Uses of Class
org.nd4j.linalg.api.buffer.DataType
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Uses of DataType in org.nd4j.autodiff.functions
Methods in org.nd4j.autodiff.functions that return types with arguments of type DataType Modifier and Type Method Description List<DataType>DifferentialFunction. calculateOutputDataTypes(List<DataType> dataTypes)Calculate the data types for the output arrays.Method parameters in org.nd4j.autodiff.functions with type arguments of type DataType Modifier and Type Method Description List<DataType>DifferentialFunction. calculateOutputDataTypes(List<DataType> dataTypes)Calculate the data types for the output arrays. -
Uses of DataType in org.nd4j.autodiff.samediff
Fields in org.nd4j.autodiff.samediff declared as DataType Modifier and Type Field Description protected DataTypeSDVariable. dataTypeMethods in org.nd4j.autodiff.samediff that return DataType Modifier and Type Method Description DataTypeSDVariable. dataType()Methods in org.nd4j.autodiff.samediff with parameters of type DataType Modifier and Type Method Description SDVariableSDVariable. castTo(@NonNull DataType dataType)SDVariableSDVariable. castTo(String name, @NonNull DataType dataType)SDVariableSameDiff. constant(String name, DataType dataType, Number value)Create a new scalar constant (rank 0) with the specified value and datatypeTrainingConfig.BuilderTrainingConfig.Builder. initialLossDataType(DataType initialLossDataType)Set the initial loss data type, defaults toFLOAT- when setting a data type for a loss function we need a beginning data type to compute the gradients.SDVariableSameDiff. one(String name, DataType dataType, int... shape)Create a new variable with the specified shape, with all values initialized to 1.0.SDVariableSameDiff. one(String name, DataType dataType, long... shape)Create a new variable with the specified shape, with all values initialized to 1.0.SDVariableSameDiff. placeHolder(@NonNull String name, DataType dataType, long... shape)Create a a placeholder variable.SDVariableSameDiff. scalar(String name, DataType dataType, Number value)Create a new scalar (rank 0) SDVariable with the specified value and datatypeTensorArraySameDiff. tensorArray(DataType dataType)Create a new TensorArray.SDVariableSameDiff. var(@NonNull String name, @NonNull VariableType variableType, WeightInitScheme weightInitScheme, DataType dataType, long... shape)Variable initialization with a specifiedWeightInitSchemeThis method creates VARIABLE type SDVariable - i.e., must be floating point, and is a trainable parameter.SDVariableSameDiff. var(@NonNull String name, @NonNull WeightInitScheme weightInitScheme, @NonNull DataType dataType, @lombok.NonNull long... shape)Variable initialization with a specifiedWeightInitSchemeThis method creates VARIABLE type SDVariable - i.e., must be floating point, and is a trainable parameter.SDVariableSameDiff. var(String name, DataType dataType, int... shape)Creates aSDVariablewith the given shape and name
Any array will be generated with all zeros for the valuesSDVariableSameDiff. var(String name, DataType dataType, long... shape)Creates aSDVariablewith the given shape and name
Any array will be generated with all zeros for the values
This is a VARIABLE type SDVariable - i.e., must be floating point, and is a trainable parameter.SDVariableSameDiff. var(DataType dataType, int... shape)Creates aSDVariablewith the specified shape and a generated name
Any array will be generated with all zeros for the values
This method creates a VARIABLE type SDVariable - i.e., must be floating point, and is a trainable parameter.SDVariableSameDiff. var(DataType dataType, long... shape)Creates aSDVariablewith the specified shape and a generated name
Any array will be generated with all zeros for the values
This method creates a VARIABLE type SDVariable - i.e., must be floating point, and is a trainable parameter.SDVariableSameDiff. var(WeightInitScheme weightInitScheme, DataType dataType, long... shape)Creates aSDVariablewith the specified shape and a generated name.SDVariableSameDiff. zero(String name, DataType dataType, int... shape)Create a new variable with the specified shape, with all values initialized to 0.SDVariableSameDiff. zero(String name, DataType dataType, long... shape)Create a new variable with the specified shape, with all values initialized to 0.Method parameters in org.nd4j.autodiff.samediff with type arguments of type DataType Modifier and Type Method Description voidSameDiff. convertDataTypes(@NonNull Map<String,DataType> dataTypeMap)Convert the datatypes of the specified constants, placeholders and variables.
After conversion, the downstream datatypes are changed.Constructors in org.nd4j.autodiff.samediff with parameters of type DataType Constructor Description SDVariable(@NonNull String varName, @NonNull VariableType varType, @NonNull SameDiff sameDiff, long[] shape, DataType dataType)TrainingConfig(IUpdater updater, List<Regularization> regularization, boolean minimize, List<String> dataSetFeatureMapping, List<String> dataSetLabelMapping, List<String> dataSetFeatureMaskMapping, List<String> dataSetLabelMaskMapping, List<String> lossVariables, Map<String,List<IEvaluation>> trainEvaluations, Map<String,Integer> trainEvaluationLabels, Map<String,List<IEvaluation>> validationEvaluations, Map<String,Integer> validationEvaluationLabels, DataType initialLossDataType)TrainingConfig(IUpdater updater, List<Regularization> regularization, boolean minimize, List<String> dataSetFeatureMapping, List<String> dataSetLabelMapping, List<String> dataSetFeatureMaskMapping, List<String> dataSetLabelMaskMapping, List<String> lossVariables, DataType initialLossDataType)Create a training configuration suitable for training both single input/output and multi input/output networks.
See also theTrainingConfig.Builderfor creating a TrainingConfig -
Uses of DataType in org.nd4j.autodiff.samediff.config
Methods in org.nd4j.autodiff.samediff.config with parameters of type DataType Modifier and Type Method Description static SDValueSDValue. empty(SDValueType valueType, DataType dataType)Create an empty value for the givenDataType -
Uses of DataType in org.nd4j.autodiff.samediff.internal
Methods in org.nd4j.autodiff.samediff.internal with parameters of type DataType Modifier and Type Method Description INDArraySessionMemMgr. allocate(boolean detached, DataType dataType, long... shape)Allocate an array with the specified datatype and shape.
NOTE: This array should be assumed to be uninitialized - i.e., contains random values. -
Uses of DataType in org.nd4j.autodiff.samediff.internal.memory
Methods in org.nd4j.autodiff.samediff.internal.memory with parameters of type DataType Modifier and Type Method Description INDArrayArrayCacheMemoryMgr. allocate(boolean detached, DataType dataType, long... shape)INDArrayNoOpMemoryMgr. allocate(boolean detached, DataType dataType, long... shape) -
Uses of DataType in org.nd4j.autodiff.samediff.ops
Methods in org.nd4j.autodiff.samediff.ops with parameters of type DataType Modifier and Type Method Description SDVariableSDRandom. bernoulli(double p, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Bernoulli distribution,
with the specified probability.SDVariableSDRandom. bernoulli(String name, double p, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Bernoulli distribution,
with the specified probability.SDVariableSDRandom. binomial(int nTrials, double p, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Binomial distribution,
with the specified number of trials and probability.SDVariableSDRandom. binomial(String name, int nTrials, double p, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Binomial distribution,
with the specified number of trials and probability.SDVariableSDBaseOps. castTo(String name, SDVariable arg, DataType datatype)Cast the array to a new datatype - for example, Integer -> FloatSDVariableSDBaseOps. castTo(SDVariable arg, DataType datatype)Cast the array to a new datatype - for example, Integer -> FloatSDVariableSDMath. confusionMatrix(String name, SDVariable labels, SDVariable pred, DataType dataType)Compute the 2d confusion matrix of size [numClasses, numClasses] from a pair of labels and predictions, both of
which are represented as integer values.SDVariableSDMath. confusionMatrix(SDVariable labels, SDVariable pred, DataType dataType)Compute the 2d confusion matrix of size [numClasses, numClasses] from a pair of labels and predictions, both of
which are represented as integer values.SDVariableSDBaseOps. create(String name, SDVariable shape, DataType dataType)Return a newly created variable, with the specified shape and data type.SDVariableSDBaseOps. create(String name, SDVariable shape, DataType dataType, String order, boolean initialize)Return a newly created variable, with the specified shape and data type.SDVariableSDBaseOps. create(SDVariable shape, DataType dataType)Return a newly created variable, with the specified shape and data type.SDVariableSDBaseOps. create(SDVariable shape, DataType dataType, String order, boolean initialize)Return a newly created variable, with the specified shape and data type.SDVariableSDRandom. exponential(double lambda, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a exponential distribution:
P(x) = lambda * exp(-lambda * x)
Inputs must satisfy the following constraints:
Must be positive: lambda > 0SDVariableSDRandom. exponential(String name, double lambda, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a exponential distribution:
P(x) = lambda * exp(-lambda * x)
Inputs must satisfy the following constraints:
Must be positive: lambda > 0SDVariableSDMath. eye(int rows, int cols, DataType dataType, int... dimensions)Generate an identity matrix with the specified number of rows and columns
Example:SDVariableSDMath. eye(String name, int rows, int cols, DataType dataType, int... dimensions)Generate an identity matrix with the specified number of rows and columns
Example:SDVariableSDBaseOps. fill(String name, SDVariable shape, DataType dataType, double value)Generate an output variable with the specified (dynamic) shape with all elements set to the specified valueSDVariableSDBaseOps. fill(SDVariable shape, DataType dataType, double value)Generate an output variable with the specified (dynamic) shape with all elements set to the specified valueSDVariableSDBaseOps. linspace(String name, SDVariable start, SDVariable stop, SDVariable number, DataType dataType)Create a new 1d array with values evenly spaced between values 'start' and 'stop'
For example, linspace(start=3.0, stop=4.0, number=3) will generate [3.0, 3.5, 4.0]SDVariableSDBaseOps. linspace(String name, DataType dataType, double start, double stop, long number)Create a new 1d array with values evenly spaced between values 'start' and 'stop'
For example, linspace(start=3.0, stop=4.0, number=3) will generate [3.0, 3.5, 4.0]SDVariableSDBaseOps. linspace(SDVariable start, SDVariable stop, SDVariable number, DataType dataType)Create a new 1d array with values evenly spaced between values 'start' and 'stop'
For example, linspace(start=3.0, stop=4.0, number=3) will generate [3.0, 3.5, 4.0]SDVariableSDBaseOps. linspace(DataType dataType, double start, double stop, long number)Create a new 1d array with values evenly spaced between values 'start' and 'stop'
For example, linspace(start=3.0, stop=4.0, number=3) will generate [3.0, 3.5, 4.0]SDVariableSDRandom. logNormal(double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Log Normal distribution,
i.e.,log(x) ~ N(mean, stdev)SDVariableSDRandom. logNormal(String name, double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Log Normal distribution,
i.e.,log(x) ~ N(mean, stdev)SDVariableSDMath. mergeMaxIndex(String name, SDVariable[] x, DataType dataType)Return array of max elements indices with along tensor dimensionsSDVariableSDMath. mergeMaxIndex(SDVariable[] x, DataType dataType)Return array of max elements indices with along tensor dimensionsSDVariableSDRandom. normal(double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev)SDVariableSDRandom. normal(String name, double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev)SDVariableSDRandom. normalTruncated(double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev).SDVariableSDRandom. normalTruncated(String name, double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev).SDVariableSDBaseOps. oneHot(String name, SDVariable indices, int depth, int axis, double on, double off, DataType dataType)Convert the array to a one-hot array with values and for each entry
If input has shape [ a, ..., n] then output has shape [ a, ..., n, depth],
with {out[i, ..., j, in[i,...,j]] with other values being set toSDVariableSDBaseOps. oneHot(SDVariable indices, int depth, int axis, double on, double off, DataType dataType)Convert the array to a one-hot array with values and for each entry
If input has shape [ a, ..., n] then output has shape [ a, ..., n, depth],
with {out[i, ..., j, in[i,...,j]] with other values being set toSDVariableSDBaseOps. onesLike(String name, SDVariable input, DataType dataType)As per onesLike(String, SDVariable) but the output datatype may be specifiedSDVariableSDBaseOps. onesLike(SDVariable input, DataType dataType)As per onesLike(String, SDVariable) but the output datatype may be specifiedSDVariableSDBaseOps. range(double from, double to, double step, DataType dataType)Create a new variable with a 1d array, where the values start at from and increment by step
up to (but not including) limit.
