2019-06-06 15:21:15 +03:00

45 lines
1.6 KiB
Scala

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