public class NextIteration extends BaseCompatOp
DynamicCustomOp.DynamicCustomOpsBuilder
Modifier and Type | Field and Description |
---|---|
static String |
OP_NAME
WARNING: do not change without changing serialization methods
See
org.nd4j.autodiff.samediff.serde.FlatBuffersMapper#getOpNum(String, Type)
and DifferentialFunctionClassHolder.customOpClassForHashAndName(long, String) |
static int |
OP_NUM |
frameName
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
NextIteration(SameDiff sameDiff,
SDVariable x) |
Modifier and Type | Method and Description |
---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> inputDataTypes)
Calculate the data types for the output arrays.
|
int |
getNumOutputs() |
void |
initFromTensorFlow(NodeDef nodeDef,
SameDiff initWith,
Map<String,AttrValue> attributesForNode,
GraphDef graph)
Initialize the function from the given
NodeDef |
String |
opName()
This method returns op opName as string
|
Op.Type |
opType()
The type of the op
|
SDVariable[] |
outputVariables()
Return the output variables for this differential function.
|
String |
tensorflowName()
The opName of this function tensorflow
|
attributeAdaptersForFunction, calculateOutputShape, getFrameName, mappingsForFunction, setFrameName
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, clearArrays, dArgs, doDiff, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, initFromOnnx, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, onnxName, opHash, opNum, outputArguments, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull
arg, arg, argNames, args, configFieldName, diff, dup, equals, getValue, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
public static final String OP_NAME
org.nd4j.autodiff.samediff.serde.FlatBuffersMapper#getOpNum(String, Type)
and DifferentialFunctionClassHolder.customOpClassForHashAndName(long, String)
public static final int OP_NUM
public NextIteration(SameDiff sameDiff, SDVariable x)
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public SDVariable[] outputVariables()
DifferentialFunction
outputVariables
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public Op.Type opType()
DifferentialFunction
opType
in class DynamicCustomOp
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class BaseCompatOp
public int getNumOutputs()
getNumOutputs
in class DifferentialFunction
public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
DifferentialFunction
DifferentialFunction.calculateOutputShape()
, this method differs in that it does not
require the input arrays to be populated.
This is important as it allows us to do greedy datatype inference for the entire net - even if arrays are not
available.calculateOutputDataTypes
in class DifferentialFunction
inputDataTypes
- The data types of the inputsCopyright © 2020. All rights reserved.