For example, range(1.0, 3.0, 0.5) will return [1.0, 1.5, 2.0, 2.5]SDVariableSDBaseOps. range(String name, double from, double to, double step, DataType dataType)Create a new variable with a 1d array, where the values start at from and increment by step
up to (but not including) limit.
For example, range(1.0, 3.0, 0.5) will return [1.0, 1.5, 2.0, 2.5]SDVariableSDBaseOps. range(String name, SDVariable from, SDVariable to, SDVariable step, DataType dataType)Create a new variable with a 1d array, where the values start at from and increment by step
up to (but not including) limit.
For example, range(1.0, 3.0, 0.5) will return [1.0, 1.5, 2.0, 2.5]SDVariableSDBaseOps. range(SDVariable from, SDVariable to, SDVariable step, DataType dataType)Create a new variable with a 1d array, where the values start at from and increment by step
up to (but not including) limit.
For example, range(1.0, 3.0, 0.5) will return [1.0, 1.5, 2.0, 2.5]SDVariableSDBaseOps. sequenceMask(String name, SDVariable lengths, int maxLen, DataType dataType)Generate a sequence mask (with values 0 or 1) based on the specified lengths
Specifically, out[i, ..., k, j] = (j < lengths[i, ..., k] ? 1.0 : 0.0)SDVariableSDBaseOps. sequenceMask(String name, SDVariable lengths, SDVariable maxLen, DataType dataType)Generate a sequence mask (with values 0 or 1) based on the specified lengths
Specifically, out[i, ..., k, j] = (j < lengths[i, ..., k] ? 1.0 : 0.0)SDVariableSDBaseOps. sequenceMask(String name, SDVariable lengths, DataType dataType)see sequenceMask(String, SDVariable, SDVariable, DataType)SDVariableSDBaseOps. sequenceMask(SDVariable lengths, int maxLen, DataType dataType)Generate a sequence mask (with values 0 or 1) based on the specified lengths
Specifically, out[i, ..., k, j] = (j < lengths[i, ..., k] ? 1.0 : 0.0)SDVariableSDBaseOps. sequenceMask(SDVariable lengths, SDVariable maxLen, DataType dataType)Generate a sequence mask (with values 0 or 1) based on the specified lengths
Specifically, out[i, ..., k, j] = (j < lengths[i, ..., k] ? 1.0 : 0.0)SDVariableSDBaseOps. sequenceMask(SDVariable lengths, DataType dataType)see sequenceMask(String, SDVariable, SDVariable, DataType)SDVariableSDLinalg. tri(String name, DataType dataType, int row, int column, int diagonal)An array with ones at and below the given diagonal and zeros elsewhere.SDVariableSDLinalg. tri(DataType dataType, int row, int column, int diagonal)An array with ones at and below the given diagonal and zeros elsewhere.SDVariableSDRandom. uniform(double min, double max, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a uniform distribution,
U(min,max)SDVariableSDRandom. uniform(String name, double min, double max, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a uniform distribution,
U(min,max) -
Uses of DataType in org.nd4j.autodiff.samediff.serde
Methods in org.nd4j.autodiff.samediff.serde that return DataType Modifier and Type Method Description static DataTypeFlatBuffersMapper. getDataTypeFromByte(byte val)This method converts enums for DataTypeMethods in org.nd4j.autodiff.samediff.serde with parameters of type DataType Modifier and Type Method Description static byteFlatBuffersMapper. getDataTypeAsByte(@NonNull DataType type)This method converts enums for DataType -
Uses of DataType in org.nd4j.imports.descriptors.properties.adapters
Methods in org.nd4j.imports.descriptors.properties.adapters that return DataType Modifier and Type Method Description static DataTypeDataTypeAdapter. dtypeConv(int dataType)static DataTypeDataTypeAdapter. dtypeConv(DataType dataType) -
Uses of DataType in org.nd4j.imports.graphmapper.tf
Methods in org.nd4j.imports.graphmapper.tf that return DataType Modifier and Type Method Description static DataTypeTFGraphMapper. convertType(DataType tfType)Convert from TF proto datatype to ND4J datatype -
Uses of DataType in org.nd4j.imports.graphmapper.tf.tensors
Methods in org.nd4j.imports.graphmapper.tf.tensors that return DataType Modifier and Type Method Description DataTypeTFTensorMapper. dataType()DataTypeTFTensorMappers.BaseTensorMapper. dataType() -
Uses of DataType in org.nd4j.linalg.api.buffer
Fields in org.nd4j.linalg.api.buffer declared as DataType Modifier and Type Field Description static DataTypeDataType. FLOAT16static DataTypeDataType. INT16static DataTypeDataType. INT32static DataTypeDataType. INT64static DataTypeDataType. INT8protected DataTypeBaseDataBuffer. typestatic DataTypeDataType. UINT8Methods in org.nd4j.linalg.api.buffer that return DataType Modifier and Type Method Description DataTypeBaseDataBuffer. dataType()The data opType of the bufferDataTypeDataBuffer. dataType()The data opType of the bufferstatic DataTypeDataType. fromInt(int type)Values inherited from https://github.com/eclipse/deeplearning4j/blob/master/libnd4j/include/array/DataType.hstatic DataTypeDataType. fromNumpy(String numpyDtypeName)static DataTypeDataType. valueOf(String name)Returns the enum constant of this type with the specified name.static DataType[]DataType. values()Returns an array containing the constants of this enum type, in the order they are declared.Methods in org.nd4j.linalg.api.buffer that return types with arguments of type DataType Modifier and Type Method Description static Triple<DataBuffer.AllocationMode,Long,DataType>BaseDataBuffer. readHeader(@NonNull InputStream is)Methods in org.nd4j.linalg.api.buffer with parameters of type DataType Modifier and Type Method Description abstract voidBaseDataBuffer. pointerIndexerByCurrentType(DataType currentType)voidBaseDataBuffer. putByDestinationType(long i, Number element, DataType globalType)voidBaseDataBuffer. read(DataInputStream s, @NonNull DataBuffer.AllocationMode allocMode, long len, @NonNull DataType dtype)voidBaseDataBuffer. read(InputStream is, DataBuffer.AllocationMode allocationMode, long length, DataType dataType)voidDataBuffer. read(DataInputStream s, DataBuffer.AllocationMode allocationMode, long length, DataType dataType)voidDataBuffer. read(InputStream is, DataBuffer.AllocationMode allocationMode, long length, DataType dataType)Write this buffer to the input stream.protected voidBaseDataBuffer. readContent(DataInputStream s, DataType sourceType, DataType thisType) -
Uses of DataType in org.nd4j.linalg.api.buffer.factory
Methods in org.nd4j.linalg.api.buffer.factory with parameters of type DataType Modifier and Type Method Description DataBufferDataBufferFactory. create(ByteBuffer underlyingBuffer, DataType type, long length, long offset)Creates a DataBuffer from java.nio.ByteBufferDataBufferDataBufferFactory. create(org.bytedeco.javacpp.Pointer pointer, org.bytedeco.javacpp.Pointer specialPointer, DataType type, long length, org.bytedeco.javacpp.indexer.Indexer indexer)DataBufferDataBufferFactory. create(org.bytedeco.javacpp.Pointer pointer, DataType type, long length, org.bytedeco.javacpp.indexer.Indexer indexer)Create a data buffer based on the given pointer, data buffer opType, and length of the bufferDataBufferDataBufferFactory. create(DataType dataType, long length, boolean initialize)DataBufferDataBufferFactory. create(DataType dataType, long length, boolean initialize, MemoryWorkspace workspace) -
Uses of DataType in org.nd4j.linalg.api.buffer.util
Methods in org.nd4j.linalg.api.buffer.util that return DataType Modifier and Type Method Description static DataTypeDataTypeUtil. getDtypeFromContext()get the allocation mode from the contextstatic DataTypeDataTypeUtil. getDtypeFromContext(String dType)Get the allocation mode from the contextMethods in org.nd4j.linalg.api.buffer.util with parameters of type DataType Modifier and Type Method Description static StringDataTypeUtil. getDTypeForName(DataType allocationMode)Gets the name of the allocation modestatic intDataTypeUtil. lengthForDtype(DataType type)Returns the length for the given data opTypestatic voidDataTypeUtil. setDTypeForContext(DataType allocationModeForContext)Set the allocation mode for the nd4j context The value must be one of: heap, java cpp, or direct or an @link{IllegalArgumentException} is thrown -
Uses of DataType in org.nd4j.linalg.api.concurrency
Methods in org.nd4j.linalg.api.concurrency with parameters of type DataType Modifier and Type Method Description voidDistributedINDArray. allocate(int entry, DataType dataType, long... shape)This method allocates INDArray for specified entry -
Uses of DataType in org.nd4j.linalg.api.memory
Methods in org.nd4j.linalg.api.memory with parameters of type DataType Modifier and Type Method Description PagedPointerMemoryWorkspace. alloc(long requiredMemory, DataType dataType, boolean initialize)This method does allocation from a given WorkspacePagedPointerMemoryWorkspace. alloc(long requiredMemory, MemoryKind kind, DataType dataType, boolean initialize)This method does allocation from a given Workspace -
Uses of DataType in org.nd4j.linalg.api.memory.abstracts
Methods in org.nd4j.linalg.api.memory.abstracts with parameters of type DataType Modifier and Type Method Description PagedPointerDummyWorkspace. alloc(long requiredMemory, DataType dataType, boolean initialize)This method does allocation from a given WorkspacePagedPointerDummyWorkspace. alloc(long requiredMemory, MemoryKind kind, DataType dataType, boolean initialize)This method does allocation from a given WorkspacePagedPointerNd4jWorkspace. alloc(long requiredMemory, DataType type, boolean initialize)PagedPointerNd4jWorkspace. alloc(long requiredMemory, MemoryKind kind, DataType type, boolean initialize) -
Uses of DataType in org.nd4j.linalg.api.ndarray
Methods in org.nd4j.linalg.api.ndarray that return DataType Modifier and Type Method Description DataTypeBaseNDArray. dataType()DataTypeINDArray. dataType()This method returns dtype for this INDArrayMethods in org.nd4j.linalg.api.ndarray with parameters of type DataType Modifier and Type Method Description INDArrayBaseNDArray. castTo(DataType dataType)INDArrayINDArray. castTo(DataType dataType)This method cast elements of this INDArray to new data typeprotected static DataTypeExBaseNDArray. convertType(DataType type)Pair<DataBuffer,long[]>BaseShapeInfoProvider. createShapeInformation(long[] shape, char order, DataType dataType)This method creates shapeInformation buffer, based on shape & order being passed inPair<DataBuffer,long[]>BaseShapeInfoProvider. createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, DataType dataType, boolean empty)Pair<DataBuffer,long[]>BaseShapeInfoProvider. createShapeInformation(long[] shape, DataType dataType)This method creates shapeInformation buffer, based on shape being passed inPair<DataBuffer,long[]>ShapeInfoProvider. createShapeInformation(long[] shape, char order, DataType dataType)This method creates long shapeInformation buffer, based on shape & order being passed inPair<DataBuffer,long[]>ShapeInfoProvider. createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, DataType dataType, boolean empty)This method creates long shapeInformation buffer, based on detailed shape info being passed inPair<DataBuffer,long[]>ShapeInfoProvider. createShapeInformation(long[] shape, DataType dataType)This method creates long shapeInformation buffer, based on shape being passed inConstructors in org.nd4j.linalg.api.ndarray with parameters of type DataType Constructor Description BaseNDArray(DataBuffer buffer, long[] shape, long[] stride, char ordering, DataType type)BaseNDArray(DataBuffer buffer, long[] shape, long[] stride, char ordering, DataType type, MemoryWorkspace workspace)BaseNDArray(DataBuffer buffer, long[] shape, long[] stride, long offset, char ordering, DataType dataType)BaseNDArray(DataBuffer buffer, long[] shape, long[] stride, long offset, long ews, char ordering, DataType dataType)BaseNDArray(DataBuffer buffer, DataType dataType, long[] shape, long[] stride, long offset, char ordering)BaseNDArray(DataType type, long[] shape, long[] paddings, long[] paddingOffsets, char ordering, MemoryWorkspace workspace)BaseNDArray(DataType type, long[] shape, long[] stride, long offset, char ordering, boolean initialize)BaseNDArray(DataType type, long[] shape, long[] stride, long offset, char ordering, boolean initialize, MemoryWorkspace workspace) -
