Class BinomialDistributionEx
- java.lang.Object
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- org.nd4j.autodiff.functions.DifferentialFunction
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- org.nd4j.linalg.api.ops.BaseOp
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- org.nd4j.linalg.api.ops.random.BaseRandomOp
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- org.nd4j.linalg.api.ops.random.impl.BinomialDistributionEx
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public class BinomialDistributionEx extends BaseRandomOp
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Field Summary
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Fields inherited from class org.nd4j.linalg.api.ops.random.BaseRandomOp
dataType, shape
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Fields inherited from class org.nd4j.linalg.api.ops.BaseOp
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
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Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
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Constructor Summary
Constructors Constructor Description BinomialDistributionEx()
BinomialDistributionEx(@NonNull INDArray z, long trials, double probability)
This op fills Z with binomial distribution over given trials with single given probability for all trialsBinomialDistributionEx(@NonNull INDArray z, long trials, @NonNull INDArray probabilities)
This op fills Z with binomial distribution over given trials with probability for each trial given as probabilities INDArrayBinomialDistributionEx(@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
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description List<LongShapeDescriptor>
calculateOutputShape()
Calculate the output shape for this opList<LongShapeDescriptor>
calculateOutputShape(OpContext oc)
List<SDVariable>
doDiff(List<SDVariable> f1)
The actual implementation for automatic differentiation.String
onnxName()
The opName of this function in onnxString
opName()
The name of the opint
opNum()
The number of the op (mainly for old legacy XYZ ops likeOp
)String
tensorflowName()
The opName of this function tensorflow-
Methods inherited from class org.nd4j.linalg.api.ops.random.BaseRandomOp
calculateOutputDataTypes, isInPlace, isTripleArgRngOp, opType
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Methods inherited from class org.nd4j.linalg.api.ops.BaseOp
clearArrays, computeVariables, defineDimensions, dimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, initFromOnnx, initFromTensorFlow, outputVariables, setX, setY, setZ, toCustomOp, toString, x, y, z
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Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
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Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
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Methods inherited from interface org.nd4j.linalg.api.ops.Op
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
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Constructor Detail
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BinomialDistributionEx
public BinomialDistributionEx()
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BinomialDistributionEx
public BinomialDistributionEx(@NonNull @NonNull INDArray z, long trials, double probability)
This op fills Z with binomial distribution over given trials with single given probability for all trials- Parameters:
z
-trials
-probability
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BinomialDistributionEx
public BinomialDistributionEx(@NonNull @NonNull INDArray z, long trials, @NonNull @NonNull INDArray probabilities)
This op fills Z with binomial distribution over given trials with probability for each trial given as probabilities INDArray- Parameters:
z
-trials
-probabilities
- array with probability value for each trial
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Method Detail
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opNum
public int opNum()
Description copied from class:DifferentialFunction
The number of the op (mainly for old legacy XYZ ops likeOp
)- Specified by:
opNum
in interfaceOp
- Overrides:
opNum
in classDifferentialFunction
- Returns:
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opName
public String opName()
Description copied from class:DifferentialFunction
The name of the op- Specified by:
opName
in interfaceOp
- Overrides:
opName
in classDifferentialFunction
- Returns:
- the opName of this operation
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onnxName
public String onnxName()
Description copied from class:DifferentialFunction
The opName of this function in onnx
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tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowName
in classBaseOp
- Returns:
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doDiff
public List<SDVariable> doDiff(List<SDVariable> f1)
Description copied from class:DifferentialFunction
The actual implementation for automatic differentiation.- Specified by:
doDiff
in classDifferentialFunction
- Returns:
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calculateOutputShape
public List<LongShapeDescriptor> calculateOutputShape(OpContext oc)
- Overrides:
calculateOutputShape
in classDifferentialFunction
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calculateOutputShape
public List<LongShapeDescriptor> calculateOutputShape()
Description copied from class:DifferentialFunction
Calculate the output shape for this op- Overrides:
calculateOutputShape
in classBaseRandomOp
- Returns:
- List of output shape descriptors
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