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@ -3830,6 +3830,7 @@ the system and <code>ignore_missing=False</code>.</p></td>
<div class="doc doc-contents first"> <div class="doc doc-contents first">
<p>Return a customised logger used throughout the GreatAI codebase.</p> <p>Return a customised logger used throughout the GreatAI codebase.</p>
<p>Uses colors, and only prints timestamps when not running inside notebook.</p>
<details class="quote"> <details class="quote">
<summary>Source code in <code>great_ai/utilities/logger/get_logger.py</code></summary> <summary>Source code in <code>great_ai/utilities/logger/get_logger.py</code></summary>
@ -3851,25 +3852,43 @@ the system and <code>ignore_missing=False</code>.</p></td>
<span class="normal"><a href="#__codelineno-0-24">24</a></span> <span class="normal"><a href="#__codelineno-0-24">24</a></span>
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<span class="normal"><a href="#__codelineno-0-27">27</a></span></pre></div></td><td class="code"><div><pre><span></span><code><a id="__codelineno-0-9" name="__codelineno-0-9"></a><span class="k">def</span> <span class="nf">get_logger</span><span class="p">(</span> <span class="normal"><a href="#__codelineno-0-27">27</a></span>
<span class="normal"><a href="#__codelineno-0-28">28</a></span>
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<span class="normal"><a href="#__codelineno-0-30">30</a></span>
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<span class="normal"><a href="#__codelineno-0-35">35</a></span>
<span class="normal"><a href="#__codelineno-0-36">36</a></span></pre></div></td><td class="code"><div><pre><span></span><code><a id="__codelineno-0-9" name="__codelineno-0-9"></a><span class="k">def</span> <span class="nf">get_logger</span><span class="p">(</span>
<a id="__codelineno-0-10" name="__codelineno-0-10"></a> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">level</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">INFO</span><span class="p">,</span> <span class="n">disable_colors</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span> <a id="__codelineno-0-10" name="__codelineno-0-10"></a> <span class="n">name</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">level</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">INFO</span><span class="p">,</span> <span class="n">disable_colors</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<a id="__codelineno-0-11" name="__codelineno-0-11"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">logging</span><span class="o">.</span><span class="n">Logger</span><span class="p">:</span> <a id="__codelineno-0-11" name="__codelineno-0-11"></a><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">logging</span><span class="o">.</span><span class="n">Logger</span><span class="p">:</span>
<a id="__codelineno-0-12" name="__codelineno-0-12"></a> <span class="sd">&quot;&quot;&quot;Return a customised logger used throughout the GreatAI codebase.&quot;&quot;&quot;</span> <a id="__codelineno-0-12" name="__codelineno-0-12"></a> <span class="sd">&quot;&quot;&quot;Return a customised logger used throughout the GreatAI codebase.</span>
<a id="__codelineno-0-13" name="__codelineno-0-13"></a> <a id="__codelineno-0-13" name="__codelineno-0-13"></a>
<a id="__codelineno-0-14" name="__codelineno-0-14"></a> <span class="k">if</span> <span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">loggers</span><span class="p">:</span> <a id="__codelineno-0-14" name="__codelineno-0-14"></a><span class="sd"> Uses colors, and only prints timestamps when not running inside notebook.</span>
<a id="__codelineno-0-15" name="__codelineno-0-15"></a> <span class="n">logger</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">getLogger</span><span class="p">(</span><span class="n">name</span><span class="p">)</span> <a id="__codelineno-0-15" name="__codelineno-0-15"></a><span class="sd"> &quot;&quot;&quot;</span>
<a id="__codelineno-0-16" name="__codelineno-0-16"></a> <span class="n">logger</span><span class="o">.</span><span class="n">setLevel</span><span class="p">(</span><span class="n">level</span><span class="p">)</span> <a id="__codelineno-0-16" name="__codelineno-0-16"></a>
