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<h1>Database for nearest neighbor retrieval</h1>
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<p>This is the build the database and retrieves nearest neighbors for <a href="index.html">RETRO model</a>.</p>
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<p>We use <a href="https://faiss.ai/">FAISS library</a> for the database whilst the paper had used the SCaNN library.</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">16</span><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Optional</span>
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<span class="lineno">17</span>
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<span class="lineno">18</span><span class="kn">import</span> <span class="nn">faiss</span>
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<span class="lineno">19</span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
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<span class="lineno">20</span><span class="kn">import</span> <span class="nn">torch</span>
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<span class="lineno">21</span>
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<span class="lineno">22</span><span class="kn">from</span> <span class="nn">labml</span> <span class="kn">import</span> <span class="n">lab</span><span class="p">,</span> <span class="n">monit</span>
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<span class="lineno">23</span><span class="kn">from</span> <span class="nn">labml_helpers.datasets.text</span> <span class="kn">import</span> <span class="n">TextFileDataset</span>
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<span class="lineno">24</span><span class="kn">from</span> <span class="nn">labml_nn.transformers.retro.bert_embeddings</span> <span class="kn">import</span> <span class="n">BERTChunkEmbeddings</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-1'>
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-1'>#</a>
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</div>
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<h2>Build Database</h2>
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<ul><li><code class="highlight"><span></span><span class="n">chunk_len</span></code>
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is the length of a chunk (number of characters) </li>
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<li><code class="highlight"><span></span><span class="n">batch_size</span></code>
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is the batch size to use when calculating <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqa" style=""><span class="mord text" style=""><span class="mord" style="">B</span><span class="mord sizing reset-size6 size5" style=""><span class="mord" style="">ERT</span></span></span><span class="mopen" style="">(</span><span class="mord mathnormal" style="margin-right:0.10903em">N</span><span class="mclose" style="">)</span></span></span></span></span></span> </li>
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<li><code class="highlight"><span></span><span class="n">d_emb</span></code>
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is the number of features in <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqa" style=""><span class="mord text" style=""><span class="mord" style="">B</span><span class="mord sizing reset-size6 size5" style=""><span class="mord" style="">ERT</span></span></span><span class="mopen" style="">(</span><span class="mord mathnormal" style="margin-right:0.10903em">N</span><span class="mclose" style="">)</span></span></span></span></span></span> embeddings <a href="https://faiss.ai/cpp_api/struct/structfaiss_1_1IndexIVFPQ.html">lists to select in FAISS index</a> </li>
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<li><code class="highlight"><span></span><span class="n">n_centeroids</span></code>
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is the number of lists in the index </li>
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<li><code class="highlight"><span></span><span class="n">code_size</span></code>
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encoded vector size in the index </li>
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<li><code class="highlight"><span></span><span class="n">n_probe</span></code>
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is the number of lists to probe </li>
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<li>`n_train' is the number of keys to train the index on</li></ul>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">27</span><span class="k">def</span> <span class="nf">build_database</span><span class="p">(</span><span class="n">chunk_len</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">64</span><span class="p">,</span> <span class="n">d_emb</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">768</span><span class="p">,</span> <span class="n">n_centeroids</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">256</span><span class="p">,</span>
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<span class="lineno">28</span> <span class="n">code_size</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">64</span><span class="p">,</span> <span class="n">n_probe</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">8</span><span class="p">,</span> <span class="n">n_train</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">50_000</span><span class="p">):</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-2'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-2'>#</a>
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</div>
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<p>Load the dataset text file </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">43</span> <span class="n">dataset</span> <span class="o">=</span> <span class="n">TextFileDataset</span><span class="p">(</span>
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<span class="lineno">44</span> <span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'tiny_shakespeare.txt'</span><span class="p">,</span>
