Add ModelError as else case to lr_normalizer() #292
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Pull Request Test Coverage Report for Build 471
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Nice, thanks :) Later this week there will be the final changes to v.0.6.2 and given this is already passing, I don't see why it would not pass then. Will merge at that point. thanks again! |
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* Fix the required parameters discrepancy * Fix hidden_layers complexity * Make @pep8speaks stop crying * Handles PRs #292 and #379 - Implements a custom error if a non-supported optimizer is used with with lr_normalizer #292 - Fixed docs typo #379 * Updated PR template
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* Fix the required parameters discrepancy * Fix hidden_layers complexity * Make @pep8speaks stop crying * fixed a tiny typo The docs for `Analyze` said `plot_bars` for `plot_kde` as well. * Handles PRs #292 and #379 - Implements a custom error if a non-supported optimizer is used with with lr_normalizer #292 - Fixed docs typo #379 * Updated PR template * enabled resample_params in AutoParams It's now possible to set the number of `resample_params` in AutoParams. Also fixed typical example docs. * updated docs and PULL_REQUEST_TEMPLATE * change version to docs
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Thanks for this :) The issue has been handled now in other commits, so closing here. |
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After adding Talos to my Tensorflow+Keras model, I found that the learning rate normalizer only recognizes objects from 'keras.optimizers' and was failing silently. Rather than making structural/dependency changes to accommodate Tensorflow, I figured it should at least have an 'else' case with an error to indicate the function cannot operate on the provided optimizer.
Also added test function to make sure this error gets triggered with a string.
My first PR, so let me know if this is prepared incorrectly.