<a id="__codelineno-0-17" name="__codelineno-0-17"></a> <a id="__codelineno-0-17" name="__codelineno-0-17"></a> <span class="k">if</span> <span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">loggers</span><span class="p">:</span>
<a id="__codelineno-0-18" name="__codelineno-0-18"></a> <span class="n">log_format</span> <span class="o">=</span> <span class="s2">&quot;</span><span class="si">%(asctime)s</span><span class="s2"> | </span><span class="si">%(levelname)8s</span><span class="s2"> | </span><span class="si">%(message)s</span><span class="s2">&quot;</span> <a id="__codelineno-0-18" name="__codelineno-0-18"></a> <span class="n">logger</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">getLogger</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
<a id="__codelineno-0-19" name="__codelineno-0-19"></a> <span class="n">stdout_handler</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">StreamHandler</span><span class="p">()</span> <a id="__codelineno-0-19" name="__codelineno-0-19"></a> <span class="n">logger</span><span class="o">.</span><span class="n">setLevel</span><span class="p">(</span><span class="n">level</span><span class="p">)</span>
<a id="__codelineno-0-20" name="__codelineno-0-20"></a> <span class="n">stdout_handler</span><span class="o">.</span><span class="n">setLevel</span><span class="p">(</span><span class="n">level</span><span class="p">)</span> <a id="__codelineno-0-20" name="__codelineno-0-20"></a>
<a id="__codelineno-0-21" name="__codelineno-0-21"></a> <span class="k">if</span> <span class="ow">not</span> <span class="n">disable_colors</span><span class="p">:</span> <a id="__codelineno-0-21" name="__codelineno-0-21"></a> <span class="k">try</span><span class="p">:</span>
<a id="__codelineno-0-22" name="__codelineno-0-22"></a> <span class="n">stdout_handler</span><span class="o">.</span><span class="n">setFormatter</span><span class="p">(</span><span class="n">CustomFormatter</span><span class="p">(</span><span class="n">log_format</span><span class="p">))</span> <a id="__codelineno-0-22" name="__codelineno-0-22"></a> <span class="n">get_ipython</span><span class="p">()</span> <span class="c1"># type: ignore</span>
<a id="__codelineno-0-23" name="__codelineno-0-23"></a> <a id="__codelineno-0-23" name="__codelineno-0-23"></a> <span class="n">log_format</span> <span class="o">=</span> <span class="s2">&quot;</span><span class="si">%(message)s</span><span class="s2">&quot;</span>
<a id="__codelineno-0-24" name="__codelineno-0-24"></a> <span class="n">logger</span><span class="o">.</span><span class="n">addHandler</span><span class="p">(</span><span class="n">stdout_handler</span><span class="p">)</span> <a id="__codelineno-0-24" name="__codelineno-0-24"></a> <span class="k">except</span> <span class="ne">NameError</span><span class="p">:</span>
<a id="__codelineno-0-25" name="__codelineno-0-25"></a> <span class="n">loggers</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">logger</span> <a id="__codelineno-0-25" name="__codelineno-0-25"></a> <span class="c1"># will fail outside of a notebook https://ipython.org/</span>
<a id="__codelineno-0-26" name="__codelineno-0-26"></a> <a id="__codelineno-0-26" name="__codelineno-0-26"></a> <span class="n">log_format</span> <span class="o">=</span> <span class="s2">&quot;</span><span class="si">%(asctime)s</span><span class="s2"> | </span><span class="si">%(levelname)8s</span><span class="s2"> | </span><span class="si">%(message)s</span><span class="s2">&quot;</span>
<a id="__codelineno-0-27" name="__codelineno-0-27"></a> <span class="k">return</span> <span class="n">loggers</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <a id="__codelineno-0-27" name="__codelineno-0-27"></a>
<a id="__codelineno-0-28" name="__codelineno-0-28"></a> <span class="n">stdout_handler</span> <span class="o">=</span> <span class="n">logging</span><span class="o">.</span><span class="n">StreamHandler</span><span class="p">()</span>
<a id="__codelineno-0-29" name="__codelineno-0-29"></a> <span class="n">stdout_handler</span><span class="o">.</span><span class="n">setLevel</span><span class="p">(</span><span class="n">level</span><span class="p">)</span>
<a id="__codelineno-0-30" name="__codelineno-0-30"></a> <span class="k">if</span> <span class="ow">not</span> <span class="n">disable_colors</span><span class="p">:</span>