Uses of DataType in org.nd4j.linalg.api.ops
Fields in org.nd4j.linalg.api.ops with type parameters of type DataType Modifier and Type Field Description protected List<DataType>DynamicCustomOp. dArgumentsprotected List<DataType>BaseOpContext. fastpath_dMethods in org.nd4j.linalg.api.ops that return DataType Modifier and Type Method Description DataType[]CustomOp. dArgs()DataType[]DynamicCustomOp. dArgs()DataTypeBaseReduceBoolOp. resultType()DataTypeBaseReduceBoolOp. resultType(OpContext oc)DataTypeBaseReduceFloatOp. resultType()DataTypeBaseReduceFloatOp. resultType(OpContext oc)DataTypeBaseReduceLongOp. resultType()DataTypeBaseReduceLongOp. resultType(OpContext oc)DataTypeBaseReduceSameOp. resultType()DataTypeBaseReduceSameOp. resultType(OpContext oc)DataTypeBaseTransformAnyOp. resultType()DataTypeBaseTransformAnyOp. resultType(OpContext oc)DataTypeBaseTransformBoolOp. resultType()DataTypeBaseTransformBoolOp. resultType(OpContext oc)DataTypeBaseTransformFloatOp. resultType()DataTypeBaseTransformFloatOp. resultType(OpContext oc)DataTypeBaseTransformSameOp. resultType()DataTypeBaseTransformSameOp. resultType(OpContext oc)DataTypeBaseTransformStrictOp. resultType()DataTypeBaseTransformStrictOp. resultType(OpContext opContext)DataTypeReduceOp. resultType()This method returns datatype for result array wrt given inputsDataTypeReduceOp. resultType(OpContext oc)DataTypeTransformOp. resultType()This method returns datatype for result array wrt given inputsDataTypeTransformOp. resultType(OpContext opContext)Methods in org.nd4j.linalg.api.ops with parameters of type DataType Modifier and Type Method Description voidCustomOp. addDArgument(DataType... arg)voidDynamicCustomOp. addDArgument(DataType... arg)DataBufferBaseOp. extraArgsDataBuff(DataType dtype)DataBufferOp. extraArgsDataBuff(DataType bufferType)Returns the extra args as a data bufferINDArrayDynamicCustomOp. generateFake(DataType dataType, long... shape)Generate fake data forDynamicCustomOp.computeArrays()of the the given shape with the given data typevoidBaseOpContext. setArgs(INDArray[] inputArrs, long[] iArgs, DataType[] dArgs, double[] tArgs, boolean[] bArgs)voidOpContext. setArgs(INDArray[] inputArrs, long[] iArgs, DataType[] dArgs, double[] tArgs, boolean[] bArgs)set context argumentsvoidBaseOpContext. setDArguments(DataType... arguments)voidOpContext. setDArguments(DataType... arguments)This method sets data type arguments required for operation -
Uses of DataType in org.nd4j.linalg.api.ops.compat
Methods in org.nd4j.linalg.api.ops.compat that return types with arguments of type DataType Modifier and Type Method Description List<DataType>CompatSparseToDense. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.compat with type arguments of type DataType Modifier and Type Method Description List<DataType>CompatSparseToDense. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.compression
Methods in org.nd4j.linalg.api.ops.compression that return types with arguments of type DataType Modifier and Type Method Description List<DataType>DecodeBitmap. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>DecodeThreshold. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>EncodeBitmap. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>EncodeThreshold. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.compression with type arguments of type DataType Modifier and Type Method Description List<DataType>DecodeBitmap. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>DecodeThreshold. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>EncodeBitmap. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>EncodeThreshold. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.custom
Constructors in org.nd4j.linalg.api.ops.custom with parameters of type DataType Constructor Description BitCast(INDArray in, DataType dataType)BitCast(INDArray in, DataType dataType, INDArray out)Tri(SameDiff sameDiff, DataType dataType, int row, int column, int diag)Tri(DataType dataType, int row, int column, int diag) -
Uses of DataType in org.nd4j.linalg.api.ops.executioner
Methods in org.nd4j.linalg.api.ops.executioner with parameters of type DataType Modifier and Type Method Description DataBufferDefaultOpExecutioner. createConstantBuffer(double[] values, DataType desiredType)DataBufferDefaultOpExecutioner. createConstantBuffer(float[] values, DataType desiredType)DataBufferDefaultOpExecutioner. createConstantBuffer(int[] values, DataType desiredType)DataBufferDefaultOpExecutioner. createConstantBuffer(long[] values, DataType desiredType)DataBufferOpExecutioner. createConstantBuffer(double[] values, DataType desiredType)DataBufferOpExecutioner. createConstantBuffer(float[] values, DataType desiredType)DataBufferOpExecutioner. createConstantBuffer(int[] values, DataType desiredType)DataBufferOpExecutioner. createConstantBuffer(long[] values, DataType desiredType)This method returns constant buffer for the given jvm arrayDataBufferDefaultOpExecutioner. createShapeInfo(long[] shape, long[] stride, long elementWiseStride, char order, DataType dtype, boolean empty)DataBufferDefaultOpExecutioner. createShapeInfo(long[] shape, long[] stride, long elementWiseStride, char order, DataType dtype, long extras)DataBufferOpExecutioner. createShapeInfo(long[] shape, long[] stride, long elementWiseStride, char order, DataType dtype, boolean empty)This method returns shapeInfo DataBufferDataBufferOpExecutioner. createShapeInfo(long[] shape, long[] stride, long elementWiseStride, char order, DataType dtype, long extra)static voidDefaultOpExecutioner. validateDataType(DataType expectedType, Object op, INDArray... operands)static voidDefaultOpExecutioner. validateDataType(DataType expectedType, Op op)Validate the data types for the given operation -
Uses of DataType in org.nd4j.linalg.api.ops.impl.broadcast
Methods in org.nd4j.linalg.api.ops.impl.broadcast that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BiasAdd. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BiasAddGrad. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BroadcastGradientArgs. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BroadcastTo. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.broadcast with type arguments of type DataType Modifier and Type Method Description List<DataType>BiasAdd. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BiasAddGrad. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BroadcastGradientArgs. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BroadcastTo. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.controlflow
Methods in org.nd4j.linalg.api.ops.impl.controlflow that return types with arguments of type DataType Modifier and Type Method Description List<DataType>Select. calculateOutputDataTypes(List<DataType> inputDataType)List<DataType>Where. calculateOutputDataTypes(List<DataType> inputTypes)Method parameters in org.nd4j.linalg.api.ops.impl.controlflow with type arguments of type DataType Modifier and Type Method Description List<DataType>Select. calculateOutputDataTypes(List<DataType> inputDataType)List<DataType>Where. calculateOutputDataTypes(List<DataType> inputTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.controlflow.compat
Methods in org.nd4j.linalg.api.ops.impl.controlflow.compat that return types with arguments of type DataType Modifier and Type Method Description List<DataType>Enter. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Exit. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LoopCond. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Merge. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>NextIteration. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>StopGradient. calculateOutputDataTypes(List<DataType> input)List<DataType>Switch. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>While. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.controlflow.compat with type arguments of type DataType Modifier and Type Method Description List<DataType>Enter. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Exit. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LoopCond. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Merge. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>NextIteration. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>StopGradient. calculateOutputDataTypes(List<DataType> input)List<DataType>Switch. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>While. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.image
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Uses of DataType in org.nd4j.linalg.api.ops.impl.layers.convolution
Fields in org.nd4j.linalg.api.ops.impl.layers.convolution declared as DataType Modifier and Type Field Description protected DataTypeMaxPoolWithArgmax. outputType -
Uses of DataType in org.nd4j.linalg.api.ops.impl.layers.recurrent
Methods in org.nd4j.linalg.api.ops.impl.layers.recurrent that return types with arguments of type DataType Modifier and Type Method Description List<DataType>GRU. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>GRUBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>GRUCell. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMBlock. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMBlockCell. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMLayer. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMLayerBp. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.layers.recurrent with type arguments of type DataType Modifier and Type Method Description List<DataType>GRU. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>GRUBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>GRUCell. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMBlock. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMBlockCell. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMLayer. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LSTMLayerBp. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.loss
Methods in org.nd4j.linalg.api.ops.impl.loss that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BaseLoss. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>L2Loss. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SoftmaxCrossEntropyWithLogitsLoss. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SparseSoftmaxCrossEntropyLossWithLogits. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>WeightedCrossEntropyLoss. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.loss with type arguments of type DataType Modifier and Type Method Description List<DataType>BaseLoss. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>L2Loss. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SoftmaxCrossEntropyWithLogitsLoss. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SparseSoftmaxCrossEntropyLossWithLogits. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>WeightedCrossEntropyLoss. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.loss.bp
