo Luschi. BESS: balanced entity sampling and sharing for large-scale knowledge graph completion. arXiv preprint arXiv:2211.12281, 2022.">CJM+22</a>]</span> inference scheme.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="besskge.bess.EmbeddingMovingBessKGE.html#besskge.bess.EmbeddingMovingBessKGE" title="besskge.bess.EmbeddingMovingBessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">EmbeddingMovingBessKGE</span></code></a>(negative_sampler, ...)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="besskge.bess.BessKGE.html#besskge.bess.BessKGE" title="besskge.bess.BessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">BessKGE</span></code></a>(negative_sampler, score_fn[, ...])</p></td>
+<td><p>Base class for distributed training and inference of KGE models, using the distribution framework BESS <span id="id3">[<a class="reference internal" href="../bibliography.html#id11" title="Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jerome Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew Fitzgibbon, Blazej Banaszewski, and Carlo Luschi. BESS: balanced entity sampling and sharing for large-scale knowledge graph completion. arXiv preprint arXiv:2211.12281, 2022.">CJM+22</a>]</span>.</p></td>
+</tr>
+<tr class="row-odd"><td><p><a class="reference internal" href="besskge.bess.EmbeddingMovingBessKGE.html#besskge.bess.EmbeddingMovingBessKGE" title="besskge.bess.EmbeddingMovingBessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">EmbeddingMovingBessKGE</span></code></a>(negative_sampler, ...)</p></td>
 <td><p>Compute negative scores on the shard where the positive triples are scored (namely the head shard).</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="besskge.bess.ScoreMovingBessKGE.html#besskge.bess.ScoreMovingBessKGE" title="besskge.bess.ScoreMovingBessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ScoreMovingBessKGE</span></code></a>(negative_sampler, score_fn)</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="besskge.bess.ScoreMovingBessKGE.html#besskge.bess.ScoreMovingBessKGE" title="besskge.bess.ScoreMovingBessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ScoreMovingBessKGE</span></code></a>(negative_sampler, score_fn)</p></td>
 <td><p>Compute negative scores on the shard where the negative entities are stored.</p></td>
 </tr>
-<tr class="row-even"><td><p><a class="reference internal" href="besskge.bess.TopKQueryBessKGE.html#besskge.bess.TopKQueryBessKGE" title="besskge.bess.TopKQueryBessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">TopKQueryBessKGE</span></code></a>(k, candidate_sampler, score_fn)</p></td>
-<td><p>Distributed scoring of (h, r, ?) or (?, r, t) queries (against all entities in the knowledge graph, or a query-specific set) returning the top-k most likely completions, based on the BESS <span id="id3">[<a class="reference internal" href="../bibliography.html#id11" title="Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jerome Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew Fitzgibbon, Blazej Banaszewski, and Carlo Luschi. BESS: balanced entity sampling and sharing for large-scale knowledge graph completion. arXiv preprint arXiv:2211.12281, 2022.">CJM+22</a>]</span> inference scheme.</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="besskge.bess.TopKQueryBessKGE.html#besskge.bess.TopKQueryBessKGE" title="besskge.bess.TopKQueryBessKGE"><code class="xref py py-obj docutils literal notranslate"><span class="pre">TopKQueryBessKGE</span></code></a>(k, candidate_sampler, score_fn)</p></td>
+<td><p>Distributed scoring of (h, r, ?) or (?, r, t) queries (against all entities in the knowledge graph, or a query-specific set) returning the top-k most likely completions, based on the BESS <span id="id4">[<a class="reference internal" href="../bibliography.html#id11" title="Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr, Jerome Maloberti, Zhenying Liu, Thorin Farnsworth, Andrew Fitzgibbon, Blazej Banaszewski, and Carlo Luschi. BESS: balanced entity sampling and sharing for large-scale knowledge graph completion. arXiv preprint arXiv:2211.12281, 2022.">CJM+22</a>]</span> inference scheme.</p></td>
 </tr>
 </tbody>
 </table>
@@ -121,7 +126,7 @@
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diff --git a/generated/besskge.dataset.KGDataset.html b/generated/besskge.dataset.KGDataset.html
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@@ -46,6 +46,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2 current"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a><ul class="current">
 <li class="toctree-l3 current"><a class="current reference internal" href="#">besskge.dataset.KGDataset</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="#besskge.dataset.KGDataset"><code class="docutils literal notranslate"><span class="pre">KGDataset</span></code></a></li>
@@ -221,12 +222,12 @@ <h1>besskge.dataset.KGDataset<a class="headerlink" href="#besskge-dataset-kgdata
 <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>df</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="http://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v2.2.0.dev0+401.g70a11418a7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>, <a class="reference external" href="http://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v2.2.0.dev0+401.g70a11418a7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code></a>]]) – Pandas DataFrame of all triples in the knowledge graph dataset,
+<li><p><strong>df</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="http://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v2.2.0.dev0+469.gb7ab856124)"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>, <a class="reference external" href="http://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.DataFrame.html#pandas.DataFrame" title="(in pandas v2.2.0.dev0+469.gb7ab856124)"><code class="xref py py-class docutils literal notranslate"><span class="pre">DataFrame</span></code></a>]]) – Pandas DataFrame of all triples in the knowledge graph dataset,
 or dictionary of DataFrames of triples for each part of the dataset split</p></li>
 <li><p><strong>head_column</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>]) – Name of the DataFrame column storing head entities</p></li>
 <li><p><strong>relation_column</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>]) – Name of the DataFrame column storing relations</p></li>
 <li><p><strong>tail_column</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>]) – Name of the DataFrame column storing tail entities</p></li>
-<li><p><strong>entity_types</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="http://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v2.2.0.dev0+401.g70a11418a7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Series</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>], <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></a>]) – If entities have types, dictionary or pandas Series of mappings
+<li><p><strong>entity_types</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="http://pandas.pydata.org/pandas-docs/dev/reference/api/pandas.Series.html#pandas.Series" title="(in pandas v2.2.0.dev0+469.gb7ab856124)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Series</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>], <a class="reference external" href="https://docs.python.org/3/library/constants.html#None" title="(in Python v3.12)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">None</span></code></a>]) – If entities have types, dictionary or pandas Series of mappings
 entity label -&gt; entity type (as strings).</p></li>
 <li><p><strong>split</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Tuple" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Tuple</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a>]) – Tuple to set the train/validation/test split.
