org.deeplearning4j.scalnet.layers.pooling.GlobalMaxPooling2D.scala Maven / Gradle / Ivy
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A Scala wrapper for Deeplearning4j, inspired by Keras. Scala + DL + Spark + GPUs
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.scalnet.layers.pooling
import org.deeplearning4j.nn.conf.layers.{ GlobalPoolingLayer, PoolingType }
import org.deeplearning4j.scalnet.layers.core.{ Layer, Node }
/**
* 2D global max pooling layer.
*
* @author Max Pumperla
*/
class GlobalMaxPooling2D(nIn: Option[List[Int]] = None, override val name: String = null) extends Node with Layer {
override def inputShape: List[Int] = nIn.getOrElse(List(0))
override def outputShape: List[Int] = {
val nOutChannels: Int =
if (inputShape.nonEmpty) inputShape.last
else 0
if (inputShape.lengthCompare(3) == 0) {
List[Int](inputShape.head, nOutChannels)
} else if (nOutChannels > 0) List(nOutChannels)
else List()
}
override def reshapeInput(nIn: List[Int]): GlobalMaxPooling2D =
new GlobalMaxPooling2D(Some(nIn), name)
override def compile: org.deeplearning4j.nn.conf.layers.Layer =
new GlobalPoolingLayer.Builder()
.poolingType(PoolingType.MAX)
.name(name)
.build()
}
object GlobalMaxPooling2D {
def apply(nIn: Option[List[Int]] = None, name: String = null): GlobalMaxPooling2D =
new GlobalMaxPooling2D(nIn, name)
}