com.intel.analytics.bigdl.nn.Echo.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.TensorModule
import com.intel.analytics.bigdl.tensor.Tensor
import com.intel.analytics.bigdl.tensor.TensorNumericMath.TensorNumeric
import scala.reflect.ClassTag
/**
* This module is for debug purpose, which can print activation and gradient in your model
* topology
*/
@SerialVersionUID(6735245897546687343L)
class Echo[T: ClassTag] (implicit ev: TensorNumeric[T])
extends TensorModule[T] {
override def updateOutput(input: Tensor[T]): Tensor[T] = {
this.output = input
println(s"${getPrintName} : Activation size is ${input.size().mkString("x")}")
this.output
}
override def updateGradInput(input: Tensor[T], gradOutput: Tensor[T]): Tensor[T] = {
this.gradInput = gradOutput
println(s"${getPrintName} : Gradient size is ${gradOutput.size().mkString("x")}")
this.gradInput
}
}
object Echo {
def apply[@specialized(Float, Double) T: ClassTag]()
(implicit ev: TensorNumeric[T]) : Echo[T] = {
new Echo[T]()
}
}