 Only used if no pre-defined dataset split is specified,
diff --git a/generated/besskge.dataset.html b/generated/besskge.dataset.html
index 510a569..21c2204 100644
--- a/generated/besskge.dataset.html
+++ b/generated/besskge.dataset.html
@@ -19,7 +19,7 @@
     <link rel="index" title="Index" href="../genindex.html" />
     <link rel="search" title="Search" href="../search.html" />
     <link rel="next" title="besskge.dataset.KGDataset" href="besskge.dataset.KGDataset.html" />
-    <link rel="prev" title="BESS-KGE API Reference" href="../API_reference.html" /> 
+    <link rel="prev" title="besskge.pipeline.AllScoresPipeline" href="besskge.pipeline.AllScoresPipeline.html" /> 
 </head>
 
 <body class="wy-body-for-nav"> 
@@ -46,6 +46,7 @@
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2 current"><a class="current reference internal" href="#">besskge.dataset</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="besskge.dataset.KGDataset.html">besskge.dataset.KGDataset</a></li>
 </ul>
@@ -108,7 +109,7 @@
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           <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
-        <a href="../API_reference.html" class="btn btn-neutral float-left" title="BESS-KGE API Reference" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
+        <a href="besskge.pipeline.AllScoresPipeline.html" class="btn btn-neutral float-left" title="besskge.pipeline.AllScoresPipeline" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
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diff --git a/generated/besskge.embedding.html b/generated/besskge.embedding.html
index 0579f5f..78cfb42 100644
--- a/generated/besskge.embedding.html
+++ b/generated/besskge.embedding.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.embedding.init_KGE_normal.html b/generated/besskge.embedding.init_KGE_normal.html
index 5c7883d..5ad0e1d 100644
--- a/generated/besskge.embedding.init_KGE_normal.html
+++ b/generated/besskge.embedding.init_KGE_normal.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.embedding.init_KGE_uniform.html b/generated/besskge.embedding.init_KGE_uniform.html
index beab19d..553f276 100644
--- a/generated/besskge.embedding.init_KGE_uniform.html
+++ b/generated/besskge.embedding.init_KGE_uniform.html
@@ -46,6 +46,7 @@
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.embedding.init_uniform_norm.html b/generated/besskge.embedding.init_uniform_norm.html
index dbc927c..423faae 100644
--- a/generated/besskge.embedding.init_uniform_norm.html
+++ b/generated/besskge.embedding.init_uniform_norm.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.embedding.initialize_entity_embedding.html b/generated/besskge.embedding.initialize_entity_embedding.html
index 2384db6..85624e2 100644
--- a/generated/besskge.embedding.initialize_entity_embedding.html
+++ b/generated/besskge.embedding.initialize_entity_embedding.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.embedding.initialize_relation_embedding.html b/generated/besskge.embedding.initialize_relation_embedding.html
index e2acd99..0fbc006 100644
--- a/generated/besskge.embedding.initialize_relation_embedding.html
+++ b/generated/besskge.embedding.initialize_relation_embedding.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.embedding.refactor_embedding_sharding.html b/generated/besskge.embedding.refactor_embedding_sharding.html
index a61c25a..1fb6b73 100644
--- a/generated/besskge.embedding.refactor_embedding_sharding.html
+++ b/generated/besskge.embedding.refactor_embedding_sharding.html
@@ -46,6 +46,7 @@
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.loss.BaseLossFunction.html b/generated/besskge.loss.BaseLossFunction.html
index f9933f1..50e689b 100644
--- a/generated/besskge.loss.BaseLossFunction.html
+++ b/generated/besskge.loss.BaseLossFunction.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.loss.LogSigmoidLoss.html b/generated/besskge.loss.LogSigmoidLoss.html
index a5b41b9..2a95461 100644
--- a/generated/besskge.loss.LogSigmoidLoss.html
+++ b/generated/besskge.loss.LogSigmoidLoss.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.loss.MarginBasedLossFunction.html b/generated/besskge.loss.MarginBasedLossFunction.html
index 5572a81..96f3624 100644
--- a/generated/besskge.loss.MarginBasedLossFunction.html
+++ b/generated/besskge.loss.MarginBasedLossFunction.html
@@ -46,6 +46,7 @@
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
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 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.loss.MarginRankingLoss.html b/generated/besskge.loss.MarginRankingLoss.html
index d5f8868..cd5af15 100644
--- a/generated/besskge.loss.MarginRankingLoss.html
+++ b/generated/besskge.loss.MarginRankingLoss.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
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diff --git a/generated/besskge.loss.SampledSoftmaxCrossEntropyLoss.html b/generated/besskge.loss.SampledSoftmaxCrossEntropyLoss.html
index abbd947..b5e2ceb 100644
--- a/generated/besskge.loss.SampledSoftmaxCrossEntropyLoss.html
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diff --git a/generated/besskge.loss.html b/generated/besskge.loss.html
index e1c933b..889a427 100644
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diff --git a/generated/besskge.metric.BaseMetric.html b/generated/besskge.metric.BaseMetric.html
index f747803..ce75efb 100644
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diff --git a/generated/besskge.metric.Evaluation.html b/generated/besskge.metric.Evaluation.html
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diff --git a/generated/besskge.metric.HitsAtK.html b/generated/besskge.metric.HitsAtK.html
index fefbed1..ee3841a 100644
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diff --git a/generated/besskge.metric.METRICS_DICT.html b/generated/besskge.metric.METRICS_DICT.html
index e351f1e..7c17a11 100644
--- a/generated/besskge.metric.METRICS_DICT.html
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diff --git a/generated/besskge.metric.ReciprocalRank.html b/generated/besskge.metric.ReciprocalRank.html
index 8178efe..4761087 100644
--- a/generated/besskge.metric.ReciprocalRank.html
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diff --git a/generated/besskge.metric.html b/generated/besskge.metric.html
