Multiple inputs (working just for tensorflow), big data files (needs further attention)

parent a8964f0c
......@@ -239,15 +239,16 @@ public class EMADLGenerator {
String b = backend.getBackendString(backend);
String trainingDataHash = "";
String testDataHash = "";
if(b.equals("CAFFE2")){ //TODO: TensorFlow (really? we can use .h5 files for tensorflow, a seperate library is used anyway, see the example code)
if(b.equals("CAFFE2")){
trainingDataHash = getChecksumForFile(architecture.get().getDataPath() + "/train_lmdb/data.mdb");
testDataHash = getChecksumForFile(architecture.get().getDataPath() + "/test_lmdb/data.mdb");
}else{
trainingDataHash = getChecksumForFile(architecture.get().getDataPath() + "/train.h5");
testDataHash = getChecksumForFile(architecture.get().getDataPath() + "/test.h5");
//What should we do here? For big files infeasible. Maybe hash of metainformation (last changed etc.)?
//trainingDataHash = getChecksumForFile(architecture.get().getDataPath() + "/train.h5");
//testDataHash = getChecksumForFile(architecture.get().getDataPath() + "/test.h5");
}
String trainingHash = emadlHash + "#" + cnntHash + "#" + trainingDataHash + "#" + testDataHash;
String trainingHash = emadlHash + "#" + cnntHash; //+ "#" + trainingDataHash + "#" + testDataHash;
boolean alreadyTrained = newHashes.contains(trainingHash) || isAlreadyTrained(trainingHash, componentInstance);
if(alreadyTrained && !forced.equals("y")) {
......
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