60 lines
2.5 KiB
Scala
60 lines
2.5 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.SubsamplingLayer
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import org.deeplearning4j.scalnet.layers.convolutional.Convolution
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import org.deeplearning4j.scalnet.layers.core.Layer
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/**
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* 2D average pooling layer in neural net architectures.
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*
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* @author Max Pumperla
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*/
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class AvgPooling2D(kernelSize: List[Int],
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stride: List[Int] = List(1, 1),
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padding: List[Int] = List(0, 0),
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dilation: List[Int] = List(1, 1),
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nIn: Option[List[Int]] = None,
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override val name: String = "")
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extends Convolution(dimension = 2, kernelSize, stride, padding, dilation, 0, nIn, 0)
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with Layer {
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if (kernelSize.length != 2 || stride.length != 2 || padding.length != 2 || dilation.length != 2) {
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throw new IllegalArgumentException("Kernel, stride, padding and dilation lists must all be length 2.")
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}
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override def reshapeInput(nIn: List[Int]): AvgPooling2D =
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new AvgPooling2D(kernelSize, stride, padding, dilation, Some(nIn), name)
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override def compile: org.deeplearning4j.nn.conf.layers.Layer =
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new SubsamplingLayer.Builder(SubsamplingLayer.PoolingType.AVG)
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.kernelSize(kernelSize.head, kernelSize.last)
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.dilation(dilation.head, dilation.last)
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.stride(stride.head, stride.last)
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.name(name)
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.build()
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}
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object AvgPooling2D {
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def apply(kernelSize: List[Int],
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stride: List[Int] = List(1, 1),
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padding: List[Int] = List(0, 0),
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dilation: List[Int] = List(1, 1),
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nIn: Option[List[Int]] = None,
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name: String = null): AvgPooling2D =
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new AvgPooling2D(kernelSize, stride, padding, dilation, nIn, name)
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}
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