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<span class="lineno">45</span> <span class="nb">list</span><span class="p">,</span>
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<span class="lineno">46</span> <span class="n">url</span><span class="o">=</span><span class="s1">'https://raw.githubusercontent.com/karpathy/char-rnn/master/data/tinyshakespeare/input.txt'</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-3'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-3'>#</a>
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</div>
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<p>Get training data (a string) </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">49</span> <span class="n">text</span> <span class="o">=</span> <span class="n">dataset</span><span class="o">.</span><span class="n">train</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-4'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-4'>#</a>
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</div>
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<p>Split the text into chunks of <code class="highlight"><span></span><span class="n">chunk_length</span></code>
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</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">52</span> <span class="n">chunks</span> <span class="o">=</span> <span class="p">[</span><span class="n">text</span><span class="p">[</span><span class="n">i</span><span class="p">:</span><span class="n">i</span> <span class="o">+</span> <span class="n">chunk_len</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="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">text</span><span class="p">),</span> <span class="n">chunk_len</span><span class="p">)</span> <span class="k">if</span> <span class="n">i</span> <span class="o">+</span> <span class="n">chunk_len</span> <span class="o">*</span> <span class="mi">2</span> <span class="o"><</span> <span class="nb">len</span><span class="p">(</span><span class="n">text</span><span class="p">)]</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-5'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-5'>#</a>
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</div>
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<p>Get the offsets of each of the chunks </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">54</span> <span class="n">chunk_offsets</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">i</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="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">text</span><span class="p">),</span> <span class="n">chunk_len</span><span class="p">)</span> <span class="k">if</span> <span class="n">i</span> <span class="o">+</span> <span class="n">chunk_len</span> <span class="o">*</span> <span class="mi">2</span> <span class="o"><</span> <span class="nb">len</span><span class="p">(</span><span class="n">text</span><span class="p">)])</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-6'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-6'>#</a>
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</div>
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<p>Number of chunks </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">56</span> <span class="n">n_chunks</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">chunks</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-7'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-7'>#</a>
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</div>
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<p>Initialize BERT to get <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqa" style=""><span class="mord text" style=""><span class="mord" style="">B</span><span class="mord sizing reset-size6 size5" style=""><span class="mord" style="">ERT</span></span></span><span class="mopen" style="">(</span><span class="mord mathnormal" style="margin-right:0.10903em">N</span><span class="mclose" style="">)</span></span></span></span></span></span> </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">59</span> <span class="n">bert</span> <span class="o">=</span> <span class="n">BERTChunkEmbeddings</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s1">'cuda:0'</span><span class="p">))</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-8'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-8'>#</a>
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</div>
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<p>Get chunk embeddings by processing <code class="highlight"><span></span><span class="n">batch_size</span></code>
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number of chunks on each iteration </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">62</span> <span class="n">chunk_emb</span> <span class="o">=</span> <span class="p">[]</span>
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<span class="lineno">63</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">monit</span><span class="o">.</span><span class="n">iterate</span><span class="p">(</span><span class="s1">'Get embeddings'</span><span class="p">,</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n_chunks</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)):</span>
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<span class="lineno">64</span> <span class="n">chunk_emb</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">bert</span><span class="p">(</span><span class="n">chunks</span><span class="p">[</span><span class="n">i</span><span class="p">:</span> <span class="n">i</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">])</span><span class="o">.</span><span class="n">cpu</span><span class="p">())</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-9'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-9'>#</a>
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</div>
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<p>Merge them into a single tensor </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">66</span> <span class="n">chunk_emb</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">cat</span><span class="p">(</span><span class="n">chunk_emb</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="o">.</span><span class="n">numpy</span><span class="p">()</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-10'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-10'>#</a>
