org.deeplearning4j.scalnet.layers.reshaping.Reshape.scala Maven / Gradle / Ivy

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/*
 *
 *  * Copyright 2016 Skymind,Inc.
 *  *
 *  *    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 org.deeplearning4j.scalnet.layers.reshaping

import org.deeplearning4j.nn.conf.InputPreProcessor
import org.deeplearning4j.nn.conf.preprocessor.ReshapePreProcessor
import org.deeplearning4j.scalnet.layers.Node
import org.deeplearning4j.scalnet.layers.Preprocessor


/**
  * Generic reshaping layer.
  *
  * @author David Kale
  */
class Reshape(
    newOutputShape: List[Int],
    oldInputShape: List[Int] = List())
  extends Node with Preprocessor {
  inputShape = oldInputShape
  _outputShape = newOutputShape

  override def compile: InputPreProcessor = {
    if (inputShape.isEmpty || (inputShape.length == 1 && inputShape.head == 0))
      throw new IllegalArgumentException("Input shape must be nonempty and nonzero.")
    if (inputShape.product != outputShape.product)
      throw new IllegalArgumentException("Overall input shape must equal overall output shape.")
    new ReshapePreProcessor(inputShape.toArray, outputShape.toArray)
  }
}