54 lines
1.9 KiB
Scala
54 lines
1.9 KiB
Scala
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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package org.deeplearning4j.scalnet.layers.pooling
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import org.deeplearning4j.nn.conf.layers.{ GlobalPoolingLayer, PoolingType }
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import org.deeplearning4j.scalnet.layers.core.{ Layer, Node }
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/**
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* 3D global avg pooling layer.
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*
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* @author Max Pumperla
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*/
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class GlobalAvgPooling3D(nIn: Option[List[Int]] = None, override val name: String = null) extends Node with Layer {
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override def inputShape: List[Int] = nIn.getOrElse(List(0))
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override def outputShape: List[Int] = {
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val nOutChannels: Int =
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if (inputShape.nonEmpty) inputShape.last
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else 0
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if (inputShape.lengthCompare(4) == 0) {
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List[Int](inputShape.head, nOutChannels)
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} else if (nOutChannels > 0) List(nOutChannels)
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else List()
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}
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override def reshapeInput(nIn: List[Int]): GlobalAvgPooling3D =
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new GlobalAvgPooling3D(Some(nIn), name)
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override def compile: org.deeplearning4j.nn.conf.layers.Layer =
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new GlobalPoolingLayer.Builder()
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.poolingType(PoolingType.AVG)
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.name(name)
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.build()
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}
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object GlobalAvgPooling3D {
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def apply(nIn: Option[List[Int]] = None, name: String = null): GlobalAvgPooling3D =
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new GlobalAvgPooling3D(nIn, name)
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}
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