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</div>
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<p>Create the <a href="https://faiss.ai/cpp_api/struct/structfaiss_1_1IndexIVFPQ.html">FAISS index</a> </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">69</span> <span class="n">quantizer</span> <span class="o">=</span> <span class="n">faiss</span><span class="o">.</span><span class="n">IndexFlatL2</span><span class="p">(</span><span class="n">d_emb</span><span class="p">)</span>
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<span class="lineno">70</span> <span class="n">index</span> <span class="o">=</span> <span class="n">faiss</span><span class="o">.</span><span class="n">IndexIVFPQ</span><span class="p">(</span><span class="n">quantizer</span><span class="p">,</span> <span class="n">d_emb</span><span class="p">,</span> <span class="n">n_centeroids</span><span class="p">,</span> <span class="n">code_size</span><span class="p">,</span> <span class="mi">8</span><span class="p">)</span>
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<span class="lineno">71</span> <span class="n">index</span><span class="o">.</span><span class="n">nprobe</span> <span class="o">=</span> <span class="n">n_probe</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-11'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-11'>#</a>
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</div>
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<p>Get a random sample of the the chunk indexes </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">74</span> <span class="n">random_sample</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">n_chunks</span><span class="p">),</span> <span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="nb">min</span><span class="p">(</span><span class="n">n_train</span><span class="p">,</span> <span class="n">n_chunks</span><span class="p">)],</span> <span class="n">replace</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-12'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-12'>#</a>
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</div>
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<p>Train the index to store the keys </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">77</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Train index'</span><span class="p">):</span>
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|
<span class="lineno">78</span> <span class="n">index</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">chunk_emb</span><span class="p">[</span><span class="n">random_sample</span><span class="p">])</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-13'>
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<div class='docs'>
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|
<div class='section-link'>
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<a href='#section-13'>#</a>
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</div>
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<p>Add the chunks to the index in batches of size <code class="highlight"><span></span><span class="mi">1024</span></code>
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</p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">81</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">monit</span><span class="o">.</span><span class="n">iterate</span><span class="p">(</span><span class="s1">'Index'</span><span class="p">,</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n_chunks</span><span class="p">,</span> <span class="mi">1024</span><span class="p">)):</span>
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<span class="lineno">82</span> <span class="n">e</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">s</span> <span class="o">+</span> <span class="mi">1024</span><span class="p">,</span> <span class="n">n_chunks</span><span class="p">)</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-14'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-14'>#</a>
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</div>
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<p>Add to index </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">84</span> <span class="n">index</span><span class="o">.</span><span class="n">add_with_ids</span><span class="p">(</span><span class="n">chunk_emb</span><span class="p">[</span><span class="n">s</span><span class="p">:</span><span class="n">e</span><span class="p">],</span> <span class="n">chunk_offsets</span><span class="p">[</span><span class="n">s</span><span class="p">:</span> <span class="n">e</span><span class="p">])</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-15'>
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<div class='docs'>
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<div class='section-link'>
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<a href='#section-15'>#</a>
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</div>
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<p>Save the index </p>
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">87</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Save'</span><span class="p">):</span>
|
|
<span class="lineno">88</span> <span class="n">faiss</span><span class="o">.</span><span class="n">write_index</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'retro.index'</span><span class="p">))</span></pre></div>
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</div>
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</div>
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<div class='section' id='section-16'>
|
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<div class='docs doc-strings'>
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<div class='section-link'>
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<a href='#section-16'>#</a>
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</div>