<a id="__codelineno-0-31" name="__codelineno-0-31"></a> <span class="n">stdout_handler</span><span class="o">.</span><span class="n">setFormatter</span><span class="p">(</span><span class="n">CustomFormatter</span><span class="p">(</span><span class="n">log_format</span><span class="p">))</span>
<a id="__codelineno-0-32" name="__codelineno-0-32"></a>
<a id="__codelineno-0-33" name="__codelineno-0-33"></a> <span class="n">logger</span><span class="o">.</span><span class="n">addHandler</span><span class="p">(</span><span class="n">stdout_handler</span><span class="p">)</span>
<a id="__codelineno-0-34" name="__codelineno-0-34"></a> <span class="n">loggers</span><span class="p">[</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">logger</span>
<a id="__codelineno-0-35" name="__codelineno-0-35"></a>
<a id="__codelineno-0-36" name="__codelineno-0-36"></a> <span class="k">return</span> <span class="n">loggers</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
</code></pre></div></td></tr></table></div> </code></pre></div></td></tr></table></div>
</details> </details>
</div> </div>

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@ -1806,13 +1806,13 @@ Licensed under the Apache License, Version 2.0.
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<pre>Requirement already satisfied: great-ai in /data/projects/great-ai/.env/lib/python3.10/site-packages (0.1.0)
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Note: you may need to restart the kernel to use updated packages.
</pre>
</div>
</div>
</div>
</div>
</div> </div>
</div> </div>
<div class="jp-Cell jp-MarkdownCell jp-Notebook-cell"> <div class="jp-Cell jp-MarkdownCell jp-Notebook-cell">
@ -1857,7 +1989,7 @@ Licensed under the Apache License, Version 2.0.
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div> </div>
<div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputArea jp-Cell-inputArea">
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[1]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[2]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter"> <div class="CodeMirror cm-s-jupyter">
@ -1921,7 +2053,7 @@ def preprocess(line):
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div> </div>
<div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputArea jp-Cell-inputArea">
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[2]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[3]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter"> <div class="CodeMirror cm-s-jupyter">
@ -1972,7 +2104,7 @@ y_train = [d[1] for d in training_data]</div>
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr"> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
<pre>100%|██████████| 84000/84000 [00:09&lt;00:00, 8705.41it/s] <pre>100%|██████████| 84000/84000 [00:08&lt;00:00, 9771.59it/s]
</pre> </pre>
</div> </div>
</div> </div>
@ -2000,7 +2132,7 @@ y_train = [d[1] for d in training_data]</div>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div> </div>
<div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputArea jp-Cell-inputArea">
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[3]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[4]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter"> <div class="CodeMirror cm-s-jupyter">
@ -2047,7 +2179,7 @@ y_test = [d[1] for d in test_data]</div>
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr"> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
<pre>100%|██████████| 22399/22399 [00:02&lt;00:00, 7963.06it/s] <pre>100%|██████████| 22399/22399 [00:02&lt;00:00, 7858.71it/s]
</pre> </pre>
</div> </div>
</div> </div>
@ -2076,7 +2208,7 @@ y_test = [d[1] for d in test_data]</div>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div> </div>
<div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputArea jp-Cell-inputArea">
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[4]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[5]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter"> <div class="CodeMirror cm-s-jupyter">
@ -2123,7 +2255,7 @@ model.fit(X_train, y_train)</div>
<div class="jp-OutputArea-child"> <div class="jp-OutputArea-child">
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[4]:</div> <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[5]:</div>
