#396 Trainer constructor cleanup

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  <h1>Source code for super_gradients.training.utils.early_stopping</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">super_gradients.training.utils.callbacks</span> <span class="kn">import</span> <span class="n">PhaseCallback</span><span class="p">,</span> <span class="n">Phase</span><span class="p">,</span> <span class="n">PhaseContext</span>
<span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">Optional</span>
<span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">super_gradients.common.abstractions.abstract_logger</span> <span class="kn">import</span> <span class="n">get_logger</span>
<span class="n">logger</span> <span class="o">=</span> <span class="n">get_logger</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
<div class="viewcode-block" id="EarlyStop"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.early_stopping.EarlyStop">[docs]</a><span class="k">class</span> <span class="nc">EarlyStop</span><span class="p">(</span><span class="n">PhaseCallback</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Callback to monitor a metric and stop training when it stops improving.</span>
<span class="sd">    Inspired by pytorch_lightning.callbacks.early_stopping and tf.keras.callbacks.EarlyStopping</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">mode_dict</span> <span class="o">=</span> <span class="p">{</span><span class="s2">&quot;min&quot;</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">lt</span><span class="p">,</span> <span class="s2">&quot;max&quot;</span><span class="p">:</span> <span class="n">torch</span><span class="o">.</span><span class="n">gt</span><span class="p">}</span>
    <span class="n">supported_phases</span> <span class="o">=</span> <span class="p">(</span><span class="n">Phase</span><span class="o">.</span><span class="n">VALIDATION_EPOCH_END</span><span class="p">,</span> <span class="n">Phase</span><span class="o">.</span><span class="n">TRAIN_EPOCH_END</span><span class="p">)</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">phase</span><span class="p">:</span> <span class="n">Phase</span><span class="p">,</span>
                 <span class="n">monitor</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span>
                 <span class="n">mode</span><span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="s2">&quot;min&quot;</span><span class="p">,</span>
                 <span class="n">min_delta</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span><span class="p">,</span>
                 <span class="n">patience</span><span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">3</span><span class="p">,</span>
                 <span class="n">check_finite</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
                 <span class="n">threshold</span><span class="p">:</span> <span class="n">Optional</span><span class="p">[</span><span class="nb">float</span><span class="p">]</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span>
                 <span class="n">verbose</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span><span class="p">,</span>
                 <span class="n">strict</span><span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span>
                 <span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        :param phase: Callback phase event.</span>
<span class="sd">        :param monitor: name of the metric to be monitored.</span>
<span class="sd">        :param mode: one of &#39;min&#39;, &#39;max&#39;. In &#39;min&#39; mode, training will stop when the quantity</span>
<span class="sd">           monitored has stopped decreasing and in &#39;max&#39; mode it will stop when the quantity</span>
<span class="sd">           monitored has stopped increasing.</span>
<span class="sd">        :param min_delta: minimum change in the monitored quantity to qualify as an improvement, i.e. an absolute</span>
<span class="sd">           change of less than `min_delta`, will count as no improvement.</span>
<span class="sd">        :param patience: number of checks with no improvement after which training will be stopped.</span>
<span class="sd">            One check happens after every phase event.</span>
<span class="sd">        :param check_finite: When set ``True``, stops training when the monitor becomes NaN or infinite.</span>
<span class="sd">        :param threshold: Stop training immediately once the monitored quantity reaches this threshold. For mode &#39;min&#39;</span>
<span class="sd">            stops training when below threshold, For mode &#39;max&#39; stops training when above threshold.</span>
<span class="sd">        :param verbose: If `True` print logs.</span>
<span class="sd">        :param strict: whether to crash the training if `monitor` is not found in the metrics.</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">EarlyStop</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">phase</span><span class="p">)</span>
        <span class="k">if</span> <span class="n">phase</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">supported_phases</span><span class="p">:</span>
            <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;EarlyStop doesn&#39;t support phase: </span><span class="si">{</span><span class="n">phase</span><span class="si">}</span><span class="s2">, &quot;</span>
                             <span class="sa">f</span><span class="s2">&quot;excepted </span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="nb">str</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">supported_phases</span><span class="p">])</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">phase</span> <span class="o">=</span> <span class="n">phase</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span> <span class="o">=</span> <span class="n">monitor</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">min_delta</span> <span class="o">=</span> <span class="n">min_delta</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">patience</span> <span class="o">=</span> <span class="n">patience</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">mode</span> <span class="o">=</span> <span class="n">mode</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">check_finite</span> <span class="o">=</span> <span class="n">check_finite</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">threshold</span> <span class="o">=</span> <span class="n">threshold</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">verbose</span> <span class="o">=</span> <span class="n">verbose</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">strict</span> <span class="o">=</span> <span class="n">strict</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">wait_count</span> <span class="o">=</span> <span class="mi">0</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode_dict</span><span class="p">:</span>
