@Override
public void map(GLMModel m) {
_res = (GLMModel) m.clone();
_res._output = (GLMOutput) _res._output.clone();
Submodel sm =
Double.isNaN(_lambda)
? _res._output._submodels[_res._output._best_lambda_idx]
: _res._output.submodelForLambda(_lambda);
assert sm != null : "GLM[" + m._key + "]: missing submodel for lambda " + _lambda;
sm = (Submodel) sm.clone();
_res._output._submodels = new Submodel[] {sm};
_res._output.setSubmodelIdx(0);
}
public static void setSubmodel(
H2O.H2OCountedCompleter cmp,
Key modelKey,
final double lambda,
double[] beta,
double[] norm_beta,
final int iteration,
long runtime,
boolean sparseCoef,
final GLMValidation val) {
final Submodel sm = new Submodel(lambda, beta, norm_beta, runtime, iteration, sparseCoef);
sm.validation = val;
cmp.addToPendingCount(1);
new TAtomic<GLMModel>(cmp) {
@Override
public GLMModel atomic(GLMModel old) {
if (old == null) return old; // job could've been cancelled!
if (old._output._submodels == null) {
old._output._submodels = new Submodel[] {sm};
} else {
int id = old._output.submodelIdForLambda(lambda);
if (id < 0) {
id = -id - 1;
old._output._submodels =
Arrays.copyOf(old._output._submodels, old._output._submodels.length + 1);
for (int i = old._output._submodels.length - 1; i > id; --i)
old._output._submodels[i] = old._output._submodels[i - 1];
} else if (old._output._submodels[id].iteration > sm.iteration) return old;
else old._output._submodels = old._output._submodels.clone();
old._output._submodels[id] = sm;
old._run_time = Math.max(old._run_time, sm.run_time);
}
old._output.pickBestModel(false);
return old;
}
}.fork(modelKey);
}