@ -2160,7 +2292,7 @@ model.fit(X_train, y_train)</div>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div> </div>
<div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputArea jp-Cell-inputArea">
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[5]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[6]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter"> <div class="CodeMirror cm-s-jupyter">
@ -2212,7 +2344,7 @@ plt.rcParams["font.size"] = 12</div>
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div> </div>
<div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputArea jp-Cell-inputArea">
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[6]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[7]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter"> <div class="CodeMirror cm-s-jupyter">
@ -2326,7 +2458,7 @@ jp-needs-light-background
<div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser">
</div> </div>
<div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputArea jp-Cell-inputArea">
<div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[7]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="jp-InputPrompt jp-InputArea-prompt">In&nbsp;[8]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline">
<div class="CodeMirror cm-s-jupyter"> <div class="CodeMirror cm-s-jupyter">
@ -2369,23 +2501,23 @@ save_model(model, key="my-domain-predictor")</div>
<div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr"> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr">
<pre><span style="color: rgb(255,255,0)">2022-07-09 22:33:18 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️</span> <pre><span style="color: rgb(255,255,0)">Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️</span>
<span style="color: rgb(255,255,0)">2022-07-09 22:33:18 | WARNING | Cannot find credentials files, defaulting to using ParallelTinyDbDriver</span> <span style="color: rgb(255,255,0)">Cannot find credentials files, defaulting to using ParallelTinyDbDriver</span>
<span style="color: rgb(255,255,0)">2022-07-09 22:33:18 | WARNING | The selected tracing database (ParallelTinyDbDriver) is not recommended for production</span> <span style="color: rgb(255,255,0)">The selected tracing database (ParallelTinyDbDriver) is not recommended for production</span>
<span style="color: rgb(255,255,0)">2022-07-09 22:33:18 | WARNING | Cannot find credentials files, defaulting to using LargeFileLocal</span> <span style="color: rgb(255,255,0)">Cannot find credentials files, defaulting to using LargeFileLocal</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | GreatAI (v0.1.0): configured ✅</span> <span style="color: rgb(0,175,255)">GreatAI (v0.1.3): configured ✅</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | 🔩 tracing_database: ParallelTinyDbDriver</span> <span style="color: rgb(0,175,255)"> 🔩 tracing_database: ParallelTinyDbDriver</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | 🔩 large_file_implementation: LargeFileLocal</span> <span style="color: rgb(0,175,255)"> 🔩 large_file_implementation: LargeFileLocal</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | 🔩 is_production: False</span> <span style="color: rgb(0,175,255)"> 🔩 is_production: False</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | 🔩 should_log_exception_stack: True</span> <span style="color: rgb(0,175,255)"> 🔩 should_log_exception_stack: True</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | 🔩 prediction_cache_size: 512</span> <span style="color: rgb(0,175,255)"> 🔩 prediction_cache_size: 512</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | 🔩 dashboard_table_size: 20</span> <span style="color: rgb(0,175,255)"> 🔩 dashboard_table_size: 50</span>
<span style="color: rgb(255,255,0)">2022-07-09 22:33:18 | WARNING | You still need to check whether you follow all best practices before trusting your deployment.</span> <span style="color: rgb(255,255,0)">You still need to check whether you follow all best practices before trusting your deployment.</span>