index d376eb0..7691f36 100644
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diff --git a/generated/besskge.negative_sampler.PlaceholderNegativeSampler.html b/generated/besskge.negative_sampler.PlaceholderNegativeSampler.html
index 0706d58..9c45654 100644
--- a/generated/besskge.negative_sampler.PlaceholderNegativeSampler.html
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diff --git a/generated/besskge.negative_sampler.RandomShardedNegativeSampler.html b/generated/besskge.negative_sampler.RandomShardedNegativeSampler.html
index 1de1dd6..c1be909 100644
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diff --git a/generated/besskge.negative_sampler.ShardedNegativeSampler.html b/generated/besskge.negative_sampler.ShardedNegativeSampler.html
index ee75865..5fa6813 100644
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diff --git a/generated/besskge.negative_sampler.TripleBasedShardedNegativeSampler.html b/generated/besskge.negative_sampler.TripleBasedShardedNegativeSampler.html
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diff --git a/generated/besskge.negative_sampler.TypeBasedShardedNegativeSampler.html b/generated/besskge.negative_sampler.TypeBasedShardedNegativeSampler.html
index 9e4cdaa..e54143b 100644
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diff --git a/generated/besskge.negative_sampler.html b/generated/besskge.negative_sampler.html
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diff --git a/generated/besskge.pipeline.AllScoresPipeline.html b/generated/besskge.pipeline.AllScoresPipeline.html
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+<h1>besskge.pipeline.AllScoresPipeline<a class="headerlink" href="#besskge-pipeline-allscorespipeline" title="Permalink to this heading"></a></h1>
+<dl class="py class">
+<dt class="sig sig-object py" id="besskge.pipeline.AllScoresPipeline">
+<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">besskge.pipeline.</span></span><span class="sig-name descname"><span class="pre">AllScoresPipeline</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">batch_sampler</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">corruption_scheme</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">score_fn</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">evaluation</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filter_triples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_scores</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">return_topk</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">k</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">10</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">window_size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1000</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">use_ipu_model</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/besskge/pipeline.html#AllScoresPipeline"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#besskge.pipeline.AllScoresPipeline" title="Permalink to this definition"></a></dt>
+<dd><p>Pipeline to compute scores of (h, r, ?) / (?, r, t) queries against all entities
+in the KG, and related prediction metrics.
+It supports filtering out the scores of specific completions that appear in a given
+set of triples.</p>
+<p>To be used in combination with a batch sampler based on a
+“h_shard”/”t_shard”-partitioned triple set.</p>
+<p>Initialize pipeline.</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>batch_sampler</strong> (<a class="reference internal" href="besskge.batch_sampler.ShardedBatchSampler.html#besskge.batch_sampler.ShardedBatchSampler" title="besskge.batch_sampler.ShardedBatchSampler"><code class="xref py py-class docutils literal notranslate"><span class="pre">ShardedBatchSampler</span></code></a>) – Batch sampler, based on a
+“h_shard”/”t_shard”-partitioned triple set.</p></li>
+<li><p><strong>corruption_scheme</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>) – Set to “t” to score (h, r, ?) completions, or to
+“h” to score (?, r, t) completions.</p></li>
+<li><p><strong>score_fn</strong> (<a class="reference internal" href="besskge.scoring.BaseScoreFunction.html#besskge.scoring.BaseScoreFunction" title="besskge.scoring.BaseScoreFunction"><code class="xref py py-class docutils literal notranslate"><span class="pre">BaseScoreFunction</span></code></a>) – The trained scoring function.</p></li>
+<li><p><strong>evaluation</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference internal" href="besskge.metric.Evaluation.html#besskge.metric.Evaluation" title="besskge.metric.Evaluation"><code class="xref py py-class docutils literal notranslate"><span class="pre">Evaluation</span></code></a>]) – Evaluation module, for computing metrics.
+Default: None.</p></li>
+<li><p><strong>filter_triples</strong> (<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Optional" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Optional</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.List" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">List</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Union" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Union</span></code></a>[<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>, <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.ndarray.html#numpy.ndarray" title="(in NumPy v1.26)"><code class="xref py py-class docutils literal notranslate"><span class="pre">ndarray</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Any</span></code></a>, <a class="reference external" href="https://numpy.org/doc/stable/reference/generated/numpy.dtype.html#numpy.dtype" title="(in NumPy v1.26)"><code class="xref py py-class docutils literal notranslate"><span class="pre">dtype</span></code></a>[<code class="xref py py-class docutils literal notranslate"><span class="pre">int32</span></code>]]]]]) – The set of all triples whose scores need to be filtered.
+The triples passed here must have GLOBAL IDs for head/tail
+entities. Default: None.</p></li>
+<li><p><strong>return_scores</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool</span></code></a>) – If True, store and return scores of all queries’ completions
+(with filters applied, if specified).
