com.intel.analytics.bigdl.nn.Input.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.Graph.ModuleNode
import com.intel.analytics.bigdl.nn.abstractnn.{AbstractModule, Activity, TensorModule}
import com.intel.analytics.bigdl.tensor.Tensor
import com.intel.analytics.bigdl.tensor.TensorNumericMath.TensorNumeric
import com.intel.analytics.bigdl.utils.Node
import scala.reflect.ClassTag
/**
* Input layer do nothing to the input tensors, just pass them. It should be used as input node
* when the first layer of your module accepts multiple tensors as inputs.
*
* Each input node of the graph container should accept one tensor as input. If you want a module
* accepting multiple tensors as input, you should add some Input module before it and connect
* the outputs of the Input nodes to it.
*
* Please note that the return is not a layer but a Node containing input layer.
*
* @tparam T The numeric type in the criterion, usually which are [[Float]] or [[Double]]
*/
@SerialVersionUID(- 8525406230282608924L)
class Input[T: ClassTag]()(implicit ev: TensorNumeric[T])
extends AbstractModule[Activity, Activity, T] {
override def updateOutput(input: Activity): Activity = {
output = input
output
}
override def updateGradInput(input: Activity, gradOutput: Activity): Activity = {
gradInput = gradOutput
gradInput
}
override def equals(other: Any): Boolean = {
if (!other.isInstanceOf[Input[_]]) return false
this.eq(other.asInstanceOf[Input[_]])
}
override def hashCode(): Int = System.identityHashCode(this)
}
object Input {
def apply[T: ClassTag](name : String = null)(implicit ev: TensorNumeric[T]): ModuleNode[T] = {
val module = new Input()
if (name != null) {
module.setName(name)
}
new Node(module.asInstanceOf[AbstractModule[Activity, Activity, T]])
}
}