<span style="color: rgb(255,255,0)">2022-07-09 22:33:18 | WARNING | &gt; Find out more at https://se-ml.github.io/practices</span> <span style="color: rgb(255,255,0)">&gt; Find out more at https://se-ml.github.io/practices</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:18 | INFO | Fetching cached versions of my-domain-predictor</span> <span style="color: rgb(0,175,255)">Fetching cached versions of my-domain-predictor</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:19 | INFO | Copying file for my-domain-predictor-5</span> <span style="color: rgb(0,175,255)">Copying file for my-domain-predictor-6</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:19 | INFO | Compressing my-domain-predictor-5</span> <span style="color: rgb(0,175,255)">Compressing my-domain-predictor-6</span>
<span style="color: rgb(0,175,255)">2022-07-09 22:33:20 | INFO | Model my-domain-predictor uploaded with version 5</span> <span style="color: rgb(0,175,255)">Model my-domain-predictor uploaded with version 6</span>
</pre> </pre>
</div> </div>
</div> </div>
@ -2393,13 +2525,13 @@ save_model(model, key="my-domain-predictor")</div>
<div class="jp-OutputArea-child"> <div class="jp-OutputArea-child">
<div class="jp-OutputPrompt jp-OutputArea-prompt">Out[7]:</div> <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[8]:</div>
<div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain"> <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain">
<pre>&#39;my-domain-predictor:5&#39;</pre> <pre>&#39;my-domain-predictor:6&#39;</pre>
</div> </div>
</div> </div>
@ -2430,7 +2562,7 @@ save_model(model, key="my-domain-predictor")</div>
<small> <small>
Last update: Last update:
<span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 9, 2022</span> <span class="git-revision-date-localized-plugin git-revision-date-localized-plugin-date">July 11, 2022</span>
</small> </small>

179
tutorial/train/train.ipynb
View file

@ -11,9 +11,126 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": null, "execution_count": 1,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
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"Requirement already satisfied: webencodings in /data/projects/great-ai/.env/lib/python3.10/site-packages (from bleach->nbconvert->great-ai) (0.5.1)\n",
"Requirement already satisfied: brotli in /data/projects/great-ai/.env/lib/python3.10/site-packages (from flask-compress->dash>=2.4.0->great-ai) (1.0.9)\n",
"Requirement already satisfied: asttokens in /data/projects/great-ai/.env/lib/python3.10/site-packages (from stack-data->ipython->great-ai) (2.0.5)\n",
"Requirement already satisfied: executing in /data/projects/great-ai/.env/lib/python3.10/site-packages (from stack-data->ipython->great-ai) (0.8.3)\n",
"Requirement already satisfied: pure-eval in /data/projects/great-ai/.env/lib/python3.10/site-packages (from stack-data->ipython->great-ai) (0.2.2)\n",
"Requirement already satisfied: attrs>=17.4.0 in /data/projects/great-ai/.env/lib/python3.10/site-packages (from jsonschema>=2.6->nbformat>=5.1->nbconvert->great-ai) (21.4.0)\n",
"Requirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /data/projects/great-ai/.env/lib/python3.10/site-packages (from jsonschema>=2.6->nbformat>=5.1->nbconvert->great-ai) (0.18.1)\n",
"Requirement already satisfied: pyzmq>=23.0 in /data/projects/great-ai/.env/lib/python3.10/site-packages (from jupyter-client>=6.1.5->nbclient>=0.5.0->nbconvert->great-ai) (23.2.0)\n",
"Requirement already satisfied: tornado>=6.0 in /data/projects/great-ai/.env/lib/python3.10/site-packages (from jupyter-client>=6.1.5->nbclient>=0.5.0->nbconvert->great-ai) (6.2)\n",
"Note: you may need to restart the kernel to use updated packages.\n"
]
}
],
"source": [ "source": [
"%pip install great-ai" "%pip install great-ai"
] ]
@ -30,7 +147,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 2,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -56,14 +173,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 3,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stderr", "name": "stderr",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"100%|██████████| 84000/84000 [00:09<00:00, 8705.41it/s] \n" "100%|██████████| 84000/84000 [00:08<00:00, 9771.59it/s] \n"
] ]
} }
], ],
@ -86,14 +203,14 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 4,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stderr", "name": "stderr",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"100%|██████████| 22399/22399 [00:02<00:00, 7963.06it/s] \n" "100%|██████████| 22399/22399 [00:02<00:00, 7858.71it/s] \n"