+For large number of queries/entities, this can cause the host
+to go OOM.
+Default: False.</p></li>
+<li><p><strong>return_topk</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool</span></code></a>) – If True, return for each query the global IDs of the most likely
+completions, after filtering out the scores of <cite>filter_triples</cite>.
+Default: False.</p></li>
+<li><p><strong>k</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a>) – If <cite>return_topk</cite> is set to True, for each query return the
+top-k most likely predictions (after filtering). Default: 10.</p></li>
+<li><p><strong>window_size</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a>) – Size of the sliding window, namely the number of negative entities
+scored against each query at each step on IPU and returned to host.
+Should be decreased with large batch sizes, to avoid an OOM error.
+Default: 1000.</p></li>
+<li><p><strong>use_ipu_model</strong> (<a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool</span></code></a>) – Run pipeline on IPU Model instead of actual hardware. Default: False.</p></li>
+</ul>
+</dd>
+</dl>
+<dl class="py method">
+<dt class="sig sig-object py" id="besskge.pipeline.AllScoresPipeline.forward">
+<span class="sig-name descname"><span class="pre">forward</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="../_modules/besskge/pipeline.html#AllScoresPipeline.forward"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#besskge.pipeline.AllScoresPipeline.forward" title="Permalink to this definition"></a></dt>
+<dd><p>Compute scores of all completions and (possibly) metrics.</p>
+<dl class="field-list simple">
+<dt class="field-odd">Return type<span class="colon">:</span></dt>
+<dd class="field-odd"><p><a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Dict" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Dict</span></code></a>[<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>, <a class="reference external" href="https://docs.python.org/3/library/typing.html#typing.Any" title="(in Python v3.12)"><code class="xref py py-data docutils literal notranslate"><span class="pre">Any</span></code></a>]</p>
+</dd>
+<dt class="field-even">Returns<span class="colon">:</span></dt>
+<dd class="field-even"><p>Scores, metrics, and (if provided in batch sampler) IDs
+of inference triples (wrt partitioned_triple_set.triples)
+to order results.</p>
+</dd>
+</dl>
+</dd></dl>
+
+</dd></dl>
+
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
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+<!DOCTYPE html>
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+</ul>
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+<li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.negative_sampler.html">besskge.negative_sampler</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.bess.html">besskge.bess</a></li>
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+<li class="toctree-l2"><a class="reference internal" href="besskge.loss.html">besskge.loss</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.metric.html">besskge.metric</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.embedding.html">besskge.embedding</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.utils.html">besskge.utils</a></li>
+</ul>
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+           <div itemprop="articleBody">
+             
+  <section id="module-besskge.pipeline">
+<span id="besskge-pipeline"></span><h1>besskge.pipeline<a class="headerlink" href="#module-besskge.pipeline" title="Permalink to this heading"></a></h1>
+<p>High-level APIs for training/inference with BESS.</p>
+<p class="rubric">Classes</p>
+<table class="autosummary longtable docutils align-default">
+<tbody>
+<tr class="row-odd"><td><p><a class="reference internal" href="besskge.pipeline.AllScoresPipeline.html#besskge.pipeline.AllScoresPipeline" title="besskge.pipeline.AllScoresPipeline"><code class="xref py py-obj docutils literal notranslate"><span class="pre">AllScoresPipeline</span></code></a>(batch_sampler, ...[, ...])</p></td>
+<td><p>Pipeline to compute scores of (h, r, ?) / (?, r, t) queries against all entities in the KG, and related prediction metrics.</p></td>
+</tr>
+</tbody>
+</table>
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
+        <a href="../API_reference.html" class="btn btn-neutral float-left" title="BESS-KGE API Reference" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
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diff --git a/generated/besskge.scoring.BaseScoreFunction.html b/generated/besskge.scoring.BaseScoreFunction.html
index 3f6d410..e25588a 100644
--- a/generated/besskge.scoring.BaseScoreFunction.html
+++ b/generated/besskge.scoring.BaseScoreFunction.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../bess.html">BESS overview</a></li>
 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.scoring.BoxE.html b/generated/besskge.scoring.BoxE.html
index 28fb804..68f5418 100644
--- a/generated/besskge.scoring.BoxE.html
+++ b/generated/besskge.scoring.BoxE.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../bess.html">BESS overview</a></li>
 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.scoring.ComplEx.html b/generated/besskge.scoring.ComplEx.html
index a11d72e..2354795 100644
--- a/generated/besskge.scoring.ComplEx.html
+++ b/generated/besskge.scoring.ComplEx.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../bess.html">BESS overview</a></li>
 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.scoring.DistMult.html b/generated/besskge.scoring.DistMult.html
index 79d9b42..5e107f8 100644
--- a/generated/besskge.scoring.DistMult.html
+++ b/generated/besskge.scoring.DistMult.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../bess.html">BESS overview</a></li>
