public class Linear extends BaseModule
DynamicCustomOp.DynamicCustomOpsBuilder, DynamicCustomOp.SameDiffBuilder
inplaceCall, outputVariables
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
Linear(int nIn,
int nOut,
WeightInitScheme weightInitScheme,
WeightInitScheme biasWeightInitScheme) |
Linear(SameDiff sameDiff,
int nIn,
int nOut,
WeightInitScheme weightInitScheme,
WeightInitScheme biasWeightInitScheme) |
Modifier and Type | Method and Description |
---|---|
List<int[]> |
calculateOutputShape()
Calculate
the output shape for this op
|
List<SDVariable> |
doDiff(List<SDVariable> f1)
The actual implementation for automatic differentiation.
|
void |
exec(INDArray... inputs) |
void |
execSameDiff(SDVariable... input) |
void |
initFromOnnx(OnnxProto3.NodeProto node,
SameDiff initWith,
Map<String,OnnxProto3.AttributeProto> attributesForNode,
OnnxProto3.GraphProto graph)
Iniitialize the function from the given
OnnxProto3.NodeProto |
void |
initFromTensorFlow(NodeDef nodeDef,
SameDiff initWith,
Map<String,AttrValue> attributesForNode,
GraphDef graph)
Initialize the function from the given
NodeDef |
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
This method returns op opName as string
|
String |
tensorflowName()
The opName of this function tensorflow
|
addModule, subModules
addIArgument, addInputArgument, addOutputArgument, addTArgument, asProperties, assertValidForExecution, builder, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, inputArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, populateInputsAndOutputsFromSameDiff, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, sameDiffBuilder, setInputArgument, setOutputArgument, tArgs, toString, updateInputsFromSameDiff
arg, args, attributeAdaptersForFunction, configFieldName, diff, dup, equals, f, getValue, hashCode, hasPlaceHolderInputs, isConfigProperties, larg, mappingsForFunction, onnxNames, propertiesForFunction, rarg, resolvePropertiesFromSameDiffBeforeExecution, setInstanceId, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, iArgs, inputArguments, isInplaceCall, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, outputArguments, populateInputsAndOutputsFromSameDiff, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, tArgs
public Linear(int nIn, int nOut, WeightInitScheme weightInitScheme, WeightInitScheme biasWeightInitScheme)
public Linear(SameDiff sameDiff, int nIn, int nOut, WeightInitScheme weightInitScheme, WeightInitScheme biasWeightInitScheme)
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunction
NodeDef
initFromTensorFlow
in class DynamicCustomOp
public void initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
DifferentialFunction
OnnxProto3.NodeProto
initFromOnnx
in class DynamicCustomOp
public List<SDVariable> doDiff(List<SDVariable> f1)
DifferentialFunction
doDiff
in class DynamicCustomOp
public List<int[]> calculateOutputShape()
DifferentialFunction
calculateOutputShape
in interface CustomOp
calculateOutputShape
in class DynamicCustomOp
public String onnxName()
DifferentialFunction
onnxName
in class DynamicCustomOp
public String tensorflowName()
DifferentialFunction
tensorflowName
in class DynamicCustomOp
public void exec(INDArray... inputs)
public void execSameDiff(SDVariable... input)
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