avplatonov commented on a change in pull request #5767: [ML] IGNITE-10573: 
Consistent API for Ensemble training
URL: https://github.com/apache/ignite/pull/5767#discussion_r247812259
 
 

 ##########
 File path: 
modules/ml/src/main/java/org/apache/ignite/ml/composition/CompositionUtils.java
 ##########
 @@ -0,0 +1,69 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *      http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.ignite.ml.composition;
+
+import org.apache.ignite.ml.IgniteModel;
+import org.apache.ignite.ml.dataset.DatasetBuilder;
+import org.apache.ignite.ml.math.functions.IgniteBiFunction;
+import org.apache.ignite.ml.math.primitives.vector.Vector;
+import org.apache.ignite.ml.trainers.DatasetTrainer;
+
+/**
+ * Various utility functions for trainers composition.
+ */
+public class CompositionUtils {
+    /**
+     * Perform blurring of model type of given trainer to {@code 
IgniteModel<I, O>}, where I, O are input and output
+     * types of original model.
+     *
+     * @param trainer Trainer to coerce.
+     * @param <I> Type of input of model produced by coerced trainer.
+     * @param <O> Type of output of model produced by coerced trainer.
+     * @param <M> Type of model produced by coerced trainer.
+     * @param <L> Type of labels.
+     * @return Trainer coerced to {@code DatasetTrainer<IgniteModel<I, O>, L>}.
+     */
+    public static <I, O, M extends IgniteModel<I, O>, L> 
DatasetTrainer<IgniteModel<I, O>, L> unsafeCoerce(
+        DatasetTrainer<? extends M, L> trainer) {
+        return new DatasetTrainer<IgniteModel<I, O>, L>() {
+            /** {@inheritDoc} */
+            @Override public <K, V> IgniteModel<I, O> fit(DatasetBuilder<K, V> 
datasetBuilder,
+                IgniteBiFunction<K, V, Vector> featureExtractor, 
IgniteBiFunction<K, V, L> lbExtractor) {
+                return trainer.fit(datasetBuilder, featureExtractor, 
lbExtractor);
+            }
+
+            /** {@inheritDoc} */
+            @Override public <K, V> IgniteModel<I, O> update(IgniteModel<I, O> 
mdl, DatasetBuilder<K, V> datasetBuilder,
+                IgniteBiFunction<K, V, Vector> featureExtractor, 
IgniteBiFunction<K, V, L> lbExtractor) {
+                DatasetTrainer<IgniteModel<I, O>, L> trainer1 = 
(DatasetTrainer<IgniteModel<I, O>, L>)trainer;
+                return trainer1.update(mdl, datasetBuilder, featureExtractor, 
lbExtractor);
+            }
+
+            /** {@inheritDoc} */
+            @Override protected boolean checkState(IgniteModel<I, O> mdl) {
+                return true;
 
 Review comment:
   Let's change protected "checkState" name to public "isUpdateable" and check 
model here

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