 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
diff --git a/generated/besskge.scoring.DistanceBasedScoreFunction.html b/generated/besskge.scoring.DistanceBasedScoreFunction.html
index 99b3239..1a795bd 100644
--- a/generated/besskge.scoring.DistanceBasedScoreFunction.html
+++ b/generated/besskge.scoring.DistanceBasedScoreFunction.html
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
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diff --git a/generated/besskge.scoring.InterHT.html b/generated/besskge.scoring.InterHT.html
index ee1cc46..853326b 100644
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.scoring.MatrixDecompositionScoreFunction.html b/generated/besskge.scoring.MatrixDecompositionScoreFunction.html
index ceb05fc..1adbd00 100644
--- a/generated/besskge.scoring.MatrixDecompositionScoreFunction.html
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.scoring.PairRE.html b/generated/besskge.scoring.PairRE.html
index 9918c67..9a8f71c 100644
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.scoring.RotatE.html b/generated/besskge.scoring.RotatE.html
index 40cdfb6..9606fbe 100644
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.scoring.TranS.html b/generated/besskge.scoring.TranS.html
index 8fa3398..280e2e1 100644
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.scoring.TransE.html b/generated/besskge.scoring.TransE.html
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.scoring.TripleRE.html b/generated/besskge.scoring.TripleRE.html
index 96308a8..994fd02 100644
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.scoring.html b/generated/besskge.scoring.html
index cd03c49..56fcc73 100644
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@@ -46,6 +46,7 @@
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.sharding.PartitionedTripleSet.html b/generated/besskge.sharding.PartitionedTripleSet.html
index ef39c15..8bc1ad9 100644
--- a/generated/besskge.sharding.PartitionedTripleSet.html
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@@ -46,6 +46,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.sharding.Sharding.html b/generated/besskge.sharding.Sharding.html
index a3793cc..9284e65 100644
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+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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diff --git a/generated/besskge.sharding.html b/generated/besskge.sharding.html
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diff --git a/generated/besskge.utils.complex_multiplication.html b/generated/besskge.utils.complex_multiplication.html
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
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 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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 </li>
 </ul>
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-    <link rel="next" title="How to contribute to the BESS-KGE project" href="../dev_guide.html" />
+    <link rel="next" title="besskge.utils.get_entity_filter" href="besskge.utils.get_entity_filter.html" />
     <link rel="prev" title="besskge.utils.complex_rotation" href="besskge.utils.complex_rotation.html" /> 
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@@ -46,6 +46,7 @@
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 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
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@@ -62,6 +63,7 @@
 <li class="toctree-l4"><a class="reference internal" href="#besskge.utils.gather_indices"><code class="docutils literal notranslate"><span class="pre">gather_indices()</span></code></a></li>
 </ul>
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+<li class="toctree-l3"><a class="reference internal" href="besskge.utils.get_entity_filter.html">besskge.utils.get_entity_filter</a></li>
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@@ -131,7 +133,7 @@ <h1>besskge.utils.gather_indices<a class="headerlink" href="#besskge-utils-gathe
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diff --git a/generated/besskge.utils.get_entity_filter.html b/generated/besskge.utils.get_entity_filter.html
new file mode 100644
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+<li class="toctree-l2"><a class="reference internal" href="besskge.negative_sampler.html">besskge.negative_sampler</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.bess.html">besskge.bess</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.scoring.html">besskge.scoring</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.loss.html">besskge.loss</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.metric.html">besskge.metric</a></li>
+<li class="toctree-l2"><a class="reference internal" href="besskge.embedding.html">besskge.embedding</a></li>
+<li class="toctree-l2 current"><a class="reference internal" href="besskge.utils.html">besskge.utils</a><ul class="current">
+<li class="toctree-l3"><a class="reference internal" href="besskge.utils.complex_multiplication.html">besskge.utils.complex_multiplication</a></li>
+<li class="toctree-l3"><a class="reference internal" href="besskge.utils.complex_rotation.html">besskge.utils.complex_rotation</a></li>
+<li class="toctree-l3"><a class="reference internal" href="besskge.utils.gather_indices.html">besskge.utils.gather_indices</a></li>
+<li class="toctree-l3 current"><a class="current reference internal" href="#">besskge.utils.get_entity_filter</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="#besskge.utils.get_entity_filter"><code class="docutils literal notranslate"><span class="pre">get_entity_filter()</span></code></a></li>
+</ul>
+</li>
+</ul>
+</li>
+</ul>
+</li>
+<li class="toctree-l1"><a class="reference internal" href="../dev_guide.html">Developers guide</a></li>