            <span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;`mode` can be </span><span class="si">{</span><span class="s1">&#39;, &#39;</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mode_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="si">}</span><span class="s2">, got </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="si">}</span><span class="s2">&quot;</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">monitor_op</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">mode_dict</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">mode</span><span class="p">]</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">min_delta</span> <span class="o">*=</span> <span class="mi">1</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">monitor_op</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">gt</span> <span class="k">else</span> <span class="o">-</span><span class="mi">1</span>
        <span class="n">torch_inf</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">Inf</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">best_score</span> <span class="o">=</span> <span class="n">torch_inf</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">monitor_op</span> <span class="o">==</span> <span class="n">torch</span><span class="o">.</span><span class="n">lt</span> <span class="k">else</span> <span class="o">-</span><span class="n">torch_inf</span>
    <span class="k">def</span> <span class="nf">_get_metric_value</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">metrics_dict</span><span class="p">):</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">metrics_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
            <span class="n">msg</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Can&#39;t find EarlyStop monitor </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span><span class="si">}</span><span class="s2"> in metrics_dict: </span><span class="si">{</span><span class="n">metrics_dict</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span><span class="si">}</span><span class="s2">&quot;</span>
            <span class="n">exception_cls</span> <span class="o">=</span> <span class="ne">RuntimeError</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">strict</span> <span class="k">else</span> <span class="n">MissingMonitorKeyException</span>
            <span class="k">raise</span> <span class="n">exception_cls</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">metrics_dict</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span><span class="p">]</span>
    <span class="k">def</span> <span class="nf">_check_for_early_stop</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">current</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">should_stop</span> <span class="o">=</span> <span class="kc">False</span>
        <span class="c1"># check if current value is Nan or inf</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">check_finite</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">torch</span><span class="o">.</span><span class="n">isfinite</span><span class="p">(</span><span class="n">current</span><span class="p">):</span>
            <span class="n">should_stop</span> <span class="o">=</span> <span class="kc">True</span>
            <span class="n">reason</span> <span class="o">=</span> <span class="p">(</span>
                <span class="sa">f</span><span class="s2">&quot;Monitored metric </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span><span class="si">}</span><span class="s2"> = </span><span class="si">{</span><span class="n">current</span><span class="si">}</span><span class="s2"> is not finite.&quot;</span>
                <span class="sa">f</span><span class="s2">&quot; Previous best value was </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">best_score</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">. Signaling Trainer to stop.&quot;</span>
            <span class="p">)</span>
        <span class="c1"># check if current value reached threshold value</span>
        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">threshold</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">monitor_op</span><span class="p">(</span><span class="n">current</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">threshold</span><span class="p">):</span>
            <span class="n">should_stop</span> <span class="o">=</span> <span class="kc">True</span>
            <span class="n">reason</span> <span class="o">=</span> <span class="p">(</span>
                <span class="s2">&quot;Stopping threshold reached:&quot;</span>
                <span class="sa">f</span><span class="s2">&quot; </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span><span class="si">}</span><span class="s2"> = </span><span class="si">{</span><span class="n">current</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_op</span><span class="si">}</span><span class="s2"> </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">threshold</span><span class="si">}</span><span class="s2">.&quot;</span>
                <span class="s2">&quot; Signaling Trainer to stop.&quot;</span>
            <span class="p">)</span>
        <span class="c1"># check if current is an improvement of monitor_key metric.</span>
        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">monitor_op</span><span class="p">(</span><span class="n">current</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">min_delta</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">best_score</span><span class="o">.</span><span class="n">to</span><span class="p">(</span><span class="n">current</span><span class="o">.</span><span class="n">device</span><span class="p">)):</span>
            <span class="n">should_stop</span> <span class="o">=</span> <span class="kc">False</span>
            <span class="k">if</span> <span class="n">torch</span><span class="o">.</span><span class="n">isfinite</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">best_score</span><span class="p">):</span>