] ]
} }
], ],
@ -116,7 +233,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 5,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -131,7 +248,7 @@
" ('linearsvc', LinearSVC())])" " ('linearsvc', LinearSVC())])"
] ]
}, },
"execution_count": 4, "execution_count": 5,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -156,7 +273,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 6,
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
@ -176,7 +293,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 7,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
@ -237,39 +354,39 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 8,
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"name": "stderr", "name": "stderr",
"output_type": "stream", "output_type": "stream",
"text": [ "text": [
"\u001b[38;5;226m2022-07-09 22:33:18 | WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n", "\u001b[38;5;226mEnvironment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n",
"\u001b[38;5;226m2022-07-09 22:33:18 | WARNING | Cannot find credentials files, defaulting to using ParallelTinyDbDriver\u001b[0m\n", "\u001b[38;5;226mCannot find credentials files, defaulting to using ParallelTinyDbDriver\u001b[0m\n",
"\u001b[38;5;226m2022-07-09 22:33:18 | WARNING | The selected tracing database (ParallelTinyDbDriver) is not recommended for production\u001b[0m\n", "\u001b[38;5;226mThe selected tracing database (ParallelTinyDbDriver) is not recommended for production\u001b[0m\n",
"\u001b[38;5;226m2022-07-09 22:33:18 | WARNING | Cannot find credentials files, defaulting to using LargeFileLocal\u001b[0m\n", "\u001b[38;5;226mCannot find credentials files, defaulting to using LargeFileLocal\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | GreatAI (v0.1.0): configured ✅\u001b[0m\n", "\u001b[38;5;39mGreatAI (v0.1.3): configured ✅\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | 🔩 tracing_database: ParallelTinyDbDriver\u001b[0m\n", "\u001b[38;5;39m 🔩 tracing_database: ParallelTinyDbDriver\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | 🔩 large_file_implementation: LargeFileLocal\u001b[0m\n", "\u001b[38;5;39m 🔩 large_file_implementation: LargeFileLocal\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | 🔩 is_production: False\u001b[0m\n", "\u001b[38;5;39m 🔩 is_production: False\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | 🔩 should_log_exception_stack: True\u001b[0m\n", "\u001b[38;5;39m 🔩 should_log_exception_stack: True\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | 🔩 prediction_cache_size: 512\u001b[0m\n", "\u001b[38;5;39m 🔩 prediction_cache_size: 512\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | 🔩 dashboard_table_size: 20\u001b[0m\n", "\u001b[38;5;39m 🔩 dashboard_table_size: 50\u001b[0m\n",
"\u001b[38;5;226m2022-07-09 22:33:18 | WARNING | You still need to check whether you follow all best practices before trusting your deployment.\u001b[0m\n", "\u001b[38;5;226mYou still need to check whether you follow all best practices before trusting your deployment.\u001b[0m\n",
"\u001b[38;5;226m2022-07-09 22:33:18 | WARNING | > Find out more at https://se-ml.github.io/practices\u001b[0m\n", "\u001b[38;5;226m> Find out more at https://se-ml.github.io/practices\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:18 | INFO | Fetching cached versions of my-domain-predictor\u001b[0m\n", "\u001b[38;5;39mFetching cached versions of my-domain-predictor\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:19 | INFO | Copying file for my-domain-predictor-5\u001b[0m\n", "\u001b[38;5;39mCopying file for my-domain-predictor-6\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:19 | INFO | Compressing my-domain-predictor-5\u001b[0m\n", "\u001b[38;5;39mCompressing my-domain-predictor-6\u001b[0m\n",
"\u001b[38;5;39m2022-07-09 22:33:20 | INFO | Model my-domain-predictor uploaded with version 5\u001b[0m\n" "\u001b[38;5;39mModel my-domain-predictor uploaded with version 6\u001b[0m\n"
] ]
}, },
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"'my-domain-predictor:5'" "'my-domain-predictor:6'"
] ]
}, },
"execution_count": 7, "execution_count": 8,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }