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KrissiHub committed Oct 21, 2024
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2 changes: 1 addition & 1 deletion docs/converters/bohb.rst
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Expand Up @@ -7,7 +7,7 @@ To load an BOHB run into DeepCAVE, it is necessary to install HpBandSter, e.g. v
pip install deepcave[bohb]
To be able to load it correctly into DeepCAVE, you need save the configuration space as a ConfigSpace JSON file:
To be able to load it correctly into DeepCAVE, you need to save the configuration space as a ConfigSpace JSON file:

.. code-block:: python
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2 changes: 1 addition & 1 deletion docs/converters/custom_converters.rst
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Expand Up @@ -71,7 +71,7 @@ Step 3: Implement the methods
Inside this method, you have to provide a configspace, objectives, and meta data, as well as the
trials, which have to be added to the newly created run object.

4. **is_valid_run**: This method sould return True, if the given path belongs to a valid run. Valid means, that the given run
4. **is_valid_run**: This method should return True if the given path belongs to a valid run. Valid means that the given run
directory contains all files that are necessary for further processing (e.g. a configspace.json).

Step 5: Document your converter
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2 changes: 1 addition & 1 deletion docs/converters/smac.rst
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Expand Up @@ -7,7 +7,7 @@ runs created with the newer SMAC version >= 2.0.0.
As Auto-Sklearn and Auto-PyTorch rely on SMAC for hyperparameter optimization, the SMAC
converter also allows to load runs created with these tools.

To be able to load it correctly into DeepCAVE, you need save the configuration space as a ConfigSpace JSON file,
To be able to load it correctly into DeepCAVE, you need to save the configuration space as a ConfigSpace JSON file,
as well as the run history:

.. code-block:: python
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