public class BinomialDistribution extends BaseRandomOp
dataType, shape
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
BinomialDistribution() |
BinomialDistribution(@NonNull INDArray z,
@NonNull INDArray probabilities)
This op fills Z with binomial distribution over given trials with probability for each trial given as probabilities INDArray
|
BinomialDistribution(@NonNull INDArray z,
int trials,
double probability)
This op fills Z with binomial distribution over given trials with single given probability for all trials
|
BinomialDistribution(@NonNull INDArray z,
int trials,
@NonNull INDArray probabilities)
This op fills Z with binomial distribution over given trials with probability for each trial given as probabilities INDArray
|
BinomialDistribution(int trials,
double probability,
DataType dt,
long[] shape) |
BinomialDistribution(SameDiff sd,
int trials,
double probability,
DataType dataType,
long[] shape) |
BinomialDistribution(SameDiff sd,
int trials,
double probability,
long[] shape) |
Modifier and Type | Method and Description |
---|---|
List<DataType> |
calculateOutputDataTypes(List<DataType> inputDataTypes)
Calculate the data types for the output arrays.
|
List<SDVariable> |
doDiff(List<SDVariable> f1)
The actual implementation for automatic differentiation.
|
boolean |
isTripleArgRngOp() |
String |
onnxName()
The opName of this function in onnx
|
String |
opName()
The name of the op
|
int |
opNum()
The number of the op (mainly for old legacy XYZ ops
like
Op ) |
void |
setZ(INDArray z)
set z (the solution ndarray)
|
String |
tensorflowName()
The opName of this function tensorflow
|
calculateOutputShape, calculateOutputShape, isInPlace, opType
clearArrays, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, outputVariables, setX, setY, toCustomOp, toString, x, y, z
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, toCustomOp, x, y, z
public BinomialDistribution(SameDiff sd, int trials, double probability, long[] shape)
public BinomialDistribution(SameDiff sd, int trials, double probability, DataType dataType, long[] shape)
public BinomialDistribution(int trials, double probability, DataType dt, long[] shape)
public BinomialDistribution()
public BinomialDistribution(@NonNull @NonNull INDArray z, int trials, double probability)
z
- trials
- probability
- public BinomialDistribution(@NonNull @NonNull INDArray z, int trials, @NonNull @NonNull INDArray probabilities)
z
- trials
- probabilities
- array with probability value for each trialpublic int opNum()
DifferentialFunction
Op
)opNum
in interface Op
opNum
in class DifferentialFunction
public String opName()
DifferentialFunction
opName
in interface Op
opName
in class DifferentialFunction
public String onnxName()
DifferentialFunction
public String tensorflowName()
DifferentialFunction
tensorflowName
in class BaseOp
public List<SDVariable> doDiff(List<SDVariable> f1)
DifferentialFunction
doDiff
in class DifferentialFunction
public void setZ(INDArray z)
Op
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 BaseRandomOp
inputDataTypes
- The data types of the inputspublic boolean isTripleArgRngOp()
isTripleArgRngOp
in class BaseRandomOp
Copyright © 2020. All rights reserved.