wrapper.fit(trainIter); time = System.currentTimeMillis() - time; log.info("*** Completed epoch {}, time: {} ***", i, time);
pw.fit(train); train.reset();
wrapper.fit(trainIter); trainIter.reset(); log.info("Epoch #" + epoch +" complete");
wrapper.fit(mnistTrain); long time2 = System.currentTimeMillis(); log.info("*** Completed epoch {}, time: {} ***", i, (time2 - time1));
wrapper.fit(mnistTrain); long time2 = System.currentTimeMillis(); log.info("*** Completed epoch {}, time: {} ***", i, (time2 - time1));
wrapper.fit(mnistTrain); long time2 = System.currentTimeMillis(); log.info("*** Completed epoch {}, time: {} ***", i, (time2 - time1));
wrapper.fit(iter);
for (int i = 0; i < nTrainEpochs; i++) { DataSetIterator trainData = getDataSetIterator(dataDirectory, 0, testStartIdx - 1, miniBatchSize); wrapper.fit(trainData);
@Override public int train(ComputationGraph graph, MultiDataSetIterator iterator, ProgressLogger pg) { score = 0; n = 0; wrapper.fit(iterator); if (logSpeed) { pg.update(numExamplesPerIterator); } return numExamplesPerIterator; }