+<li class="toctree-l1"><a class="reference internal" href="../bibliography.html">Bibliography</a></li>
+</ul>
+
+        </div>
+      </div>
+    </nav>
+
+    <section data-toggle="wy-nav-shift" class="wy-nav-content-wrap"><nav class="wy-nav-top" aria-label="Mobile navigation menu" >
+          <i data-toggle="wy-nav-top" class="fa fa-bars"></i>
+          <a href="../index.html">BESS-KGE</a>
+      </nav>
+
+      <div class="wy-nav-content">
+        <div class="rst-content">
+          <div role="navigation" aria-label="Page navigation">
+  <ul class="wy-breadcrumbs">
+      <li><a href="../index.html" class="icon icon-home" aria-label="Home"></a></li>
+          <li class="breadcrumb-item"><a href="../API_reference.html">BESS-KGE API Reference</a></li>
+          <li class="breadcrumb-item"><a href="besskge.utils.html">besskge.utils</a></li>
+      <li class="breadcrumb-item active">besskge.utils.get_entity_filter</li>
+      <li class="wy-breadcrumbs-aside">
+            <a href="../_sources/generated/besskge.utils.get_entity_filter.rst.txt" rel="nofollow"> View page source</a>
+      </li>
+  </ul>
+  <hr/>
+</div>
+          <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
+           <div itemprop="articleBody">
+             
+  <section id="besskge-utils-get-entity-filter">
+<h1>besskge.utils.get_entity_filter<a class="headerlink" href="#besskge-utils-get-entity-filter" title="Permalink to this heading"></a></h1>
+<dl class="py function">
+<dt class="sig sig-object py" id="besskge.utils.get_entity_filter">
+<span class="sig-prename descclassname"><span class="pre">besskge.utils.</span></span><span class="sig-name descname"><span class="pre">get_entity_filter</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">triples</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filter_triples</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filter_mode</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../_modules/besskge/utils.html#get_entity_filter"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#besskge.utils.get_entity_filter" title="Permalink to this definition"></a></dt>
+<dd><p>Compare two sets of triples: for each triple (h,r,t) in the first set, find
+the entities <cite>e</cite> such that (e,r,t) (or (h,r,e), depending on <cite>filter_mode</cite>)
+appears in the second set of triples.</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>triples</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>) – shape (x, 3)
+The set of triples to construct filters for.</p></li>
+<li><p><strong>filter_triples</strong> (<a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a>) – shape (y, 3)
+The set of triples determining the head/tail entities to filter.</p></li>
+<li><p><strong>filter_mode</strong> (<a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.12)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a>) – Set to “h” to look for entities appearing as heads of the same (r,t) pair,
+or to “t” to look for entities appearing as tails of the same (h,r) pair.</p></li>
+</ul>
+</dd>
+<dt class="field-even">Return type<span class="colon">:</span></dt>
+<dd class="field-even"><p><a class="reference external" href="https://pytorch.org/docs/stable/tensors.html#torch.Tensor" title="(in PyTorch v2.1)"><code class="xref py py-class docutils literal notranslate"><span class="pre">Tensor</span></code></a></p>
+</dd>
+<dt class="field-odd">Returns<span class="colon">:</span></dt>
+<dd class="field-odd"><p>shape (z, 2)
+The sparse filters. Each row is given by a tuple (i, j), with i the index
+of the triple in <cite>triples</cite> to which the filter applies to and j the global
+ID of the entity to filter.</p>
+</dd>
+</dl>
+</dd></dl>
+
+</section>
+
+
+           </div>
+          </div>
+          <footer><div class="rst-footer-buttons" role="navigation" aria-label="Footer">
+        <a href="besskge.utils.gather_indices.html" class="btn btn-neutral float-left" title="besskge.utils.gather_indices" accesskey="p" rel="prev"><span class="fa fa-arrow-circle-left" aria-hidden="true"></span> Previous</a>
+        <a href="../dev_guide.html" class="btn btn-neutral float-right" title="How to contribute to the BESS-KGE project" accesskey="n" rel="next">Next <span class="fa fa-arrow-circle-right" aria-hidden="true"></span></a>
+    </div>
+
+  <hr/>
+
+  <div role="contentinfo">
+    <p>&#169; Copyright (c) 2023 Graphcore Ltd. All rights reserved.</p>
+  </div>
+
+  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>.
+   
+
+</footer>
+        </div>
+      </div>
+    </section>
+  </div>
+  <script>
+      jQuery(function () {
+          SphinxRtdTheme.Navigation.enable(true);
+      });
+  </script> 
+
+</body>
+</html>
\ No newline at end of file
diff --git a/generated/besskge.utils.html b/generated/besskge.utils.html
index 4e7fb02..0c46776 100644
--- a/generated/besskge.utils.html
+++ b/generated/besskge.utils.html
@@ -46,6 +46,7 @@
 <li class="toctree-l1"><a class="reference internal" href="../user_guide.html">User guide</a></li>
 <li class="toctree-l1"><a class="reference internal" href="../bess.html">BESS overview</a></li>
 <li class="toctree-l1 current"><a class="reference internal" href="../API_reference.html">API reference</a><ul class="current">
+<li class="toctree-l2"><a class="reference internal" href="besskge.pipeline.html">besskge.pipeline</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.dataset.html">besskge.dataset</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.sharding.html">besskge.sharding</a></li>
 <li class="toctree-l2"><a class="reference internal" href="besskge.batch_sampler.html">besskge.batch_sampler</a></li>
@@ -59,6 +60,7 @@
 <li class="toctree-l3"><a class="reference internal" href="besskge.utils.complex_multiplication.html">besskge.utils.complex_multiplication</a></li>
