Keras Fit Shuffle

If i test the same model on examples c b a it should obtain the same accuracy.

Keras fit shuffle. In other words shuffling the examples shouldn t change my. The method getitem should return a complete batch. Consider this piece of code. The training data the remainder can optionally be shuffled at every epoch shuffle argument in fit.

Keras utils sequence is a utility that you can subclass to obtain a python generator with two important properties. Batch is a special option for dealing with the limitations of hdf5 data. But when using fit you don t get the option to shuffle or not shuffle the validation set independent of the training set. Import numpy as np np random seed 1337 for reproducibility from keras models import sequential.

When passing shuffle true in fit. Be sure that model fit shuffle false. It can be shuffled e g. If i test my model on examples a b c it will obtain a certain accuracy.

Lm fit train data train labels epochs 2 validation data val data val labels shuffle true when using fit generator with batches each individual batch can be created with shuffle true or false separately. You should the set numpy seed before importing keras. So no the validation data is not necessarily taken from every class and it is just the last 10 assuming that you ask for 10 of the data. Train 1 npy train 2 npy and then i create a dataset as shown in the middle of the code then i apply it to model fit function.

Has no effect when steps per epoch is not null. That doesn t affect the validation data obviously it has to be the same set from epoch to epoch. So my question is when. It works well with multiprocessing.

Just adding shuffle true in the argument for model fit function doesn t do anything it seems. It shuffles in batch sized chunks.