I have a big dataset (around 20GB for training and 2GB for testing) and I want to use MXnet and R. Due to lack of memory, I search for an iterator to load the training and test set by a custom iterator and I found this solution.
Now, I can train the model using the code on this page, but the problem is that if I read the test set with the save iterator as follow:
test.iter <- CustomCSVIter$new(iter = NULL, data.csv = "test.csv", data.shape = 480, batch.size = batch.size)
Then, the prediction command does not work and there is no prediction template in the page;
preds <- predict(model, test.iter)
So, my specific problem is, if I build my model using the code on the page, how can I read my test set and predict its labels for the evaluation process? My test set and train set is in this format.
Thank you for your help