Methods in org.nd4j.linalg.api.ops.impl.loss.bp that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BaseLossBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SoftmaxCrossEntropyLossBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SoftmaxCrossEntropyWithLogitsLossBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>SparseSoftmaxCrossEntropyLossWithLogitsBp. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.loss.bp with type arguments of type DataType Modifier and Type Method Description List<DataType>BaseLossBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SoftmaxCrossEntropyLossBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SoftmaxCrossEntropyWithLogitsLossBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>SparseSoftmaxCrossEntropyLossWithLogitsBp. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.reduce
Methods in org.nd4j.linalg.api.ops.impl.reduce that return types with arguments of type DataType Modifier and Type Method Description List<DataType>Mmul. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MmulBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>Moments. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>NormalizeMoments. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SufficientStatistics. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>TensorMmul. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>TensorMmulBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>ZeroFraction. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.reduce with type arguments of type DataType Modifier and Type Method Description List<DataType>Mmul. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MmulBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>Moments. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>NormalizeMoments. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SufficientStatistics. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>TensorMmul. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>TensorMmulBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>ZeroFraction. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.reduce.bp
Methods in org.nd4j.linalg.api.ops.impl.reduce.bp that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BaseReductionBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>DotBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>PowBp. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.reduce.bp with type arguments of type DataType Modifier and Type Method Description List<DataType>BaseReductionBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>DotBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>PowBp. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.reduce.custom
Methods in org.nd4j.linalg.api.ops.impl.reduce.custom that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BaseDynamicCustomBoolReduction. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BaseDynamicCustomIndexReduction. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BaseDynamicCustomLongReduction. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BaseDynamicCustomReduction. calculateOutputDataTypes(List<DataType> dataTypes)Calculate the data types for the output arrays.List<DataType>BatchMmul. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>LogSumExp. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.reduce.custom with type arguments of type DataType Modifier and Type Method Description List<DataType>BaseDynamicCustomBoolReduction. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BaseDynamicCustomIndexReduction. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BaseDynamicCustomLongReduction. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BaseDynamicCustomReduction. calculateOutputDataTypes(List<DataType> dataTypes)Calculate the data types for the output arrays.List<DataType>BatchMmul. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>LogSumExp. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.reduce3
Methods in org.nd4j.linalg.api.ops.impl.reduce3 that return DataType Modifier and Type Method Description DataTypeBaseReduce3Op. resultType()DataTypeJaccardDistance. resultType()Methods in org.nd4j.linalg.api.ops.impl.reduce3 that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BaseReduce3Op. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.reduce3 with type arguments of type DataType Modifier and Type Method Description List<DataType>BaseReduce3Op. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.scalar
Methods in org.nd4j.linalg.api.ops.impl.scalar that return types with arguments of type DataType Modifier and Type Method Description List<DataType>PRelu. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>RectifiedLinearDerivative. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.scalar with type arguments of type DataType Modifier and Type Method Description List<DataType>PRelu. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>RectifiedLinearDerivative. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.scatter
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Uses of DataType in org.nd4j.linalg.api.ops.impl.shape
Fields in org.nd4j.linalg.api.ops.impl.shape declared as DataType Modifier and Type Field Description protected DataTypeShape. dataTypeprotected DataTypeShapeN. dataTypeprotected DataTypeSize. dataTypestatic DataTypeConfusionMatrix. DEFAULT_DTYPEstatic DataTypeEye. DEFAULT_DTYPEstatic DataTypeOneHot. DEFAULT_DTYPEstatic DataTypeSequenceMask. DEFAULT_DTYPEprotected DataTypeCreate. outputTypeprotected DataTypeOnesAs. outputTypeprotected DataTypeOnesLike. outputTypeprotected DataTypeZerosLike. outputTypeConstructors in org.nd4j.linalg.api.ops.impl.shape with parameters of type DataType Constructor Description ConfusionMatrix(@NonNull INDArray labels, @NonNull INDArray predicted, @NonNull DataType dataType)ConfusionMatrix(@NonNull INDArray labels, @NonNull INDArray predicted, Integer numClasses, @NonNull DataType dataType)ConfusionMatrix(@NonNull INDArray labels, @NonNull INDArray predicted, INDArray weights, Integer numClasses, @NonNull DataType dataType)ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, SDVariable weights, DataType dataType)ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, DataType dataType)Create(@NonNull INDArray shape, char order, boolean initialize, DataType dataType)Create(String name, SameDiff sameDiff, SDVariable input, char order, boolean initialize, DataType dataType)Create(SameDiff sd, SDVariable shape, DataType dataType)Create(SameDiff sd, SDVariable shape, DataType dataType, String order, boolean initialize)Create(INDArray shape, boolean initialize, DataType dataType)Create(INDArray shape, DataType dataType)Create(INDArray shape, DataType dataType, String order, boolean initialize)Eye(int numRows, int numCols, DataType dataType)Eye(int numRows, int numCols, DataType dataType, int[] batchDimension)Eye(SameDiff sameDiff, int numRows, int numCols, DataType dataType)Eye(SameDiff sameDiff, int numRows, int numCols, DataType dataType, int[] batchDimension)Eye(SameDiff sameDiff, SDVariable numRows, SDVariable numCols, DataType dataType, int[] batchDimension)Linspace(double start, double stop, long number, @NonNull DataType dataType)Linspace(@NonNull INDArray start, @NonNull INDArray stop, @NonNull INDArray number, @NonNull DataType dataType)Linspace(SameDiff sameDiff, SDVariable from, SDVariable to, SDVariable length, DataType dataType)Linspace(SameDiff sameDiff, DataType dataType, double start, double stop, long number)Linspace(DataType dataType, double start, double stop, long number)Linspace(DataType dataType, INDArray start, INDArray stop, INDArray number)MergeMaxIndex(@NonNull SameDiff sd, @NonNull SDVariable[] x, @NonNull DataType dataType)MergeMaxIndex(@NonNull INDArray[] x, @NonNull DataType dataType)OneHot(SameDiff sameDiff, SDVariable indices, int depth, int axis, double on, double off, DataType dataType)OneHot(INDArray indices, int depth, int axis, double on, double off, DataType dataType)OnesAs(@NonNull INDArray input, DataType dataType)OnesAs(String name, SameDiff sameDiff, SDVariable input, DataType dataType)OnesAs(SameDiff sameDiff, SDVariable input, DataType dataType)OnesLike(@NonNull INDArray input, DataType dataType)OnesLike(String name, SameDiff sameDiff, SDVariable input, DataType dataType)OnesLike(SameDiff sameDiff, SDVariable input, DataType dataType)SequenceMask(@NonNull INDArray input, int maxLen, DataType dataType)SequenceMask(@NonNull INDArray input, @NonNull DataType dataType)SequenceMask(@NonNull INDArray input, INDArray maxLength, @NonNull DataType dataType)SequenceMask(SameDiff sameDiff, SDVariable input, int maxLen, DataType dataType)SequenceMask(SameDiff sameDiff, SDVariable input, SDVariable maxLen, DataType dataType)SequenceMask(SameDiff sameDiff, SDVariable input, DataType dataType)ZerosLike(String name, SameDiff sameDiff, SDVariable input, boolean inPlace, DataType dataType)ZerosLike(String name, SameDiff sameDiff, SDVariable input, DataType dataType)ZerosLike(INDArray in, INDArray out, DataType dataType) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.shape.bp
Methods in org.nd4j.linalg.api.ops.impl.shape.bp that return types with arguments of type DataType Modifier and Type Method Description List<DataType>ConcatBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MergeAvgBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>MergeMaxBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SliceBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>StridedSliceBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>TileBp. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.shape.bp with type arguments of type DataType Modifier and Type Method Description List<DataType>ConcatBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MergeAvgBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>MergeMaxBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SliceBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>StridedSliceBp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>TileBp. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.shape.tensorops
Fields in org.nd4j.linalg.api.ops.impl.shape.tensorops declared as DataType Modifier and Type Field Description protected DataTypeTensorArrayRead. importDataTypeprotected DataTypeTensorArray. tensorArrayDataTypeMethods in org.nd4j.linalg.api.ops.impl.shape.tensorops with parameters of type DataType Modifier and Type Method Description static SDVariableTensorArray. createEmpty(SameDiff sd, DataType dataType)Create an empty sequence with the specified data type.static SDVariableTensorArray. createEmpty(SameDiff sd, DataType dataType, String outputVarName)Create an empty sequence with the specified data type.Constructors in org.nd4j.linalg.api.ops.impl.shape.tensorops with parameters of type DataType Constructor Description TensorArray(String name, SameDiff sameDiff, DataType dataType)TensorArray(SameDiff sameDiff, DataType dataType)TensorArray(DataType dataType) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.summarystats
Methods in org.nd4j.linalg.api.ops.impl.summarystats that return DataType Modifier and Type Method Description DataTypeVariance. resultType()DataTypeVariance. resultType(OpContext oc)Methods in org.nd4j.linalg.api.ops.impl.summarystats that return types with arguments of type DataType Modifier and Type Method Description List<DataType>StandardDeviation. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>Variance. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.summarystats with type arguments of type DataType Modifier and Type Method Description List<DataType>StandardDeviation. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>Variance. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms
