com.intel.analytics.bigdl.utils.tf.loaders.Dilation2D.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.utils.tf.loaders
import java.nio.ByteOrder
import com.intel.analytics.bigdl.Module
import com.intel.analytics.bigdl.nn.ops.{Dilation2D => Dilation2DOps}
import com.intel.analytics.bigdl.tensor.TensorNumericMath.TensorNumeric
import com.intel.analytics.bigdl.utils.tf.Context
import org.tensorflow.framework.{DataType, NodeDef}
import scala.reflect.ClassTag
class Dilation2D extends TensorflowOpsLoader {
import Utils._
override def build[T: ClassTag](nodeDef: NodeDef, byteOrder: ByteOrder,
context: Context[T])(implicit ev: TensorNumeric[T]): Module[T] = {
val attributes = nodeDef.getAttrMap
val padding = getString(attributes, "padding")
val strides = getIntList(attributes, "strides").toArray
val rates = getIntList(attributes, "rates").toArray
val t = getType(nodeDef.getAttrMap, "T")
if (t == DataType.DT_FLOAT) {
Dilation2DOps[T, Float](strides, rates, padding)
} else if (t == DataType.DT_DOUBLE) {
Dilation2DOps[T, Double](strides, rates, padding)
} else {
throw new UnsupportedOperationException(s"Not support load Dilation2D when type is ${t}")
}
}
}