ai.djl.training.initializer.NormalInitializer Maven / Gradle / Ivy
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/*
* Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance
* with the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0/
*
* or in the "license" file accompanying this file. This file 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 ai.djl.training.initializer;
import ai.djl.ndarray.NDArray;
import ai.djl.ndarray.NDManager;
import ai.djl.ndarray.types.DataType;
import ai.djl.ndarray.types.Shape;
/**
* {@code NormalInitializer} initializes weights with random values sampled from a normal
* distribution with a mean of zero and standard deviation of {@code sigma}. Default standard
* deviation is 0.01.
*/
public class NormalInitializer implements Initializer {
private float sigma;
/** Creates an instance of {@code NormalInitializer} with a default sigma of 0.01. */
public NormalInitializer() {
this.sigma = 0.01f;
}
/**
* Creates a Normal initializer.
*
* @param sigma the standard deviation of the normal distribution
*/
public NormalInitializer(float sigma) {
this.sigma = sigma;
}
/** {@inheritDoc} */
@Override
public NDArray initialize(NDManager manager, Shape shape, DataType dataType) {
return manager.randomNormal(0.0f, sigma, shape, dataType, manager.getDevice());
}
}