com.intel.analytics.bigdl.utils.tf.loaders.StridedSlice.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.abstractnn.{AbstractModule, Activity}
import com.intel.analytics.bigdl.nn.tf.{StridedSlice => StridedSliceOps}
import com.intel.analytics.bigdl.tensor.Tensor
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 StridedSlice extends TensorflowOpsLoader {
import Utils._
override def build[T: ClassTag](nodeDef: NodeDef, byteOrder: ByteOrder,
context: Context[T])(implicit ev: TensorNumeric[T]): Module[T] = {
val t = getType(nodeDef, "T")
val beginMask = getInt(nodeDef.getAttrMap, "begin_mask")
val ellipsisMask = getInt(nodeDef.getAttrMap, "ellipsis_mask")
val endMask = getInt(nodeDef.getAttrMap, "end_mask")
val newAxisMask = getInt(nodeDef.getAttrMap, "new_axis_mask")
val shrinkAxisMask = getInt(nodeDef.getAttrMap, "shrink_axis_mask")
if (t == DataType.DT_INT32) {
StridedSliceOps[T, Int](beginMask, endMask, ellipsisMask,
newAxisMask, shrinkAxisMask, true)
} else if (t == DataType.DT_FLOAT) {
StridedSliceOps[T, Float](beginMask, endMask, ellipsisMask,
newAxisMask, shrinkAxisMask, true)
} else if (t == DataType.DT_DOUBLE) {
StridedSliceOps[T, Double](beginMask, endMask, ellipsisMask,
newAxisMask, shrinkAxisMask, true)
} else {
throw new UnsupportedOperationException(s"Not support load StridedSlice with type ${t}")
}
}
}
object StridedSlice {
def oneDTensorToArray(tensor: Tensor[Int]): Array[Int] = {
require(tensor.nDimension() == 1, "1D tensor required")
val result = new Array[Int](tensor.nElement())
var i = 0
while(i < tensor.nElement()) {
result(i) = tensor.valueAt(i + 1)
i += 1
}
result
}
}