org.deeplearning4j.scalnet.layers.pooling.MaxPooling2D.scala Maven / Gradle / Ivy

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/*
 *
 *  * Copyright 2016 Skymind,Inc.
 *  *
 *  *    Licensed 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.deeplearning4j.scalnet.layers.pooling

import org.deeplearning4j.nn.conf.layers.SubsamplingLayer
import org.deeplearning4j.scalnet.layers.Layer
import org.deeplearning4j.scalnet.layers.convolutional.Convolution


/**
  * 2D max pooling in neural net architectures.
  *
  * @author David Kale
  */
class MaxPooling2D(
    kernelSize: List[Int],
    stride: List[Int] = List(1, 1),
    padding: List[Int] = List(0, 0),
    override val name: String = null)
  extends Convolution(kernelSize, stride, padding)
    with Layer {
  if (kernelSize.length != 2 || stride.length != 2 || padding.length != 2)
    throw new IllegalArgumentException("Kernel, stride, padding lists must all be length 2.")

  override def compile: org.deeplearning4j.nn.conf.layers.Layer =
    new SubsamplingLayer.Builder(SubsamplingLayer.PoolingType.MAX)
      .kernelSize(kernelSize.head, kernelSize.last)
      .stride(stride.head, stride.last)
      .name(name)
      .build()
  }