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Update webapp images (#200)

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2022-03-13 15:07:06 +02:00
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docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt.md
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@@ -3,7 +3,7 @@ title: Hyperparameter Optimization
---
The [hyper_parameter_optimizer.py](https://github.com/allegroai/clearml/blob/master/examples/optimization/hyper-parameter-optimization/hyper_parameter_optimizer.py)
example script demonstrates hyperparameter optimization, which is automated by using **ClearML**
example script demonstrates hyperparameter optimization, which is automated by using ClearML
## Set the Search Strategy for Optimization
@@ -18,13 +18,13 @@ The following search strategies can be used:
BOHB performs robust and efficient hyperparameter optimization at scale by combining the speed of Hyperband searches
with the guidance and guarantees of convergence of Bayesian Optimization.
**ClearML** implements BOHB for automation with HpBandSter's [bohb.py](https://github.com/automl/HpBandSter/blob/master/hpbandster/optimizers/bohb.py).
ClearML implements BOHB for automation with HpBandSter's [bohb.py](https://github.com/automl/HpBandSter/blob/master/hpbandster/optimizers/bohb.py).
For more information about HpBandSter BOHB, see the [HpBandSter](https://automl.github.io/HpBandSter/build/html/index.html)
documentation.
* Random uniform sampling of hyperparameter strategy - [automation.RandomSearch](../../../references/sdk/hpo_optimization_randomsearch.md)
* Full grid sampling strategy of every hyperparameter combination - Grid search [automation.GridSearch](../../../references/sdk/hpo_optimization_gridsearch.md).
* Custom - Use a custom class and inherit from the **ClearML** automation base strategy class, automation.optimization.SearchStrategy.
* Custom - Use a custom class and inherit from the ClearML automation base strategy class, automation.optimization.SearchStrategy.
The search strategy class that is chosen will be passed to the [automation.HyperParameterOptimizer](../../../references/sdk/hpo_optimization_hyperparameteroptimizer.md)
object later.
@@ -122,7 +122,7 @@ an_optimizer = HyperParameterOptimizer(
base_task_id=args['template_task_id'],
```
Set the hyperparameter ranges to sample, instantiating them as **ClearML** automation objects using [automation.UniformIntegerParameterRange](../../../references/sdk/hpo_parameters_uniformintegerparameterrange.md)
Set the hyperparameter ranges to sample, instantiating them as ClearML automation objects using [automation.UniformIntegerParameterRange](../../../references/sdk/hpo_parameters_uniformintegerparameterrange.md)
and [automation.DiscreteParameterRange](../../../references/sdk/hpo_parameters_discreteparameterrange.md).
```python