Comments (1)
May I ask to elaborate the question?
Based on the issue title, I shall mention that DEHB doesn't require or depend on torch
to run. The function being optimized may require torch and that then depends on the user. For example, the MNIST example you'll find for DEHB uses torch and the version used to test that example is given here .
If the above clarifies your concern, please feel free to close the issue. :)
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Related Issues (20)
- Improve doc strings and add type annotations HOT 2
- Handling min_budget = max_budget situation HOT 4
- Continuously develop unit tests
- Keep active brackets in a dictionary HOT 1
- Implement ask-and-tell interface for DEHB HOT 1
- Use of deprecated np.int in dimension type checking HOT 3
- [Bug] `isinstance(self, Client)` will never be `True` HOT 6
- Configuration and budgets in each brackets HOT 6
- Using Dask ```Client``` as context manager
- No support for Constant type in vector_to_configspace() and configspace_to_vector() HOT 3
- Update CHANGELOG with the historic releases
- Updating and populating the documentation
- Implement versioning for documentation HOT 1
- Introduce IDs for evaluated configurations HOT 2
- Continuing configuration evolution when run budget is exhausted. HOT 2
- Implement parallel DE
- [Bug] Seeding is not applied to configspace HOT 3
- Is there any way to hide non-critical logs to stdout? HOT 8
- ERROR - Failed to communicate with scheduler during heartbeat. followed by TimeoutError: No valid workers found HOT 2
- Test backward compatibility with NumPy2.0 HOT 3
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