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Skip certain parameter combinations in the parameter space #528
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Just to be safe... You can achieve it with Also, you can within the input model itself handle any logics you like. Talos will compute everything that is in the input model, regardless if it relates with tf/keras or not. This gives you unrestricted power to add any logic to the input model. I do appreciate that there is a benefit in following a pattern by a library that benefits many in the Talos community. Thank you for suggesting it 👍 |
Hi. Thanks for your answer. First, I have to thank you for this tool. It is very useful to me. Before I post my suggestion, I considered the following approaches:
Kind regards and happy new year |
1) I think Talos should add a method for skip impossible combinations of parameters
If for example, I want to test a CNN with MLP networks, some parameters, such as the kernel_size does not exists in certain combinations. Moreover, if I limit the time or the number of combinations I do not want to waste some impossible combinations.
2) Once implemented, I can see how this feature will
Although there are methods for skip this manually, I think it should be nice to use parameter space in the same way that ParametersGrid from scikit-learn does.
For example:
3) I believe this feature is
4) Given the chance, I'd be happy to make a PR for this feature
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