Methods in org.nd4j.linalg.api.ops.impl.transforms that return DataType Modifier and Type Method Description DataTypeMaxOut. resultType()DataTypeMaxOut. resultType(OpContext oc)Methods in org.nd4j.linalg.api.ops.impl.transforms that return types with arguments of type DataType Modifier and Type Method Description List<DataType>Angle. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>Assert. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BaseDynamicTransformOp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BinCount. calculateOutputDataTypes(List<DataType> inputTypes)List<DataType>CheckNumerics. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Cholesky. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>HistogramFixedWidth. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>IdentityN. calculateOutputDataTypes(List<DataType> list)List<DataType>NthElement. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Pad. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms with type arguments of type DataType Modifier and Type Method Description List<DataType>Angle. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>Assert. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BaseDynamicTransformOp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>BinCount. calculateOutputDataTypes(List<DataType> inputTypes)List<DataType>CheckNumerics. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Cholesky. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>HistogramFixedWidth. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>IdentityN. calculateOutputDataTypes(List<DataType> list)List<DataType>NthElement. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Pad. calculateOutputDataTypes(List<DataType> inputDataTypes)Constructors in org.nd4j.linalg.api.ops.impl.transforms with parameters of type DataType Constructor Description BinCount(SameDiff sd, SDVariable in, SDVariable weights, Integer minLength, Integer maxLength, DataType outputType) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.any
Methods in org.nd4j.linalg.api.ops.impl.transforms.any that return types with arguments of type DataType Modifier and Type Method Description List<DataType>IsMax. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.any with type arguments of type DataType Modifier and Type Method Description List<DataType>IsMax. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.clip
Methods in org.nd4j.linalg.api.ops.impl.transforms.clip that return types with arguments of type DataType Modifier and Type Method Description List<DataType>ClipByAvgNorm. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>ClipByNorm. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>ClipByNormBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>ClipByValue. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.clip with type arguments of type DataType Modifier and Type Method Description List<DataType>ClipByAvgNorm. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>ClipByNorm. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>ClipByNormBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>ClipByValue. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.comparison
Methods in org.nd4j.linalg.api.ops.impl.transforms.comparison that return types with arguments of type DataType Modifier and Type Method Description List<DataType>CompareAndReplace. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.comparison with type arguments of type DataType Modifier and Type Method Description List<DataType>CompareAndReplace. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.custom
Fields in org.nd4j.linalg.api.ops.impl.transforms.custom declared as DataType Modifier and Type Field Description static DataTypeUnique. DEFAULT_IDX_DTYPEstatic DataTypeUniqueWithCounts. DEFAULT_IDX_DTYPEMethods in org.nd4j.linalg.api.ops.impl.transforms.custom with parameters of type DataType Modifier and Type Method Description INDArrayInvertPermutation. generateFake(DataType dataType, long... shape)Constructors in org.nd4j.linalg.api.ops.impl.transforms.custom with parameters of type DataType Constructor Description Fill(SameDiff sameDiff, SDVariable shape, DataType dtype, double value)Fill(INDArray shape, DataType dtype, double value) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.custom.segment
Methods in org.nd4j.linalg.api.ops.impl.transforms.custom.segment that return types with arguments of type DataType Modifier and Type Method Description List<DataType>SegmentMax. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentMean. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentMin. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentProd. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentSum. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.custom.segment with type arguments of type DataType Modifier and Type Method Description List<DataType>SegmentMax. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentMean. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentMin. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentProd. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SegmentSum. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.dtype
Methods in org.nd4j.linalg.api.ops.impl.transforms.dtype that return types with arguments of type DataType Modifier and Type Method Description List<DataType>Cast. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MinMaxDataType. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.dtype with type arguments of type DataType Modifier and Type Method Description List<DataType>Cast. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MinMaxDataType. calculateOutputDataTypes(List<DataType> dataTypes)Constructors in org.nd4j.linalg.api.ops.impl.transforms.dtype with parameters of type DataType Constructor Description Cast(@NonNull INDArray arg, @NonNull DataType dataType)Cast(SameDiff sameDiff, SDVariable arg, @NonNull DataType dst) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.gradient
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Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic
Methods in org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic that return types with arguments of type DataType Modifier and Type Method Description List<DataType>FloorModOp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MergeAddOp. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic with type arguments of type DataType Modifier and Type Method Description List<DataType>FloorModOp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MergeAddOp. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic.bp
Methods in org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic.bp that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BaseArithmeticBackpropOp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MergeAddBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SquaredDifferenceBpOp. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.pairwise.arithmetic.bp with type arguments of type DataType Modifier and Type Method Description List<DataType>BaseArithmeticBackpropOp. calculateOutputDataTypes(List<DataType> dataTypes)List<DataType>MergeAddBp. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>SquaredDifferenceBpOp. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.same
Methods in org.nd4j.linalg.api.ops.impl.transforms.same that return types with arguments of type DataType Modifier and Type Method Description List<DataType>Abs. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Identity. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.same with type arguments of type DataType Modifier and Type Method Description List<DataType>Abs. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Identity. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.segment
Methods in org.nd4j.linalg.api.ops.impl.transforms.segment that return types with arguments of type DataType Modifier and Type Method Description List<DataType>UnsortedSegmentMax. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentMean. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentMin. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentProd. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentSqrtN. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentSum. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.segment with type arguments of type DataType Modifier and Type Method Description List<DataType>UnsortedSegmentMax. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentMean. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentMin. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentProd. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentSqrtN. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UnsortedSegmentSum. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.segment.bp
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Uses of DataType in org.nd4j.linalg.api.ops.impl.transforms.strict
Methods in org.nd4j.linalg.api.ops.impl.transforms.strict that return types with arguments of type DataType Modifier and Type Method Description List<DataType>ELU. calculateOutputDataTypes(List<DataType> dataTypes)Method parameters in org.nd4j.linalg.api.ops.impl.transforms.strict with type arguments of type DataType Modifier and Type Method Description List<DataType>ELU. calculateOutputDataTypes(List<DataType> dataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.random
Fields in org.nd4j.linalg.api.ops.random declared as DataType Modifier and Type Field Description protected DataTypeBaseRandomOp. dataTypeMethods in org.nd4j.linalg.api.ops.random that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BaseRandomOp. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.random with type arguments of type DataType Modifier and Type Method Description List<DataType>BaseRandomOp. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.random.compat
Methods in org.nd4j.linalg.api.ops.random.compat that return types with arguments of type DataType Modifier and Type Method Description List<DataType>RandomStandardNormal. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.random.compat with type arguments of type DataType Modifier and Type Method Description List<DataType>RandomStandardNormal. calculateOutputDataTypes(List<DataType> inputDataTypes) -
Uses of DataType in org.nd4j.linalg.api.ops.random.custom
Methods in org.nd4j.linalg.api.ops.random.custom that return types with arguments of type DataType Modifier and Type Method Description List<DataType>DistributionUniform. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomBernoulli. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomExponential. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomGamma. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomNormal. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomPoisson. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomShuffle. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.random.custom with type arguments of type DataType Modifier and Type Method Description List<DataType>DistributionUniform. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomBernoulli. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomExponential. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomGamma. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomNormal. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomPoisson. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomShuffle. calculateOutputDataTypes(List<DataType> inputDataTypes)Constructors in org.nd4j.linalg.api.ops.random.custom with parameters of type DataType Constructor Description DistributionUniform(SameDiff sd, SDVariable shape, double min, double max, DataType dataType)DistributionUniform(INDArray shape, INDArray out, double min, double max, DataType dataType)RandomExponential(double lambda, DataType datatype, long... shape)RandomExponential(SameDiff sd, double lambda, DataType dataType, long... shape) -
Uses of DataType in org.nd4j.linalg.api.ops.random.impl
