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79 lines
2.7 KiB
Markdown
79 lines
2.7 KiB
Markdown
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---
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title: Keras Tuner Integration
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---
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Integrate **ClearML** into code that uses [Keras Tuner](https://www.tensorflow.org/tutorials/keras/keras_tuner). By
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specifying `ClearMLTunerLogger` (see [kerastuner.py](https://github.com/allegroai/clearml/blob/master/clearml/external/kerastuner.py))
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as the Keras Tuner logger, **ClearML** automatically logs scalars and hyperparameter optimization.
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## ClearMLTunerLogger
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Take a look at [keras_tuner_cifar.py](https://github.com/allegroai/clearml/blob/master/examples/frameworks/kerastuner/keras_tuner_cifar.py)
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example script, which demonstrates the integration of **ClearML** in a code that uses Keras Tuner.
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The script does the following:
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1. Creates a `Hyperband` object, which uses Keras Tuner's `Hyperband` tuner. It finds the best hyperparameters to train a
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network on a CIFAR10 dataset.
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1. When the `Hyperband` object is created, instantiates a `ClearMLTunerLogger` object and assigns it to the `Hyperband` logger.
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The `ClearMLTunerLogger` class provides the required binding for **ClearML** automatic logging.
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```python
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tuner = kt.Hyperband(
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build_model,
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project_name='kt examples',
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logger=ClearMLTunerLogger(),
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objective='val_accuracy',
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max_epochs=10,
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hyperband_iterations=6)
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```
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When the script runs, it logs:
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* Tabular summary of hyperparameters tested and their metrics by trial ID
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* Scalar plot showing metrics for all runs
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* Summary plot
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* Output model with configuration and snapshot location.
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## Scalars
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**ClearML** logs the scalars from training each network. They appear in the project's page in the **ClearML web UI**, under
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**RESULTS** **>** **SCALARS**.
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
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## Summary of hyperparameter optimization
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**ClearML** automatically logs the parameters of each experiment run in the hyperparameter search. They appear in tabular
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form in **RESULTS** **>** **PLOTS**.
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
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## Artifacts
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**ClearML** automatically stores the output model. It appears in **ARTIFACTS** **>** **Output Model**.
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
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Model details, such as snap locations, appear in the **MODELS** tab.
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
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The model configuration is stored with the model.
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
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## Configuration objects
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### Hyperparameters
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**ClearML** automatically logs the TensorFlow Definitions, which appear in **RESULTS** **>** **CONFIGURATION** **>** **HYPER PARAMETERS**.
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
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### Configuration
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The Task configuration appears in **RESULTS** **>** **CONFIGURATION** **>** **General**.
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
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