wassname/pytorch-lightning
1
0
Fork 0
mirror of https://github.com/wassname/pytorch-lightning.git synced 2026-09-09 11:32:07 +08:00
Code Issues Packages Projects Releases Wiki Activity

Deployed f0af138 with MkDocs version: 1.0.4

Browse Source
This commit is contained in:
William Falcon
2019-08-13 15:21:24 -05:00
parent d32c548cf8
commit 9b8a06bfdb
15 changed files with 1240 additions and 598 deletions
Download Patch File Download Diff File Expand all files Collapse all files
Trainer/Validation loop/index.html
+40 -21
View File
@@ -595,46 +595,65 @@ Lightning will run 5 steps of validation in the beginning of training as a sanit
<hr />
<h4 id="check-validation-every-n-epochs">Check validation every n epochs</h4>
<p>If you have a small dataset you might want to check validation every n epochs</p>
<pre><code class="python"># DEFAULT
trainer = Trainer(check_val_every_n_epoch=1)
</code></pre>
<table class="codehilitetable"><tr><td class="linenos"><div class="linenodiv"><pre>1
2</pre></div></td><td class="code"><div class="codehilite"><pre><span></span><span class="c1"># DEFAULT</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">check_val_every_n_epoch</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
</pre></div>
</td></tr></table>
<hr />
<h4 id="set-how-much-of-the-validation-set-to-check">Set how much of the validation set to check</h4>
<p>If you don't want to check 100% of the validation set (for debugging or if it's huge), set this flag</p>
<pre><code class="python"># DEFAULT
trainer = Trainer(val_percent_check=1.0)
<table class="codehilitetable"><tr><td class="linenos"><div class="linenodiv"><pre>1
2
3
4
5</pre></div></td><td class="code"><div class="codehilite"><pre><span></span><span class="c1"># DEFAULT</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">val_percent_check</span><span class="o">=</span><span class="mf">1.0</span><span class="p">)</span>
# check 10% only
trainer = Trainer(val_percent_check=0.1)
</code></pre>
<span class="c1"># check 10% only</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">val_percent_check</span><span class="o">=</span><span class="mf">0.1</span><span class="p">)</span>
</pre></div>
</td></tr></table>
<hr />
<h4 id="set-how-much-of-the-test-set-to-check">Set how much of the test set to check</h4>
<p>If you don't want to check 100% of the test set (for debugging or if it's huge), set this flag</p>
<pre><code class="python"># DEFAULT
trainer = Trainer(test_percent_check=1.0)
<table class="codehilitetable"><tr><td class="linenos"><div class="linenodiv"><pre>1
2
3
4
5</pre></div></td><td class="code"><div class="codehilite"><pre><span></span><span class="c1"># DEFAULT</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">test_percent_check</span><span class="o">=</span><span class="mf">1.0</span><span class="p">)</span>
# check 10% only
trainer = Trainer(test_percent_check=0.1)
</code></pre>
<span class="c1"># check 10% only</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">test_percent_check</span><span class="o">=</span><span class="mf">0.1</span><span class="p">)</span>
</pre></div>
</td></tr></table>
<hr />
<h4 id="set-validation-check-frequency-within-1-training-epoch">Set validation check frequency within 1 training epoch</h4>
<p>For large datasets it's often desirable to check validation multiple times within a training loop</p>
<pre><code class="python"># DEFAULT
trainer = Trainer(val_check_interval=0.95)
<table class="codehilitetable"><tr><td class="linenos"><div class="linenodiv"><pre>1
2
3
4
5</pre></div></td><td class="code"><div class="codehilite"><pre><span></span><span class="c1"># DEFAULT</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">val_check_interval</span><span class="o">=</span><span class="mf">0.95</span><span class="p">)</span>
# check every .25 of an epoch
trainer = Trainer(val_check_interval=0.25)
</code></pre>
<span class="c1"># check every .25 of an epoch </span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">val_check_interval</span><span class="o">=</span><span class="mf">0.25</span><span class="p">)</span>
</pre></div>
</td></tr></table>
<hr />
<h4 id="set-the-number-of-validation-sanity-steps">Set the number of validation sanity steps</h4>
<p>Lightning runs a few steps of validation in the beginning of training. This avoids crashing in the validation loop sometime deep into a lengthy training loop.</p>
<pre><code class="python"># DEFAULT
trainer = Trainer(nb_sanity_val_steps=5)
</code></pre>
<table class="codehilitetable"><tr><td class="linenos"><div class="linenodiv"><pre>1
2</pre></div></td><td class="code"><div class="codehilite"><pre><span></span><span class="c1"># DEFAULT</span>
<span class="n">trainer</span> <span class="o">=</span> <span class="n">Trainer</span><span class="p">(</span><span class="n">nb_sanity_val_steps</span><span class="o">=</span><span class="mi">5</span><span class="p">)</span>
</pre></div>
</td></tr></table>