Fields in org.nd4j.linalg.api.ops.random.impl declared as DataType Modifier and Type Field Description static DataTypeRange. DEFAULT_DTYPEMethods in org.nd4j.linalg.api.ops.random.impl that return types with arguments of type DataType Modifier and Type Method Description List<DataType>BernoulliDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BinomialDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>GaussianDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LogNormalDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomMultinomial. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Range. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>TruncatedNormalDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UniformDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)Method parameters in org.nd4j.linalg.api.ops.random.impl with type arguments of type DataType Modifier and Type Method Description List<DataType>BernoulliDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>BinomialDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>GaussianDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>LogNormalDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>RandomMultinomial. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>Range. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>TruncatedNormalDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)List<DataType>UniformDistribution. calculateOutputDataTypes(List<DataType> inputDataTypes)Constructors in org.nd4j.linalg.api.ops.random.impl with parameters of type DataType Constructor Description BernoulliDistribution(double p, DataType datatype, long... shape)BernoulliDistribution(SameDiff sd, double prob, DataType dataType, long[] shape)BinomialDistribution(int trials, double probability, DataType dt, long[] shape)BinomialDistribution(SameDiff sd, int trials, double probability, DataType dataType, long[] shape)GaussianDistribution(double mean, double stddev, DataType datatype, long... shape)GaussianDistribution(SameDiff sd, double mean, double stddev, DataType dataType, long[] shape)Linspace(double from, double to, long length, DataType dataType)Linspace(double from, long length, double step, DataType dataType)LogNormalDistribution(double mean, double stddev, DataType datatype, long... shape)LogNormalDistribution(SameDiff sd, double mean, double stdev, DataType dataType, long... shape)Range(double from, double to, double step, DataType dataType)Range(SameDiff sd, double from, double to, double step, DataType dataType)Range(SameDiff sd, SDVariable from, SDVariable to, SDVariable step, DataType dataType)Range(INDArray from, INDArray to, INDArray step, DataType dataType)TruncatedNormalDistribution(double mean, double stddev, DataType datatype, long... shape)TruncatedNormalDistribution(SameDiff sd, double mean, double stddev, DataType dataType, long[] shape)UniformDistribution(double min, double max, DataType datatype, long... shape)UniformDistribution(SameDiff sd, double from, double to, DataType dataType, long[] shape) -
Uses of DataType in org.nd4j.linalg.api.shape
Methods in org.nd4j.linalg.api.shape that return DataType Modifier and Type Method Description DataTypeLongShapeDescriptor. dataType()static DataTypeShape. pickPairwiseDataType(@NonNull DataType typeX, @NonNull Number number)static DataTypeShape. pickPairwiseDataType(@NonNull DataType typeX, @NonNull DataType typeY)Return a data type to use for output within a pair wise operation such as add or subtract.Methods in org.nd4j.linalg.api.shape with parameters of type DataType Modifier and Type Method Description LongShapeDescriptorLongShapeDescriptor. asDataType(DataType dataType)Return a new LongShapeDescriptor with the same shape, strides, order etc but with the specified datatype insteadstatic DataBufferShape. createShapeInformation(long[] shape, long[] stride, long elementWiseStride, char order, DataType dataType, boolean empty)static LongShapeDescriptorLongShapeDescriptor. empty(@NonNull DataType dataType)static LongShapeDescriptorLongShapeDescriptor. fromShape(@lombok.NonNull long[] shape, @lombok.NonNull long[] strides, long ews, char order, @NonNull DataType dataType, boolean empty)static LongShapeDescriptorLongShapeDescriptor. fromShape(int[] shape, @NonNull DataType dataType)static LongShapeDescriptorLongShapeDescriptor. fromShape(long[] shape, @NonNull DataType dataType)static booleanShape. isB(@NonNull DataType x)static booleanShape. isR(@NonNull DataType x)static booleanShape. isS(@NonNull DataType x)static booleanShape. isZ(@NonNull DataType x)static DataTypeShape. pickPairwiseDataType(@NonNull DataType typeX, @NonNull Number number)static DataTypeShape. pickPairwiseDataType(@NonNull DataType typeX, @NonNull DataType typeY)Return a data type to use for output within a pair wise operation such as add or subtract. -
Uses of DataType in org.nd4j.linalg.api.shape.options
Methods in org.nd4j.linalg.api.shape.options that return DataType Modifier and Type Method Description static DataTypeArrayOptionsHelper. convertToDataType(DataType dataType)static DataTypeArrayOptionsHelper. dataType(long opt)static DataTypeArrayOptionsHelper. dataType(long[] shapeInfo)static DataTypeArrayOptionsHelper. dataType(@NonNull String dataType)Methods in org.nd4j.linalg.api.shape.options with parameters of type DataType Modifier and Type Method Description static longArrayOptionsHelper. setOptionBit(long storage, DataType type) -
Uses of DataType in org.nd4j.linalg.cache
Methods in org.nd4j.linalg.cache with parameters of type DataType Modifier and Type Method Description DataBufferConstantHandler. getConstantBuffer(boolean[] array, DataType dataType)This method returns DataBuffer with constant equal to input array.DataBufferConstantHandler. getConstantBuffer(double[] array, DataType dataType)This method returns DataBuffer with contant equal to input array.DataBufferConstantHandler. getConstantBuffer(float[] array, DataType dataType)This method returns DataBuffer with contant equal to input array.DataBufferConstantHandler. getConstantBuffer(int[] array, DataType dataType)DataBufferConstantHandler. getConstantBuffer(long[] array, DataType dataType)This method returns DataBuffer with constant equal to input array.Constructors in org.nd4j.linalg.cache with parameters of type DataType Constructor Description ArrayDescriptor(boolean[] array, DataType dtype)ArrayDescriptor(double[] array, DataType dtype)ArrayDescriptor(float[] array, DataType dtype)ArrayDescriptor(int[] array, DataType dtype)ArrayDescriptor(long[] array, DataType dtype) -
Uses of DataType in org.nd4j.linalg.checkutil
Methods in org.nd4j.linalg.checkutil with parameters of type DataType Modifier and Type Method Description static INDArrayCheckUtil. convertFromApacheMatrix(org.apache.commons.math3.linear.RealMatrix matrix, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dPermutedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dPermutedWithShape(long seed, long[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dReshapedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dReshapedWithShape(long seed, long[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dSubArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dSubArraysWithShape(long seed, long[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dTensorAlongDimensionWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get3dTensorAlongDimensionWithShape(long seed, long[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get4dPermutedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get4dReshapedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get4dSubArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get4dTensorAlongDimensionWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get5dPermutedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get5dReshapedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get5dSubArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get5dTensorAlongDimensionWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get6dPermutedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get6dReshapedWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. get6dSubArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getAll3dTestArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getAll3dTestArraysWithShape(long seed, long[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getAll4dTestArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getAll4dTestArraysWithShape(int seed, long[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getAll5dTestArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getAll6dTestArraysWithShape(int seed, int[] shape, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getAllTestMatricesWithShape(char ordering, int rows, int cols, int seed, DataType dataType)Get an array of INDArrays (2d) all with the specified shape.static List<Pair<INDArray,String>>NDArrayCreationUtil. getAllTestMatricesWithShape(long rows, long cols, long seed, DataType dataType)Get an array of INDArrays (2d) all with the specified shape.static Pair<INDArray,String>NDArrayCreationUtil. getPermutedWithShape(char ordering, long rows, long cols, long seed, DataType dataType)static Pair<INDArray,String>NDArrayCreationUtil. getPermutedWithShape(long rows, long cols, long seed, DataType dataType)static Pair<INDArray,String>NDArrayCreationUtil. getReshapedWithShape(char ordering, long rows, long cols, long seed, DataType dataType)static Pair<INDArray,String>NDArrayCreationUtil. getReshapedWithShape(long rows, long cols, long seed, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getSubMatricesWithShape(char ordering, long rows, long cols, long seed, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getSubMatricesWithShape(long rows, long cols, long seed, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getTensorAlongDimensionMatricesWithShape(char ordering, long rows, long cols, long seed, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getTensorAlongDimensionMatricesWithShape(long rows, long cols, long seed, DataType dataType)static List<Pair<INDArray,String>>NDArrayCreationUtil. getTestMatricesWithVaryingShapes(int rank, char order, DataType dataType)Test utility to sweep shapes given a rank Given a rank will generate random test matrices that will cover all cases of a shape with a '1' anywhere in the shape as well a shape with random ints that are not 0 or 1 eg.static Pair<INDArray,String>NDArrayCreationUtil. getTransposedMatrixWithShape(char ordering, int rows, int cols, int seed, DataType dataType)static Pair<INDArray,String>NDArrayCreationUtil. getTransposedMatrixWithShape(long rows, long cols, long seed, DataType dataType) -
Uses of DataType in org.nd4j.linalg.compression
Methods in org.nd4j.linalg.compression with parameters of type DataType Modifier and Type Method Description DataBufferBasicNDArrayCompressor. decompress(DataBuffer buffer, DataType targetType)Decompress the given databufferDataBufferNDArrayCompressor. decompress(DataBuffer buffer, DataType targetType)Return a compressed databuffervoidCompressedDataBuffer. pointerIndexerByCurrentType(DataType currentType)static DataBufferCompressedDataBuffer. readUnknown(DataInputStream s, DataBuffer.AllocationMode allocMode, long length, DataType type)Drop-in replacement wrapper for BaseDataBuffer.read() method, aware of CompressedDataBuffer -
Uses of DataType in org.nd4j.linalg.factory
