@Override
protected void checkMemoryFootPrint() {
if (_model._output._ntrees == 0) return;
int trees_so_far = _model._output._ntrees; // existing trees
long model_mem_size =
new ComputeModelSize(trees_so_far, _model._output._treeKeys).doAllNodes()._model_mem_size;
_model._output._treeStats._byte_size = model_mem_size;
double avg_tree_mem_size = (double) model_mem_size / trees_so_far;
Log.debug(
"Average tree size (for all classes): " + PrettyPrint.bytes((long) avg_tree_mem_size));
// all the compressed trees are stored on the driver node
long max_mem = H2O.SELF.get_max_mem();
if (_parms._ntrees * avg_tree_mem_size > max_mem) {
String msg =
"The tree model will not fit in the driver node's memory ("
+ PrettyPrint.bytes((long) avg_tree_mem_size)
+ " per tree x "
+ _parms._ntrees
+ " > "
+ PrettyPrint.bytes(max_mem)
+ ") - try decreasing ntrees and/or max_depth or increasing min_rows!";
error("_ntrees", msg);
cancel(msg);
}
}
/**
* Simple GLM wrapper to enable launching GLM from command line.
*
* <p>Example input: java -jar target/h2o.jar -name=test -runMethod water.util.GLMRunner
* -file=smalldata/logreg/prostate.csv -y=CAPSULE -family=binomial
*
* @param args
* @throws InterruptedException
*/
public static void main(String[] args) throws InterruptedException {
try {
GLMArgs ARGS = new GLMArgs();
new Arguments(args).extract(ARGS);
System.out.println("==================<GLMRunner START>===================");
ValueArray ary = Utils.loadAndParseKey(ARGS.file);
int ycol;
try {
ycol = Integer.parseInt(ARGS.y);
} catch (NumberFormatException e) {
ycol = ary.getColumnIds(new String[] {ARGS.y})[0];
}
int ncols = ary.numCols();
if (ycol < 0 || ycol >= ary.numCols()) {
System.err.println("invalid y column: " + ycol);
H2O.exit(-1);
}
int[] xcols;
if (ARGS.xs.equalsIgnoreCase("all")) {
xcols = new int[ncols - 1];
for (int i = 0; i < ycol; ++i) xcols[i] = i;
for (int i = ycol; i < ncols - 1; ++i) xcols[i] = i + 1;
} else {
System.out.println("xs = " + ARGS.xs);
String[] names = ARGS.xs.split(",");
xcols = new int[names.length];
try {
for (int i = 0; i < names.length; ++i) xcols[i] = Integer.valueOf(names[i]);
} catch (NumberFormatException e) {
xcols = ary.getColumnIds(ARGS.xs.split(","));
}
}
for (int x : xcols)
if (x < 0) {
System.err.println("Invalid predictor specification " + ARGS.xs);
H2O.exit(-1);
}
GLMJob j =
DGLM.startGLMJob(
DGLM.getData(ary, xcols, ycol, null, true),
new ADMMSolver(ARGS.lambda, ARGS._alpha),
new GLMParams(Family.valueOf(ARGS.family)),
null,
ARGS.xval,
true);
System.out.print("[GLM] computing model...");
int progress = 0;
while (!j.isDone()) {
int p = (int) (100 * j.progress());
int dots = p - progress;
progress = p;
for (int i = 0; i < dots; ++i) System.out.print('.');
Thread.sleep(250);
}
Log.debug(Sys.GENLM, "DONE.");
GLMModel m = j.get();
String[] colnames = ary.colNames();
System.out.println("Intercept" + " = " + m._beta[ncols - 1]);
for (int i = 0; i < xcols.length; ++i) {
System.out.println(colnames[i] + " = " + m._beta[i]);
}
} catch (Throwable t) {
Log.err(t);
} finally { // we're done. shutdown the cloud
Log.debug(Sys.GENLM, "==================<GLMRunner DONE>===================");
UDPRebooted.suicide(UDPRebooted.T.shutdown, H2O.SELF);
}
}