LambdaCallback

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form.onsubmit = function(e) { e.preventDefault(); var query = document.getElementById('search-input').value; window.location.href = '/search.html?query=' + query; return False } </script> </div> <div class='k-main-inner' id='k-main-id'> <div class='k-location-slug'> <span class="k-location-slug-pointer">►</span> <a href='/api/'>Keras 3 API documentation</a> / <a href='/api/callbacks/'>Callbacks API</a> / LambdaCallback </div> <div class='k-content'> <h1 id="lambdacallback">LambdaCallback</h1> <p><span style="float:right;"><a href="https://github.com/keras-team/keras/tree/v3.7.0/keras/src/callbacks/lambda_callback.py#L5">[source]</a></span></p> <h3 id="lambdacallback-class"><code>LambdaCallback</code> class</h3> <div class="codehilite"><pre><span></span><code><span class="n">keras</span><span class="o">.</span><span class="n">callbacks</span><span class="o">.</span><span class="n">LambdaCallback</span><span class="p">(</span> <span class="n">on_epoch_begin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">on_epoch_end</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">on_train_begin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">on_train_end</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">on_train_batch_begin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">on_train_batch_end</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span> <span class="p">)</span> </code></pre></div> <p>Callback for creating simple, custom callbacks on-the-fly.</p> <div class="codehilite"><pre><span></span><code>This callback is constructed with anonymous functions that will be called at the appropriate time (during `Model.{fit | evaluate | predict}`). Note that the callbacks expects positional arguments, as: - `on_epoch_begin` and `on_epoch_end` expect two positional arguments: `epoch`, `logs` - `on_train_begin` and `on_train_end` expect one positional argument: `logs` - `on_train_batch_begin` and `on_train_batch_end` expect two positional arguments: `batch`, `logs` - See `Callback` class definition for the full list of functions and their expected arguments. # Arguments on_epoch_begin: called at the beginning of every epoch. on_epoch_end: called at the end of every epoch. on_train_begin: called at the beginning of model training. on_train_end: called at the end of model training. on_train_batch_begin: called at the beginning of every train batch. on_train_batch_end: called at the end of every train batch. kwargs: Any function in `Callback` that you want to override by passing `function_name=function`. For example, `LambdaCallback(.., on_train_end=train_end_fn)`. The custom function needs to have same arguments as the ones defined in `Callback`. # Example ```python # Print the batch number at the beginning of every batch. batch_print_callback = LambdaCallback( on_train_batch_begin=lambda batch,logs: print(batch)) # Stream the epoch loss to a file in JSON format. The file content # is not well-formed JSON but rather has a JSON object per line. import json json_log = open('loss_log.json', mode='wt', buffering=1) json_logging_callback = LambdaCallback( on_epoch_end=lambda epoch, logs: json_log.write( json.dumps({'epoch': epoch, 'loss': logs['loss']}) + ' </code></pre></div> <p>'), on_train_end=lambda logs: json_log.close() )</p> <div class="codehilite"><pre><span></span><code># Terminate some processes after having finished model training. processes = ... cleanup_callback = LambdaCallback( on_train_end=lambda logs: [ p.terminate() for p in processes if p.is_alive()]) model.fit(..., callbacks=[batch_print_callback, json_logging_callback, cleanup_callback]) ``` </code></pre></div> <hr /> </div> <div class='k-outline'> <div class='k-outline-depth-1'> <a href='#lambdacallback'>LambdaCallback</a> </div> <div class='k-outline-depth-3'> <a href='#lambdacallback-class'><code>LambdaCallback</code> class</a> </div> </div> </div> </div> </div> </body> <footer style="float: left; width: 100%; padding: 1em; border-top: solid 1px #bbb;"> <a href="https://policies.google.com/terms">Terms</a> | <a href="https://policies.google.com/privacy">Privacy</a> </footer> </html>

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LambdaCallback