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/*
* 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.nn.abstractnn.{AbstractModule, DataFormat}
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
/**
* Cropping layer for 2D input (e.g. picture).
* The input of this layer should be 4D.
*
* When you use this layer as the first layer of a model, you need to provide the argument
* inputShape (a Single Shape, does not include the batch dimension).
*
* @param heightCrop Int array of length 2. Height of the 2 cropping dimension. Default is (0, 0).
* @param widthCrop Int array of length 2. Width of the 2 cropping dimension. Default is (0, 0).
* @param dimOrdering Format of input data. Either DataFormat.NCHW (dimOrdering='th') or
* DataFormat.NHWC (dimOrdering='tf'). Default is NCHW.
* @tparam T Numeric type of parameter(e.g. weight, bias). Only support float/double now.
*/
class Cropping2D[T: ClassTag](
val heightCrop: Array[Int] = Array(0, 0),
val widthCrop: Array[Int] = Array(0, 0),
val dimOrdering: DataFormat = DataFormat.NCHW,
val inputShape: Shape = null)(implicit ev: TensorNumeric[T])
extends KerasLayer[Tensor[T], Tensor[T], T](KerasLayer.addBatch(inputShape)) {
require(heightCrop.length == 2,
s"Cropping3D: height cropping values should be of length 2, but got ${heightCrop.length}")
require(widthCrop.length == 2,
s"Cropping3D: width cropping values should be of length 2, but got ${widthCrop.length}")
override def doBuild(inputShape: Shape): AbstractModule[Tensor[T], Tensor[T], T] = {
val layer = com.intel.analytics.bigdl.nn.Cropping2D(
heightCrop = heightCrop,
widthCrop = widthCrop,
format = dimOrdering)
layer.asInstanceOf[AbstractModule[Tensor[T], Tensor[T], T]]
}
}
object Cropping2D {
def apply[@specialized(Float, Double) T: ClassTag](
cropping: ((Int, Int), (Int, Int)) = ((0, 0), (0, 0)),
dimOrdering: String = "th",
inputShape: Shape = null)(implicit ev: TensorNumeric[T]): Cropping2D[T] = {
val heightCrop = Array(cropping._1._1, cropping._1._2)
val widthCrop = Array(cropping._2._1, cropping._2._2)
new Cropping2D[T](heightCrop, widthCrop,
KerasUtils.toBigDLFormat(dimOrdering), inputShape)
}
}