 <li class="toctree-l3"><a class="reference internal" href="besskge.utils.complex_rotation.html">besskge.utils.complex_rotation</a></li>
 <li class="toctree-l3"><a class="reference internal" href="besskge.utils.gather_indices.html">besskge.utils.gather_indices</a></li>
+<li class="toctree-l3"><a class="reference internal" href="besskge.utils.get_entity_filter.html">besskge.utils.get_entity_filter</a></li>
 </ul>
 </li>
 </ul>
@@ -107,6 +109,9 @@
 <tr class="row-odd"><td><p><a class="reference internal" href="besskge.utils.gather_indices.html#besskge.utils.gather_indices" title="besskge.utils.gather_indices"><code class="xref py py-obj docutils literal notranslate"><span class="pre">gather_indices</span></code></a>(x, index)</p></td>
 <td><p>IPU-friendly gather function like <a class="reference external" href="https://pytorch.org/docs/stable/generated/torch.take_along_dim.html#torch.take_along_dim" title="(in PyTorch v2.1)"><code class="xref py py-func docutils literal notranslate"><span class="pre">torch.take_along_dim()</span></code></a> for 2-dimensional tensors (indices along dim=1).</p></td>
 </tr>
+<tr class="row-even"><td><p><a class="reference internal" href="besskge.utils.get_entity_filter.html#besskge.utils.get_entity_filter" title="besskge.utils.get_entity_filter"><code class="xref py py-obj docutils literal notranslate"><span class="pre">get_entity_filter</span></code></a>(triples, filter_triples, ...)</p></td>
+<td><p>Compare two sets of triples: for each triple (h,r,t) in the first set, find the entities <cite>e</cite> such that (e,r,t) (or (h,r,e), depending on <cite>filter_mode</cite>) appears in the second set of triples.</p></td>
+</tr>
 </tbody>
 </table>
 </section>
diff --git a/genindex.html b/genindex.html
index 39a37df..e3be28c 100644
--- a/genindex.html
+++ b/genindex.html
@@ -74,7 +74,8 @@
 <h1 id="index">Index</h1>
 
 <div class="genindex-jumpbox">
- <a href="#B"><strong>B</strong></a>
+ <a href="#A"><strong>A</strong></a>
+ | <a href="#B"><strong>B</strong></a>
  | <a href="#C"><strong>C</strong></a>
  | <a href="#D"><strong>D</strong></a>
  | <a href="#E"><strong>E</strong></a>
@@ -94,6 +95,18 @@ <h1 id="index">Index</h1>
  | <a href="#W"><strong>W</strong></a>
  
 </div>
+<h2 id="A">A</h2>
+<table style="width: 100%" class="indextable genindextable"><tr>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="generated/besskge.bess.AllScoresBESS.html#besskge.bess.AllScoresBESS">AllScoresBESS (class in besskge.bess)</a>
+</li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="generated/besskge.pipeline.AllScoresPipeline.html#besskge.pipeline.AllScoresPipeline">AllScoresPipeline (class in besskge.pipeline)</a>
+</li>
+  </ul></td>
+</tr></table>
+
 <h2 id="B">B</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
@@ -162,15 +175,22 @@ <h2 id="B">B</h2>
 </li>
       </ul></li>
       <li>
-    besskge.scoring
+    besskge.pipeline
 
       <ul>
-        <li><a href="generated/besskge.scoring.html#module-besskge.scoring">module</a>
+        <li><a href="generated/besskge.pipeline.html#module-besskge.pipeline">module</a>
 </li>
       </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li>
+    besskge.scoring
+
+      <ul>
+        <li><a href="generated/besskge.scoring.html#module-besskge.scoring">module</a>
+</li>
+      </ul></li>
+      <li>
     besskge.sharding
 
       <ul>
@@ -336,9 +356,11 @@ <h2 id="F">F</h2>
         <li><a href="generated/besskge.negative_sampler.TypeBasedShardedNegativeSampler.html#besskge.negative_sampler.TypeBasedShardedNegativeSampler.flat_negative_format">(besskge.negative_sampler.TypeBasedShardedNegativeSampler attribute)</a>
 </li>
       </ul></li>
-      <li><a href="generated/besskge.bess.BessKGE.html#besskge.bess.BessKGE.forward">forward() (besskge.bess.BessKGE method)</a>
+      <li><a href="generated/besskge.bess.AllScoresBESS.html#besskge.bess.AllScoresBESS.forward">forward() (besskge.bess.AllScoresBESS method)</a>
 
       <ul>
+        <li><a href="generated/besskge.bess.BessKGE.html#besskge.bess.BessKGE.forward">(besskge.bess.BessKGE method)</a>
+</li>
         <li><a href="generated/besskge.bess.EmbeddingMovingBessKGE.html#besskge.bess.EmbeddingMovingBessKGE.forward">(besskge.bess.EmbeddingMovingBessKGE method)</a>
 </li>
         <li><a href="generated/besskge.bess.ScoreMovingBessKGE.html#besskge.bess.ScoreMovingBessKGE.forward">(besskge.bess.ScoreMovingBessKGE method)</a>
@@ -354,6 +376,8 @@ <h2 id="F">F</h2>
         <li><a href="generated/besskge.loss.MarginRankingLoss.html#besskge.loss.MarginRankingLoss.forward">(besskge.loss.MarginRankingLoss method)</a>
 </li>
         <li><a href="generated/besskge.loss.SampledSoftmaxCrossEntropyLoss.html#besskge.loss.SampledSoftmaxCrossEntropyLoss.forward">(besskge.loss.SampledSoftmaxCrossEntropyLoss method)</a>
+</li>
+        <li><a href="generated/besskge.pipeline.AllScoresPipeline.html#besskge.pipeline.AllScoresPipeline.forward">(besskge.pipeline.AllScoresPipeline method)</a>
 </li>
         <li><a href="generated/besskge.scoring.BaseScoreFunction.html#besskge.scoring.BaseScoreFunction.forward">(besskge.scoring.BaseScoreFunction method)</a>
 </li>
@@ -412,6 +436,8 @@ <h2 id="G">G</h2>
       </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
+      <li><a href="generated/besskge.utils.get_entity_filter.html#besskge.utils.get_entity_filter">get_entity_filter() (in module besskge.utils)</a>
+</li>
       <li><a href="generated/besskge.loss.BaseLossFunction.html#besskge.loss.BaseLossFunction.get_negative_weights">get_negative_weights() (besskge.loss.BaseLossFunction method)</a>
 
       <ul>
@@ -541,6 +567,8 @@ <h2 id="M">M</h2>
         <li><a href="generated/besskge.metric.html#module-besskge.metric">besskge.metric</a>
 </li>
