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In PyTorch we split the validation set from the training set randomly. It has the size of the test set. The validation performance is used by the tuner and analyzer to obtain the best instance. This split should be implemented in the TensorFlow data sets as well. We have already prepared the test problem and the runner implementations for this change. The only change that needs to be done to the runner is marked in the code with a ToDo flag.
The text was updated successfully, but these errors were encountered:
In PyTorch we split the validation set from the training set randomly. It has the size of the test set. The validation performance is used by the tuner and analyzer to obtain the best instance. This split should be implemented in the TensorFlow data sets as well. We have already prepared the test problem and the runner implementations for this change. The only change that needs to be done to the runner is marked in the code with a ToDo flag.
The text was updated successfully, but these errors were encountered: