com.intel.analytics.bigdl.nn.keras.Pooling1D.scala Maven / Gradle / Ivy
/*
* Copyright 2016 The BigDL Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://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.
*/
package com.intel.analytics.bigdl.nn.keras
import com.intel.analytics.bigdl.tensor.Tensor
import com.intel.analytics.bigdl.tensor.TensorNumericMath.TensorNumeric
import com.intel.analytics.bigdl.utils.Shape
import scala.reflect.ClassTag
/**
* Abstract class for different pooling 1D layers.
* Do not create a new instance of it or use it in a model.
* Please use its child classes, 'AveragePooling1D' and 'MaxPooling1D' instead.
*/
abstract class Pooling1D[T: ClassTag](
val poolLength: Int = 2,
val stride: Int = -1,
val borderMode: String = "valid",
val inputShape: Shape = null)(implicit ev: TensorNumeric[T])
extends KerasLayer[Tensor[T], Tensor[T], T](KerasLayer.addBatch(inputShape)) {
// -1 means stride by default to be poolLength
require(stride == -1 || stride > 0, s"Invalid stride value for Pooling1D: $stride")
val strideValue: Int = if (stride > 0) stride else poolLength
override def computeOutputShape(inputShape: Shape): Shape = {
val input = inputShape.toSingle().toArray
require(input.length == 3,
s"Pooling1D requires 3D input, but got input dim ${input.length}")
val outputLength = KerasUtils.computeConvOutputLength(input(1), poolLength,
borderMode, strideValue)
Shape(input(0), outputLength, input(2))
}
}