com.intel.analytics.bigdl.nn.ops.SquaredDifference.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.ops
import com.intel.analytics.bigdl.tensor.Tensor
import com.intel.analytics.bigdl.tensor.TensorNumericMath._
import com.intel.analytics.bigdl.utils.Table
import scala.reflect.ClassTag
/**
* Returns (x - y)(x - y) element-wise.
*/
class SquaredDifference[T: ClassTag]()(implicit ev: TensorNumeric[T])
extends Operation[Table, Tensor[_], T] {
def updateOutput(inputs: Table): Tensor[_] = {
val x = inputs[Tensor[NumericWildcard]](1)
val y = inputs[Tensor[NumericWildcard]](2)
require(x.getType() == y.getType(), "The numeric type of x and y must be the same, but got" +
s"x: ${x.getType()}, y: ${y.getType()}")
if (output.getType() != x.getType()) {
output = x.emptyInstance()
}
output.asInstanceOf[Tensor[NumericWildcard]]
.resizeAs(x).copy(x).sub(y).square()
output
}
}
object SquaredDifference {
def apply[T: ClassTag]()(implicit ev: TensorNumeric[T]): SquaredDifference[T]
= new SquaredDifference()
}