Github user myui commented on a diff in the pull request:
https://github.com/apache/incubator-hivemall/pull/116#discussion_r140725317
--- Diff: core/src/main/java/hivemall/embedding/AbstractWord2VecModel.java
---
@@ -0,0 +1,117 @@
+/*
+ * 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 hivemall.embedding;
+
+import hivemall.math.random.PRNG;
+import hivemall.math.random.RandomNumberGeneratorFactory;
+import hivemall.utils.collections.maps.Int2FloatOpenHashTable;
+
+import javax.annotation.Nonnegative;
+import javax.annotation.Nonnull;
+
+public abstract class AbstractWord2VecModel {
+ // cached sigmoid function parameters
+ protected final int MAX_SIGMOID = 6;
+ protected final int SIGMOID_TABLE_SIZE = 1000;
+ protected float[] sigmoidTable;
+
+ // learning rate parameters
+ @Nonnegative
+ protected float lr;
+ @Nonnegative
+ private float startingLR;
+ @Nonnegative
+ private long numTrainWords;
+ @Nonnegative
+ protected long wordCount;
+ @Nonnegative
+ private long lastWordCount;
+ @Nonnegative
+ private long wordCountActual;
+
+ @Nonnegative
+ protected int dim;
+ private PRNG _rnd;
+
+ protected Int2FloatOpenHashTable contextWeights;
+ protected Int2FloatOpenHashTable inputWeights;
+
+ protected AbstractWord2VecModel(final int dim, final float startingLR,
final long numTrainWords) {
+ this.dim = dim;
+ this.startingLR = this.lr = startingLR;
+ this.numTrainWords = numTrainWords;
+
+ this.wordCount = 0L;
+ this.lastWordCount = 0L;
+ this.wordCountActual = 0L;
+ this._rnd = RandomNumberGeneratorFactory.createPRNG(1001);
+
+ this.sigmoidTable = initSigmoidTable(MAX_SIGMOID,
SIGMOID_TABLE_SIZE);
+
+ // TODO how to estimate size
+ this.inputWeights = new Int2FloatOpenHashTable(10578 * dim);
+ this.inputWeights.defaultReturnValue(-0.f);
+ this.contextWeights = new Int2FloatOpenHashTable(10578 * dim);
+ this.contextWeights.defaultReturnValue(0.f);
+ }
+
+ private static float[] initSigmoidTable(final int maxSigmoid, final
int sigmoidTableSize) {
+ float[] sigmoidTable = new float[sigmoidTableSize];
+ for (int i = 0; i < sigmoidTableSize; i++) {
+ float x = ((float) i / sigmoidTableSize * 2 - 1) * (float)
maxSigmoid;
+ sigmoidTable[i] = 1.f / ((float) Math.exp(-x) + 1.f);
+ }
+ return sigmoidTable;
+ }
+
+ protected void initWordWeights(final int wordId) {
+ for (int i = 0; i < dim; i++) {
+ inputWeights.put(wordId * dim + i, ((float) _rnd.nextDouble()
- 0.5f) / dim);
+ }
+ }
+
+ protected static float sigmoid(final float v, final int MAX_SIGMOID,
--- End diff --
No need to use Constants for argument: `final int MAX_SIGMOID, final int
SIGMOID_TABLE_SIZE`
---
