49 lines
1.7 KiB
Scala
49 lines
1.7 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.noise
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import org.deeplearning4j.nn.conf.dropout.{ AlphaDropout => JAlphaDropout }
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import org.deeplearning4j.nn.conf.layers.DropoutLayer
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import org.deeplearning4j.scalnet.layers.core.Layer
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/**
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* AlphaDropout layer
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*
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* @author Max Pumperla
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*/
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class AlphaDropout(nOut: List[Int], nIn: List[Int], rate: Double, override val name: String) extends Layer {
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override def compile: org.deeplearning4j.nn.conf.layers.Layer =
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new DropoutLayer.Builder()
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.dropOut(new JAlphaDropout(rate))
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.nIn(inputShape.last)
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.nOut(outputShape.last)
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.name(name)
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.build()
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override val outputShape: List[Int] = nOut
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override val inputShape: List[Int] = nIn
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override def reshapeInput(newIn: List[Int]): AlphaDropout =
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new AlphaDropout(nOut, newIn, rate, name)
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}
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object AlphaDropout {
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def apply(nOut: Int, nIn: Int = 0, rate: Double, name: String = ""): AlphaDropout =
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new AlphaDropout(List(nOut), List(nIn), rate, name)
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}
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