Fields in org.nd4j.linalg.factory declared as DataType Modifier and Type Field Description protected static DataTypeNd4j. dtypeMethods in org.nd4j.linalg.factory that return DataType Modifier and Type Method Description static DataTypeNd4j. dataType()Returns the data opType used for the runtimestatic DataTypeNd4j. defaultFloatingPointType()DataTypeBaseNDArrayFactory. dtype()Returns the data opType for this ndarrayDataTypeNDArrayFactory. dtype()Returns the data opType for this ndarrayMethods in org.nd4j.linalg.factory with parameters of type DataType Modifier and Type Method Description abstract INDArrayBaseNDArrayFactory. create(float[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayBaseNDArrayFactory. create(int[] shape, DataType dataType, MemoryWorkspace workspace)static INDArrayNd4j. create(boolean[] data, long[] shape, long[] strides, char order, DataType type)static INDArrayNd4j. create(boolean[] data, long[] shape, DataType type)static INDArrayNd4j. create(byte[] data, long[] shape, long[] strides, char order, DataType type)static INDArrayNd4j. create(byte[] data, long[] shape, DataType type)static INDArrayNd4j. create(double[] data, long[] shape, long[] strides, char order, DataType type)static INDArrayNd4j. create(double[] data, long[] shape, DataType type)static INDArrayNd4j. create(float[] data, long[] shape, long[] strides, char order, DataType type)static INDArrayNd4j. create(float[] data, long[] shape, DataType type)static INDArrayNd4j. create(int[] data, long[] shape, long[] strides, char order, DataType type)Create an array of the specified type, shape and stride initialized with values from a java 1d array.static INDArrayNd4j. create(int[] data, long[] shape, DataType type)Create an array of the specified type and shape initialized with values from a java 1d array.static INDArrayNd4j. create(int[] shape, DataType dataType)Create an array of given shape and data type.static INDArrayNd4j. create(long[] data, long[] shape, long[] strides, char order, DataType type)static INDArrayNd4j. create(long[] data, long[] shape, DataType type)static INDArrayNd4j. create(short[] data, long[] shape, long[] strides, char order, DataType type)static INDArrayNd4j. create(short[] data, long[] shape, DataType type)static INDArrayNd4j. create(@NonNull DataType dataType, @lombok.NonNull long[] shape, char ordering)Create an array with given data type shape and ordering.static INDArrayNd4j. create(DataBuffer data, long[] newShape, long[] newStride, long offset, char ordering, DataType dataType)Create an array based on the data buffer with given shape, stride, offset and data type.static INDArrayNd4j. create(DataType dataType, @lombok.NonNull long[] shape, long[] strides, char ordering)Create an array with given shape, stride and ordering.static INDArrayNd4j. create(DataType type, long... shape)Create an array with specified shape and datatype.INDArrayNDArrayFactory. create(boolean[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(boolean[] data, long[] shape, long[] stride, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(byte[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(byte[] data, long[] shape, long[] stride, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(double[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(double[] data, long[] shape, long[] stride, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(float[] data, long[] shape, long[] stride, char order, DataType dataType)INDArrayNDArrayFactory. create(float[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(float[] data, long[] shape, long[] stride, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(int[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(int[] data, long[] shape, long[] stride, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(int[] shape, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(long[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(long[] data, long[] shape, long[] stride, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(short[] data, long[] shape, long[] stride, char order, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(short[] data, long[] shape, long[] stride, DataType dataType, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(DataBuffer data, long[] newShape, long[] newStride, long offset, char ordering, DataType dataType)INDArrayNDArrayFactory. create(DataType dataType, long[] shape, char ordering, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(DataType dataType, long[] shape, long[] strides, char ordering, MemoryWorkspace workspace)INDArrayNDArrayFactory. create(DataType dataType, long[] shape, long[] paddings, long[] paddingOffsets, char ordering, MemoryWorkspace workspace)Create an ndArray with padded Bufferstatic DataBufferNd4j. createBuffer(@lombok.NonNull int[] shape, @NonNull DataType type)Create a buffer equal of length prod(shape)static DataBufferNd4j. createBuffer(@lombok.NonNull long[] shape, @NonNull DataType type)static DataBufferNd4j. createBuffer(int[] shape, DataType type, long offset)Create a buffer equal of length prod(shape)static DataBufferNd4j. createBuffer(@NonNull org.bytedeco.javacpp.Pointer pointer, long length, @NonNull DataType dataType)Creates a buffer of the specified type and length with the given pointer.static DataBufferNd4j. createBuffer(@NonNull org.bytedeco.javacpp.Pointer pointer, @NonNull org.bytedeco.javacpp.Pointer devicePointer, long length, @NonNull DataType dataType)Creates a buffer of the specified type and length with the given pointer at the specified device.static DataBufferNd4j. createBuffer(ByteBuffer buffer, DataType type, int length)Creates a buffer of the specified opType and length with the given byte buffer.static DataBufferNd4j. createBuffer(ByteBuffer buffer, DataType type, int length, long offset)Creates a buffer of the specified opType and length with the given byte buffer.static DataBufferNd4j. createBuffer(org.bytedeco.javacpp.Pointer pointer, DataType type, long length, org.bytedeco.javacpp.indexer.Indexer indexer)Create a data buffer based on a pointer with the given opType and lengthstatic DataBufferNd4j. createBuffer(DataType dataType, long length, boolean initialize)Create a data buffer based on datatype.static DataBufferNd4j. createBuffer(DataType dataType, long length, boolean initialize, MemoryWorkspace workspace)Create a data buffer based on datatype, workspace.static DataBufferNd4j. createBufferDetached(int[] shape, DataType type)Create a buffer equal of length prod(shape).static DataBufferNd4j. createBufferDetached(long[] shape, DataType type)static DataBufferNd4j. createTypedBuffer(boolean[] data, DataType dataType)static DataBufferNd4j. createTypedBuffer(byte[] data, DataType dataType)static DataBufferNd4j. createTypedBuffer(double[] data, DataType dataType)Create a buffer based on the data of the underlying java array with the specified type..static DataBufferNd4j. createTypedBuffer(double[] data, DataType dataType, MemoryWorkspace workspace)Create a buffer based on the data of the underlying java array, specified type and workspacestatic DataBufferNd4j. createTypedBuffer(float[] data, DataType dataType)static DataBufferNd4j. createTypedBuffer(float[] data, DataType dataType, MemoryWorkspace workspace)static DataBufferNd4j. createTypedBuffer(int[] data, DataType dataType)static DataBufferNd4j. createTypedBuffer(long[] data, DataType dataType)static DataBufferNd4j. createTypedBuffer(short[] data, DataType dataType)static DataBufferNd4j. createTypedBufferDetached(boolean[] data, DataType dataType)static DataBufferNd4j. createTypedBufferDetached(byte[] data, DataType dataType)static DataBufferNd4j. createTypedBufferDetached(double[] data, DataType dataType)Create am uninitialized buffer based on the data of the underlying java array and specified type.static DataBufferNd4j. createTypedBufferDetached(float[] data, DataType dataType)static DataBufferNd4j. createTypedBufferDetached(int[] data, DataType dataType)static DataBufferNd4j. createTypedBufferDetached(long[] data, DataType dataType)static DataBufferNd4j. createTypedBufferDetached(short[] data, DataType dataType)static INDArrayNd4j. createUninitialized(DataType type, long... shape)static INDArrayNd4j. createUninitialized(DataType type, long[] shape, char ordering)Creates an *uninitialized* array with the specified data type, shape and ordering.INDArrayNDArrayFactory. createUninitialized(DataType dataType, long[] shape, char ordering, MemoryWorkspace workspace)static INDArrayNd4j. createUninitializedDetached(DataType dataType, char ordering, long... shape)Create an uninitialized ndArray.static INDArrayNd4j. createUninitializedDetached(DataType dataType, long... shape)SeeNd4j.createUninitializedDetached(DataType, char, long...)with default ordering.INDArrayNDArrayFactory. createUninitializedDetached(DataType dataType, char ordering, long... shape)Create an uninitialized ndArray.static INDArrayNd4j. empty(DataType type)This method creates "empty" INDArray of the specified datatypeINDArrayNDArrayFactory. empty(DataType type)static INDArrayNd4j. linspace(double lower, double upper, long num, @NonNull DataType dataType)Generate a linearly spaced 1d vector of the specified datatypestatic INDArrayNd4j. linspace(long lower, long upper, long num, @NonNull DataType dtype)Generate a linearly spaced vectorstatic INDArrayNd4j. linspace(@NonNull DataType dataType, double lower, double step, long num)Generate a linearly spaced 1d vector of the specified datatypestatic INDArrayNd4j. linspace(@NonNull DataType dtype, long lower, long num, long step)Generate a linearly spaced vectorstatic INDArrayNd4j. ones(DataType dataType, @lombok.NonNull long... shape)Creates an array with the specified datatype and shape, with values all set to 1static INDArrayNd4j. rand(@NonNull DataType dataType, @lombok.NonNull int... shape)Create a random ndarray with the given shape and data type Values are sampled from a uniform distribution over (0, 1)static INDArrayNd4j. rand(@NonNull DataType dataType, @lombok.NonNull long... shape)Create a random ndarray with values from a uniform distribution over (0, 1) with the given shape and data typestatic INDArrayNd4j. rand(@NonNull DataType dataType, char order, @lombok.NonNull int... shape)Deprecated.static INDArrayNd4j. rand(@NonNull DataType dataType, char order, @lombok.NonNull long... shape)Create a random ndarray with the given shape, data type, and array order Values are sampled from a uniform distribution over (0, 1)static INDArrayNd4j. rand(@NonNull DataType dataType, int[] shape, char order)Deprecated.use {@link Nd4j#rand(DataType, char, long...))static INDArrayNd4j. randn(@NonNull DataType dataType, @lombok.NonNull int[] shape)Create a ndarray of the given shape and data type with values from N(0,1)static INDArrayNd4j. randn(@NonNull DataType dataType, @lombok.NonNull long... shape)Create a ndarray of the given shape and data type with values from N(0,1)static INDArrayNd4j. randn(@NonNull DataType dataType, char order, @lombok.NonNull long... shape)Random normal N(0,1) with the specified shape and array orderstatic INDArrayNd4j. readNumpy(@NonNull DataType dataType, @NonNull InputStream filePath, @NonNull String split, @NonNull Charset charset)Read array from input stream.static INDArrayNd4j. readNumpy(DataType dataType, String filePath)Read array.
SeeNd4j.readNumpy(DataType, InputStream, String , Charset)with default split and UTF-8 encoding.static INDArrayNd4j. readNumpy(DataType dataType, String filePath, String split)Read array via input stream.INDArrayBaseNDArrayFactory. scalar(DataType dataType)static INDArrayNd4j. scalar(DataType dataType, Number value)Create a scalar ndarray with the specified value and datatypeINDArrayNDArrayFactory. scalar(DataType dataType)Create a scalar nd array with the data type and a default value depending on the data type.static voidNd4j. setDataType(@NonNull DataType dtype)Deprecated.static voidNd4j. setDefaultDataTypes(@NonNull DataType defaultType, @NonNull DataType defaultFloatingPointType)Set the default data types.