                <span class="n">reason</span> <span class="o">=</span> <span class="p">(</span>
                    <span class="sa">f</span><span class="s2">&quot;Metric </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span><span class="si">}</span><span class="s2"> improved by </span><span class="si">{</span><span class="nb">abs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">best_score</span> <span class="o">-</span> <span class="n">current</span><span class="p">)</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2"> &gt;=&quot;</span>
                    <span class="sa">f</span><span class="s2">&quot; min_delta = </span><span class="si">{</span><span class="nb">abs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min_delta</span><span class="p">)</span><span class="si">}</span><span class="s2">. New best score: </span><span class="si">{</span><span class="n">current</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span>
                <span class="p">)</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="n">reason</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Metric </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span><span class="si">}</span><span class="s2"> improved. New best score: </span><span class="si">{</span><span class="n">current</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">&quot;</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">best_score</span> <span class="o">=</span> <span class="n">current</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">wait_count</span> <span class="o">=</span> <span class="mi">0</span>
        <span class="c1"># no improvement in monitor_key metric, check if wait_count is bigger than patience.</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">wait_count</span> <span class="o">+=</span> <span class="mi">1</span>
            <span class="n">reason</span> <span class="o">=</span> <span class="sa">f</span><span class="s2">&quot;Monitored metric </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">monitor_key</span><span class="si">}</span><span class="s2"> did not improve in the last </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">wait_count</span><span class="si">}</span><span class="s2"> records.&quot;</span>
            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">wait_count</span> <span class="o">&gt;=</span> <span class="bp">self</span><span class="o">.</span><span class="n">patience</span><span class="p">:</span>
                <span class="n">should_stop</span> <span class="o">=</span> <span class="kc">True</span>
                <span class="n">reason</span> <span class="o">+=</span> <span class="sa">f</span><span class="s2">&quot; Best score: </span><span class="si">{</span><span class="bp">self</span><span class="o">.</span><span class="n">best_score</span><span class="si">:</span><span class="s2">.3f</span><span class="si">}</span><span class="s2">. Signaling Trainer to stop.&quot;</span>
        <span class="k">return</span> <span class="n">reason</span><span class="p">,</span> <span class="n">should_stop</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">context</span><span class="p">:</span> <span class="n">PhaseContext</span><span class="p">):</span>
        <span class="k">try</span><span class="p">:</span>
            <span class="n">current</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_get_metric_value</span><span class="p">(</span><span class="n">context</span><span class="o">.</span><span class="n">metrics_dict</span><span class="p">)</span>
        <span class="k">except</span> <span class="n">MissingMonitorKeyException</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">warning</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
            <span class="k">return</span>
        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">current</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">current</span> <span class="o">=</span> <span class="n">torch</span><span class="o">.</span><span class="n">tensor</span><span class="p">(</span><span class="n">current</span><span class="p">)</span>
        <span class="n">reason</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">should_stop</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_check_for_early_stop</span><span class="p">(</span><span class="n">current</span><span class="p">)</span>
        <span class="c1"># log reason message, and signal early stop if should_stop=True.</span>
        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">should_stop</span><span class="p">:</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">_signal_early_stop</span><span class="p">(</span><span class="n">context</span><span class="p">,</span> <span class="n">reason</span><span class="p">)</span>
        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">verbose</span><span class="p">:</span>
            <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="n">reason</span><span class="p">)</span>
    <span class="k">def</span> <span class="nf">_signal_early_stop</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">context</span><span class="p">:</span> <span class="n">PhaseContext</span><span class="p">,</span> <span class="n">reason</span><span class="p">:</span> <span class="nb">str</span><span class="p">):</span>
        <span class="n">logger</span><span class="o">.</span><span class="n">info</span><span class="p">(</span><span class="n">reason</span><span class="p">)</span>
        <span class="n">context</span><span class="o">.</span><span class="n">update_context</span><span class="p">(</span><span class="n">stop_training</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
<div class="viewcode-block" id="MissingMonitorKeyException"><a class="viewcode-back" href="../../../../super_gradients.training.utils.html#super_gradients.training.utils.early_stopping.MissingMonitorKeyException">[docs]</a><span class="k">class</span> <span class="nc">MissingMonitorKeyException</span><span class="p">(</span><span class="ne">Exception</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Exception raised for missing monitor key in metrics_dict.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">pass</span></div>
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Deci-AI / super-gradients connected to https://github.com/Deci-AI/super-gradients.git

#396 Trainer constructor cleanup

Deci-AI
/
super-gradients
connected to https://github.com/Deci-AI/super-gradients.git
