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fix issues #48 and #49 #52
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jakubczakon
reviewed
May 16, 2018
steps/pytorch/callbacks.py
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| @@ -52,6 +53,13 @@ def on_batch_begin(self, *args, **kwargs): | |||
| def on_batch_end(self, *args, **kwargs): | |||
| self.batch_id += 1 | |||
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| def get_validation_loss(self): | |||
| if self.epoch_id not in self.validation_loss.keys(): | |||
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@apyskir there is a really cool method for dicts called .get(key, fallback_value). for instance here it would be self.validation_loss.get(self.epoch_id, score_model(self.model, self.function, self.validation_dataget)
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@jakubczakon Yes, but this method does not update the dictionary. But if the key is not in dict.keys() we want to perform dict[key]=score_model...
I think .setdefault() is the answer
This was referenced May 17, 2018
kamil-kaczmarek
pushed a commit
that referenced
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May 23, 2018
* initial * cleaned up * updates keras models and callbacks * added explanation notebook * renamed notebook * ran notebook * transformer loading now to be clicked * dropped nlp * fixed typos * updated whats missing * updated with dsb and talking data * added simple pipeline notebook * imports optimized * feature_names=None and categorical_features=None * refactor the way the model parameters are passed * moved adapters to seperate file, renamed identity/take_first adapters * Update misc.py * fit_transform -> transform * Update base.py * fixed #10 * fixed typo * * added: get_upsample_pad, get_downsample_pad * added: multiclass_segmentation_loss * *warning added * Add some user interface messages * Notebook#3: Adapter for ensembling * Add example: 1-getting-started.ipynb * Remove custom adapter; other minor changes after reviewer feedback * Add example 2-multi-step.ipynb and some minor changes to example 1-getting-started.ipynb * Cleanup of examples 1 and 2 * Fix a mistake in notebook text * Add steps/__pycache__ to .gitignore * Further changes based on Github feedback * add self.conv_stride parameter in unet definition * Change steps/__pycache__ to *.pyc in .gitignore * Changes in Notebook#3 following code review * train forests on train data and ensembler on ensembling data * decoupled sklearn preprocessing from text preprocessing with heavy de… (#32) * decoupled sklearn preprocessing from text preprocessing with heavy dependencies * fixed import error * dropped anonymization from text.py, reformatted imports, small refactors * small refactor for readability * Change time format (#40) * Dev docstrings (#33) * Step halfway done * Step init args done * Steps docstrings done * added docstrings to Step properties * Step docstring done * dropped mock transformer addeed docstrings to Base and Dummy Transformers * base documentation finished, minor refactors * docstrings added to adapters * docstrings added * started refactoring lgbm * Update base.py * updated docstrings * base transformer docstring fix * fixed logging docstrings * Notebook #5: Example with Keras (#41) * Notebook #5: Example with Keras * Corrected notebook for Keras and necessary refactors in ClassifierGenerator * Fix issue #28: Unintuitive adapter syntax (#42) * Write tests for new adapter syntax * Refactor adapter * Improve handling of caches and logs in tests * Fix minor issues mentioned in PR comments * Rewrite tests in pytest framework * Move adapting to seperate class, alter behaviour * Correction: mutable object as default argument in Step initializer * Issue #16: make_transformer (#50) * Corrections and tests for Sklearn wrappers * make_transformer taking arbitrary functions * fix issues #48 and #49 (#52) * fix issues #48 and #49 * use of setdefault method * fix according to Kamil's request * Fix post merge issues * Prepare package (#58) * Remove tutorial notebooks * Remove modules with heavy dependencies * Rename steps -> steppy * Add setup.py * Tell git to ignore egg files * Read the docs might output of sphinx-quickstart * Requirements file * Try adding sphinx-apidoc output * Add some requirements * Add IPython to requirements * removed intro.ipynb and updated requirements.txt * corrected setup.py * refactored NoOperation to IdentityOperation, optimized inputs * moved misc.py to steppy-toolkit * simplified ProbabilityCalibation, BaseTransformer small refactor * prepare setup.py and setup.cfg for PyPI registration * added install requires to setup.py * name refactor * Create README.md
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