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<h2>Index for retrieving nearest neighbors</h2>
|
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</div>
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<div class='code'>
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<div class="highlight"><pre><span class="lineno">91</span><span class="k">class</span> <span class="nc">RetroIndex</span><span class="p">:</span></pre></div>
|
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</div>
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</div>
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<div class='section' id='section-17'>
|
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<div class='docs doc-strings'>
|
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<div class='section-link'>
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<a href='#section-17'>#</a>
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</div>
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<ul><li><code class="highlight"><span></span><span class="n">chunk_len</span></code>
|
|
is the chunk length </li>
|
|
<li><code class="highlight"><span></span><span class="n">n_probe</span></code>
|
|
is the number of lists to probe </li>
|
|
<li><code class="highlight"><span></span><span class="n">n_neighbors</span></code>
|
|
is the number of neighbors to retrieve </li>
|
|
<li><code class="highlight"><span></span><span class="n">n_extra</span></code>
|
|
is the number of extra neighbors to retrieve since we will be removing neighbors overlapping with the query chunk </li>
|
|
<li><code class="highlight"><span></span><span class="n">exclude_neighbor_span</span></code>
|
|
is the extra text length to avoid when checking for overlaps</li></ul>
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</div>
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<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">96</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">chunk_len</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">16</span><span class="p">,</span> <span class="n">n_probe</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">8</span><span class="p">,</span>
|
|
<span class="lineno">97</span> <span class="n">n_neighbors</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span> <span class="n">n_extra</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">2</span><span class="p">,</span>
|
|
<span class="lineno">98</span> <span class="n">exclude_neighbor_span</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">8</span><span class="p">):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-18'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-18'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">108</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_neighbors</span> <span class="o">=</span> <span class="n">n_neighbors</span>
|
|
<span class="lineno">109</span> <span class="bp">self</span><span class="o">.</span><span class="n">chunk_len</span> <span class="o">=</span> <span class="n">chunk_len</span>
|
|
<span class="lineno">110</span> <span class="bp">self</span><span class="o">.</span><span class="n">exclude_neighbor_span</span> <span class="o">=</span> <span class="n">exclude_neighbor_span</span>
|
|
<span class="lineno">111</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_extra</span> <span class="o">=</span> <span class="n">n_extra</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-19'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-19'>#</a>
|
|
</div>
|
|
<p>Initialize BERT to get <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqa" style=""><span class="mord text" style=""><span class="mord" style="">B</span><span class="mord sizing reset-size6 size5" style=""><span class="mord" style="">ERT</span></span></span><span class="mopen" style="">(</span><span class="mord mathnormal" style="margin-right:0.10903em">N</span><span class="mclose" style="">)</span></span></span></span></span></span> </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">114</span> <span class="bp">self</span><span class="o">.</span><span class="n">bert</span> <span class="o">=</span> <span class="n">BERTChunkEmbeddings</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">device</span><span class="p">(</span><span class="s1">'cuda:0'</span><span class="p">))</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-20'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-20'>#</a>
|
|
</div>
|
|
<p>Load the database </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">116</span> <span class="k">with</span> <span class="n">monit</span><span class="o">.</span><span class="n">section</span><span class="p">(</span><span class="s1">'Load index'</span><span class="p">):</span>
|
|
<span class="lineno">117</span> <span class="bp">self</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">faiss</span><span class="o">.</span><span class="n">read_index</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">lab</span><span class="o">.</span><span class="n">get_data_path</span><span class="p">()</span> <span class="o">/</span> <span class="s1">'retro.index'</span><span class="p">))</span>
|
|
<span class="lineno">118</span> <span class="bp">self</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">nprobe</span> <span class="o">=</span> <span class="n">n_probe</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-21'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-21'>#</a>
|
|
</div>
|
|
<h4>Filter neighbors that overlap with the query</h4>
|
|
<p>The positions of the neighbors are given by <code class="highlight"><span></span><span class="n">neighbor_offsets</span></code>
|
|
and the position of the query chunk is <code class="highlight"><span></span><span class="n">offset</span></code>
|
|
.</p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">120</span> <span class="k">def</span> <span class="nf">filter_neighbors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">offset</span><span class="p">:</span> <span class="nb">int</span><span class="p">,</span> <span class="n">neighbor_offsets</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">int</span><span class="p">]):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-22'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-22'>#</a>
