45 lines
1.6 KiB
Scala
45 lines
1.6 KiB
Scala
/*******************************************************************************
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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.scalatest.FunSpec
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/**
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* Created by maxpumperla on 19/07/17.
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*/
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class AvgPooling2DTest extends FunSpec {
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describe("A 2D averaging pooling layer with kernel size (5,5)") {
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val kernelSize = List(5, 5)
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val avgPool = AvgPooling2D(kernelSize)
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it("should have inputShape List(0)") {
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assert(avgPool.inputShape == List(0))
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}
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it("should have empty outputShape") {
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assert(avgPool.outputShape == List())
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}
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it("should accept a new input shape when provided") {
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val reshapedPool = avgPool.reshapeInput(List(1, 2, 3))
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assert(reshapedPool.inputShape == List(1, 2, 3))
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}
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it("should become a DL4J pooling layer when compiled") {
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val compiledPool = avgPool.compile
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assert(compiledPool.isInstanceOf[SubsamplingLayer])
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}
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}
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}
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