The default data types are used for array creation methods where no data type is specified.
When the user explicitly provides a datatype (such as in Nd4j.ones(DataType.FLOAT, 1, 10)) these default values will not be used.
defaultType: used in methods such as Nd4j.ones(1,10) and Nd4j.zeros(10).
defaultFloatingPointType: used internally where a floating point array needs to be created, but no datatype is specified.voidBaseNDArrayFactory. setDType(DataType dtype)Sets the data opTypevoidNDArrayFactory. setDType(DataType dtype)Sets the data opTypestatic intNd4j. sizeOfDataType(DataType dtype)This method returns size of element for specified dataType, in bytesstatic INDArrayNd4j. valueArrayOf(long[] shape, double value, DataType type)Creates an ndarray with the specified value as the only value in the ndarray.static INDArrayNd4j. valueArrayOf(long[] shape, long value, DataType type)static INDArrayNd4j. zeros(int[] shape, DataType dataType)static INDArrayNd4j. zeros(DataType dataType, @lombok.NonNull long... shape)Creates an array with the specified data tyoe and shape initialized with zero.Constructors in org.nd4j.linalg.factory with parameters of type DataType Constructor Description BaseNDArrayFactory(DataType dtype, char order)BaseNDArrayFactory(DataType dtype, Character order)Initialize with the given data opType and ordering The ndarray factory will use this for -
Uses of DataType in org.nd4j.linalg.factory.ops
Methods in org.nd4j.linalg.factory.ops with parameters of type DataType Modifier and Type Method Description INDArrayNDRandom. bernoulli(double p, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Bernoulli distribution,
with the specified probability.INDArrayNDRandom. binomial(int nTrials, double p, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Binomial distribution,
with the specified number of trials and probability.INDArrayNDBase. castTo(INDArray arg, DataType datatype)Cast the array to a new datatype - for example, Integer -> FloatINDArrayNDMath. confusionMatrix(INDArray labels, INDArray pred, DataType dataType)Compute the 2d confusion matrix of size [numClasses, numClasses] from a pair of labels and predictions, both of
which are represented as integer values.INDArrayNDBase. create(INDArray shape, DataType dataType)Return a newly created variable, with the specified shape and data type.INDArrayNDBase. create(INDArray shape, DataType dataType, String order, boolean initialize)Return a newly created variable, with the specified shape and data type.INDArrayNDRandom. exponential(double lambda, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a exponential distribution:
P(x) = lambda * exp(-lambda * x)
Inputs must satisfy the following constraints:
Must be positive: lambda > 0INDArrayNDMath. eye(int rows, int cols, DataType dataType, int... dimensions)Generate an identity matrix with the specified number of rows and columns
Example:INDArrayNDBase. fill(INDArray shape, DataType dataType, double value)Generate an output variable with the specified (dynamic) shape with all elements set to the specified valueINDArrayNDBase. linspace(DataType dataType, double start, double stop, long number)Create a new 1d array with values evenly spaced between values 'start' and 'stop'
For example, linspace(start=3.0, stop=4.0, number=3) will generate [3.0, 3.5, 4.0]INDArrayNDBase. linspace(INDArray start, INDArray stop, INDArray number, DataType dataType)Create a new 1d array with values evenly spaced between values 'start' and 'stop'
For example, linspace(start=3.0, stop=4.0, number=3) will generate [3.0, 3.5, 4.0]INDArrayNDRandom. logNormal(double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Log Normal distribution,
i.e.,log(x) ~ N(mean, stdev)INDArrayNDMath. mergeMaxIndex(INDArray[] x, DataType dataType)Return array of max elements indices with along tensor dimensionsINDArrayNDRandom. normal(double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev)INDArrayNDRandom. normalTruncated(double mean, double stddev, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev).INDArrayNDBase. oneHot(INDArray indices, int depth, int axis, double on, double off, DataType dataType)Convert the array to a one-hot array with values and for each entry
If input has shape [ a, ..., n] then output has shape [ a, ..., n, depth],
with {out[i, ..., j, in[i,...,j]] with other values being set toINDArrayNDBase. onesLike(INDArray input, DataType dataType)As per onesLike(String, SDVariable) but the output datatype may be specifiedINDArrayNDBase. range(double from, double to, double step, DataType dataType)Create a new variable with a 1d array, where the values start at from and increment by step
up to (but not including) limit.
For example, range(1.0, 3.0, 0.5) will return [1.0, 1.5, 2.0, 2.5]INDArrayNDBase. range(INDArray from, INDArray to, INDArray step, DataType dataType)Create a new variable with a 1d array, where the values start at from and increment by step
up to (but not including) limit.
For example, range(1.0, 3.0, 0.5) will return [1.0, 1.5, 2.0, 2.5]INDArrayNDBase. sequenceMask(INDArray lengths, int maxLen, DataType dataType)Generate a sequence mask (with values 0 or 1) based on the specified lengths
Specifically, out[i, ..., k, j] = (j < lengths[i, ..., k] ? 1.0 : 0.0)INDArrayNDBase. sequenceMask(INDArray lengths, DataType dataType)see sequenceMask(String, SDVariable, SDVariable, DataType)INDArrayNDBase. sequenceMask(INDArray lengths, INDArray maxLen, DataType dataType)Generate a sequence mask (with values 0 or 1) based on the specified lengths
Specifically, out[i, ..., k, j] = (j < lengths[i, ..., k] ? 1.0 : 0.0)INDArrayNDLinalg. tri(DataType dataType, int row, int column, int diagonal)An array with ones at and below the given diagonal and zeros elsewhere.INDArrayNDRandom. uniform(double min, double max, DataType datatype, long... shape)Generate a new random INDArray, where values are randomly sampled according to a uniform distribution,
U(min,max) -
Uses of DataType in org.nd4j.linalg.lossfunctions
Methods in org.nd4j.linalg.lossfunctions with parameters of type DataType Modifier and Type Method Description protected voidSameDiffLoss. createSameDiffInstance(DataType dataType) -
Uses of DataType in org.nd4j.linalg.ops.transforms
Methods in org.nd4j.linalg.ops.transforms with parameters of type DataType Modifier and Type Method Description static INDArrayTransforms. isMax(INDArray input, DataType dataType) -
Uses of DataType in org.nd4j.linalg.util
Methods in org.nd4j.linalg.util with parameters of type DataType Modifier and Type Method Description static ValidationResultNd4jValidator. validateINDArrayFile(@NonNull File f, DataType... allowableDataTypes)Validate whether the file represents a valid INDArray (of one of the allowed/specified data types) saved previously withNd4j.saveBinary(INDArray, File)to be read withNd4j.readBinary(File) -
Uses of DataType in org.nd4j.linalg.workspace
Methods in org.nd4j.linalg.workspace with parameters of type DataType Modifier and Type Method Description INDArrayBaseWorkspaceMgr. castTo(T arrayType, @NonNull DataType dataType, @NonNull INDArray toCast, boolean dupIfCorrectType)INDArrayWorkspaceMgr. castTo(T arrayType, @NonNull DataType dataType, @NonNull INDArray toCast, boolean dupIfCorrectType)Cast the specified array to the specified datatype.
If the array is already the correct type, the bahaviour depends on the 'dupIfCorrectType' argument.
dupIfCorrectType = false && toCast.dataType() == dataType: return input array as-is (unless workspace is wrong)
dupIfCorrectType = true && toCast.dataType() == dataType: duplicate the array into the specified workspaceINDArrayBaseWorkspaceMgr. create(T arrayType, @NonNull DataType dataType, @lombok.NonNull long... shape)INDArrayBaseWorkspaceMgr. create(T arrayType, @NonNull DataType dataType, @lombok.NonNull long[] shape, @lombok.NonNull char order)INDArrayWorkspaceMgr. create(T arrayType, DataType dataType, long... shape)Create an array in the specified array type's workspace (or detached if none is specified).INDArrayWorkspaceMgr. create(T arrayType, DataType dataType, long[] shape, char ordering)Create an array in the specified array type's workspace (or detached if none is specified).INDArrayBaseWorkspaceMgr. createUninitialized(T arrayType, @NonNull DataType dataType, @lombok.NonNull long[] shape, char order)INDArrayBaseWorkspaceMgr. createUninitialized(T arrayType, DataType dataType, long... shape)INDArrayWorkspaceMgr. createUninitialized(T arrayType, DataType dataType, long... shape)Create an uninitialized array in the specified array type's workspace (or detached if none is specified).INDArrayWorkspaceMgr. createUninitialized(T arrayType, DataType dataType, long[] shape, char order)Create an uninitialized array in the specified array type's workspace (or detached if none is specified). -
Uses of DataType in org.nd4j.list
Constructors in org.nd4j.list with parameters of type DataType Constructor Description NDArrayList(DataType dataType, int size) -
Uses of DataType in org.nd4j.weightinit
Methods in org.nd4j.weightinit with parameters of type DataType Modifier and Type Method Description INDArrayBaseWeightInitScheme. create(DataType dataType, long... shape)INDArrayWeightInitScheme. create(DataType dataType, long... shape)Create the arrayabstract INDArrayBaseWeightInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView) -
Uses of DataType in org.nd4j.weightinit.impl
Methods in org.nd4j.weightinit.impl with parameters of type DataType Modifier and Type Method Description INDArrayNDArraySupplierInitScheme. create(DataType dataType, long[] shape)INDArrayConstantInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayDistributionInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayIdentityInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayLecunUniformInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayOneInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayReluInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayReluUniformInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArraySigmoidUniformInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayUniformInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayVarScalingNormalFanAvgInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayVarScalingNormalFanInInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayVarScalingNormalFanOutInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayVarScalingNormalUniformFanInInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayVarScalingNormalUniformFanOutInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayVarScalingUniformFanAvgInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayXavierFanInInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayXavierInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayXavierUniformInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)INDArrayZeroInitScheme. doCreate(DataType dataType, long[] shape, INDArray paramsView)
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