|
|
</div>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">127</span> <span class="k">return</span> <span class="p">[</span><span class="n">n</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">neighbor_offsets</span>
|
|
<span class="lineno">128</span> <span class="k">if</span> <span class="n">n</span> <span class="o"><</span> <span class="n">offset</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_len</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">exclude_neighbor_span</span><span class="p">)</span>
|
|
<span class="lineno">129</span> <span class="ow">or</span> <span class="n">n</span> <span class="o">></span> <span class="n">offset</span> <span class="o">+</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">chunk_len</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">exclude_neighbor_span</span><span class="p">)]</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-23'>
|
|
<div class='docs doc-strings'>
|
|
<div class='section-link'>
|
|
<a href='#section-23'>#</a>
|
|
</div>
|
|
<h3>Retrieve nearest neighbors</h3>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">131</span> <span class="k">def</span> <span class="fm">__call__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">query_chunks</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">],</span> <span class="n">offsets</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="nb">int</span><span class="p">]]):</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-24'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-24'>#</a>
|
|
</div>
|
|
<p>Get <span ><span class="katex"><span aria-hidden="true" class="katex-html"><span class="base"><span class="strut" style="height:1em;vertical-align:-0.25em;"></span><span class="mord coloredeq eqa" style=""><span class="mord text" style=""><span class="mord" style="">B</span><span class="mord sizing reset-size6 size5" style=""><span class="mord" style="">ERT</span></span></span><span class="mopen" style="">(</span><span class="mord mathnormal" style="margin-right:0.10903em">N</span><span class="mclose" style="">)</span></span></span></span></span></span> of query chunks </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">137</span> <span class="n">emb</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bert</span><span class="p">(</span><span class="n">query_chunks</span><span class="p">)</span><span class="o">.</span><span class="n">cpu</span><span class="p">()</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-25'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-25'>#</a>
|
|
</div>
|
|
<p>Get <code class="highlight"><span></span><span class="n">n_neighbors</span> <span class="o">+</span> <span class="n">n_extra</span></code>
|
|
nearest neighbors from the database </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">140</span> <span class="n">distance</span><span class="p">,</span> <span class="n">neighbor_offsets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">search</span><span class="p">(</span><span class="n">emb</span><span class="o">.</span><span class="n">numpy</span><span class="p">(),</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_neighbors</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">n_extra</span><span class="p">)</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-26'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-26'>#</a>
|
|
</div>
|
|
<p>If the query chunk offsets are given filter out overlapping chunks </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">143</span> <span class="k">if</span> <span class="n">offsets</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
|
<span class="lineno">144</span> <span class="n">neighbor_offsets</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">filter_neighbors</span><span class="p">(</span><span class="n">off</span><span class="p">,</span> <span class="n">n_off</span><span class="p">)</span>
|
|
<span class="lineno">145</span> <span class="k">for</span> <span class="n">off</span><span class="p">,</span> <span class="n">n_off</span> <span class="ow">in</span> <span class="nb">zip</span><span class="p">(</span><span class="n">offsets</span><span class="p">,</span> <span class="n">neighbor_offsets</span><span class="p">)]</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-27'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-27'>#</a>
|
|
</div>
|
|
<p>Get the closest <code class="highlight"><span></span><span class="n">n_neighbors</span></code>
|
|
after filtering </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">148</span> <span class="n">neighbor_offsets</span> <span class="o">=</span> <span class="p">[</span><span class="n">n_off</span><span class="p">[:</span><span class="bp">self</span><span class="o">.</span><span class="n">n_neighbors</span><span class="p">]</span> <span class="k">for</span> <span class="n">n_off</span> <span class="ow">in</span> <span class="n">neighbor_offsets</span><span class="p">]</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-28'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-28'>#</a>
|
|
</div>
|
|
<p> </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">151</span> <span class="k">return</span> <span class="n">neighbor_offsets</span></pre></div>
|
|
</div>
|
|
</div>
|
|
<div class='section' id='section-29'>
|
|
<div class='docs'>
|
|
<div class='section-link'>
|
|
<a href='#section-29'>#</a>
|
|
</div>
|
|
<p> </p>
|
|
|
|
</div>
|
|
<div class='code'>
|
|
<div class="highlight"><pre><span class="lineno">155</span><span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s1">'__main__'</span><span class="p">:</span>
|
|
<span class="lineno">156</span> <span class="n">build_database</span><span class="p">()</span></pre></div>
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document.body.appendChild(modal)
|
|
modalImage.src = img.src
|
|
}
|
|
|
|
span.onclick = function () {
|
|
document.body.removeChild(modal)
|
|
}
|
|
}
|
|
|
|
handleImages()
|
|
</script>
|
|
</body>
|
|
</html> |