com.intel.analytics.bigdl.nn.Index.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
import com.intel.analytics.bigdl.nn.abstractnn.AbstractModule
import com.intel.analytics.bigdl.tensor.Tensor
import com.intel.analytics.bigdl.tensor.TensorNumericMath.TensorNumeric
import com.intel.analytics.bigdl.utils.Table
import scala.reflect.ClassTag
/**
* Applies the Tensor index operation along the given dimension.
*
* @param dimension
*/
@SerialVersionUID(2608373524149209793L)
class Index[T: ClassTag](dimension: Int)(implicit ev: TensorNumeric[T])
extends AbstractModule[Table, Tensor[T], T]{
override def updateOutput(input: Table): Tensor[T] = {
val t = input[Tensor[T]](1)
val index = input[Tensor[T]](2)
output.index(dimension, index, t)
output
}
override def updateGradInput(input: Table, gradOutput: Tensor[T]): Table = {
val t = input[Tensor[T]](1)
val index = input[Tensor[T]](2)
if (!gradInput.contains(1)) gradInput.insert(1, Tensor[T])
if (!gradInput.contains(2)) gradInput.insert(2, Tensor[T])
gradInput[Tensor[T]](2).resizeAs(index).zero()
gradInput[Tensor[T]](1).resizeAs(t).zero()
gradInput[Tensor[T]](1).indexAdd(dimension, index, gradOutput)
gradInput
}
override def canEqual(other: Any): Boolean = other.isInstanceOf[Index[T]]
override def equals(other: Any): Boolean = other match {
case that: Index[T] =>
super.equals(that) &&
(that canEqual this)
case _ => false
}
override def hashCode(): Int = {
def getHashCode(a: Any): Int = if (a == null) 0 else a.hashCode()
val state = Seq(super.hashCode())
state.map(getHashCode).foldLeft(0)((a, b) => 31 * a + b)
}
override def toString(): String = {
s"${getPrintName}($dimension)"
}
}
object Index {
def apply[@specialized(Float, Double) T: ClassTag](
dimension: Int)(implicit ev: TensorNumeric[T]) : Index[T] = {
new Index[T](dimension)
}
}