Why is accuracy from fit_generator different to that from evaluate_generator in Keras?

Question

What I do:

• I am training a pre-trained CNN with Keras fit_generator(). This produces evaluation metrics (loss, acc, val_los

Answer 1

Set use_multiprocessing=False at fit_generator level fixes the problem BUT at the cost of slowing down training significantly. A better but still imperfect workround would be to set use_multiprocessing=False for only the validation generator as the code below modified from keras' fit_generator function.

...
        try:
            if do_validation:
                if val_gen and workers > 0:
                    # Create an Enqueuer that can be reused
                    val_data = validation_data
                    if isinstance(val_data, Sequence):
                        val_enqueuer = OrderedEnqueuer(val_data,
                                                       **use_multiprocessing=False**)
                        validation_steps = len(val_data)
                    else:
                        val_enqueuer = GeneratorEnqueuer(val_data,
                                                         **use_multiprocessing=False**)
                    val_enqueuer.start(workers=workers,
                                       max_queue_size=max_queue_size)
                    val_enqueuer_gen = val_enqueuer.get()
...