Eval And Test_minibatch In Cntk

We are using TrainResNet_CIFAR10.py as an example to learn cntk. We have created two methods, eval_metric and calc_error as below: def eval_metric(trainer, reader_test, test_epoc

Solution 1:

trainer.test_minibatch returns the average value of the loss (or in general the first argument).

There are also these methods that you can use after calling test_minibatch: trainer.previous_minibatch_loss_average, trainer.previous_minibatch_sample_count, and trainer.previous_minibatch_evaluation_average.

The differences are likely coming from pre-processing. Is the mean_value the same as when you trained the network? Is it in RGB order or in BGR order?

Have you considered reducing your evaluation set to a single image and verify that you get exactly the same output with the reader and by manually loading the image?