         <li><a href="generated/besskge.negative_sampler.html#module-besskge.negative_sampler">besskge.negative_sampler</a>
+</li>
+        <li><a href="generated/besskge.pipeline.html#module-besskge.pipeline">besskge.pipeline</a>
 </li>
         <li><a href="generated/besskge.scoring.html#module-besskge.scoring">besskge.scoring</a>
 </li>
diff --git a/index.html b/index.html
index 4c3f826..54ee68c 100644
--- a/index.html
+++ b/index.html
@@ -103,6 +103,10 @@
 </li>
 <li class="toctree-l1"><a class="reference internal" href="bess.html">BESS overview</a></li>
 <li class="toctree-l1"><a class="reference internal" href="API_reference.html">API reference</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="generated/besskge.pipeline.html">besskge.pipeline</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="generated/besskge.pipeline.AllScoresPipeline.html">besskge.pipeline.AllScoresPipeline</a></li>
+</ul>
+</li>
 <li class="toctree-l2"><a class="reference internal" href="generated/besskge.dataset.html">besskge.dataset</a><ul>
 <li class="toctree-l3"><a class="reference internal" href="generated/besskge.dataset.KGDataset.html">besskge.dataset.KGDataset</a></li>
 </ul>
@@ -127,6 +131,7 @@
 </ul>
 </li>
 <li class="toctree-l2"><a class="reference internal" href="generated/besskge.bess.html">besskge.bess</a><ul>
+<li class="toctree-l3"><a class="reference internal" href="generated/besskge.bess.AllScoresBESS.html">besskge.bess.AllScoresBESS</a></li>
 <li class="toctree-l3"><a class="reference internal" href="generated/besskge.bess.BessKGE.html">besskge.bess.BessKGE</a></li>
 <li class="toctree-l3"><a class="reference internal" href="generated/besskge.bess.EmbeddingMovingBessKGE.html">besskge.bess.EmbeddingMovingBessKGE</a></li>
 <li class="toctree-l3"><a class="reference internal" href="generated/besskge.bess.ScoreMovingBessKGE.html">besskge.bess.ScoreMovingBessKGE</a></li>
@@ -177,6 +182,7 @@
 <li class="toctree-l3"><a class="reference internal" href="generated/besskge.utils.complex_multiplication.html">besskge.utils.complex_multiplication</a></li>
 <li class="toctree-l3"><a class="reference internal" href="generated/besskge.utils.complex_rotation.html">besskge.utils.complex_rotation</a></li>
 <li class="toctree-l3"><a class="reference internal" href="generated/besskge.utils.gather_indices.html">besskge.utils.gather_indices</a></li>
+<li class="toctree-l3"><a class="reference internal" href="generated/besskge.utils.get_entity_filter.html">besskge.utils.get_entity_filter</a></li>
 </ul>
 </li>
 </ul>
diff --git a/objects.inv b/objects.inv
index 22e6f52..e2a7e02 100644
Binary files a/objects.inv and b/objects.inv differ
diff --git a/py-modindex.html b/py-modindex.html
index 8a95a97..d6519a0 100644
--- a/py-modindex.html
+++ b/py-modindex.html
@@ -125,6 +125,11 @@ <h1>Python Module Index</h1>
        <td>&#160;&#160;&#160;
        <a href="generated/besskge.negative_sampler.html#module-besskge.negative_sampler"><code class="xref">besskge.negative_sampler</code></a></td><td>
        <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="generated/besskge.pipeline.html#module-besskge.pipeline"><code class="xref">besskge.pipeline</code></a></td><td>
+       <em></em></td></tr>
      <tr class="cg-1">
        <td></td>
        <td>&#160;&#160;&#160;
diff --git a/searchindex.js b/searchindex.js
index 3b7b9af..8fc6ee6 100644
--- a/searchindex.js
+++ b/searchindex.js
@@ -1 +1 @@
-Search.setIndex({"docnames": ["API_reference", "bess", "bibliography", "contrib", "dev_guide", "generated/besskge.batch_sampler", "generated/besskge.batch_sampler.RandomShardedBatchSampler", "generated/besskge.batch_sampler.RigidShardedBatchSampler", "generated/besskge.batch_sampler.ShardedBatchSampler", "generated/besskge.bess", "generated/besskge.bess.BessKGE", "generated/besskge.bess.EmbeddingMovingBessKGE", "generated/besskge.bess.ScoreMovingBessKGE", "generated/besskge.bess.TopKQueryBessKGE", "generated/besskge.dataset", "generated/besskge.dataset.KGDataset", "generated/besskge.embedding", "generated/besskge.embedding.init_KGE_normal", "generated/besskge.embedding.init_KGE_uniform", "generated/besskge.embedding.init_uniform_norm", "generated/besskge.embedding.initialize_entity_embedding", "generated/besskge.embedding.initialize_relation_embedding", "generated/besskge.embedding.refactor_embedding_sharding", "generated/besskge.loss", "generated/besskge.loss.BaseLossFunction", 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"besskge.sharding.Sharding.entity_type_counts"]], "entity_type_offsets (besskge.sharding.sharding attribute)": [[59, "besskge.sharding.Sharding.entity_type_offsets"]], "load() (besskge.sharding.sharding class method)": [[59, "besskge.sharding.Sharding.load"]], "max_entity_per_shard (besskge.sharding.sharding property)": [[59, "besskge.sharding.Sharding.max_entity_per_shard"]], "n_entity (besskge.sharding.sharding property)": [[59, "besskge.sharding.Sharding.n_entity"]], "n_shard (besskge.sharding.sharding attribute)": [[59, "besskge.sharding.Sharding.n_shard"]], "save() (besskge.sharding.sharding method)": [[59, "besskge.sharding.Sharding.save"]], "shard_and_idx_to_entity (besskge.sharding.sharding attribute)": [[59, "besskge.sharding.Sharding.shard_and_idx_to_entity"]], "shard_counts (besskge.sharding.sharding attribute)": [[59, "besskge.sharding.Sharding.shard_counts"]], "besskge.utils": [[60, "module-besskge.utils"]], "complex_multiplication() (in module besskge.utils)": [[61, "besskge.utils.complex_multiplication"]], "complex_rotation() (in module besskge.utils)": [[62, "besskge.utils.complex_rotation"]], "gather_indices() (in module besskge.utils)": [[63, "besskge.utils.gather_indices"]], "get_entity_filter() (in module besskge.utils)": [[64, "besskge.utils.get_entity_filter"]], "besskge": [[65, "module-besskge"]]}})
\ No newline at end of file