Deprecated API

Contents

• Deprecated Classes
• Deprecated Fields
• Deprecated Methods
• Deprecated Enum Constants

Deprecated Classes

Class and Description
org.nd4j.linalg.api.ops.aggregates.impl.AggregateAxpy
org.nd4j.linalg.api.ops.aggregates.impl.AggregateCBOW
org.nd4j.linalg.api.ops.aggregates.impl.AggregateDot
org.nd4j.linalg.api.ops.aggregates.impl.AggregateSkipGram
org.nd4j.linalg.api.ops.impl.transforms.gradient.CubeDerivative Use CubeBp
org.nd4j.linalg.api.ops.impl.transforms.gradient.HardSigmoidDerivative Use HardSigmoidBp
org.nd4j.linalg.api.ops.impl.transforms.gradient.HardTanhDerivative Use HardTanhBp
org.nd4j.linalg.api.ops.aggregates.impl.HierarchicSoftmax
org.nd4j.linalg.dataset.api.iterator.MultipleEpochsIterator
org.nd4j.linalg.api.ops.impl.transforms.gradient.RationalTanhDerivative Use RationalTanhBp
org.nd4j.linalg.api.ops.impl.transforms.gradient.RectifiedTanhDerivative Use RectifiedTanhBp
org.nd4j.linalg.lossfunctions.serde.RowVectorDeserializer Use NDArrayTextDeSerializer
org.nd4j.linalg.lossfunctions.serde.RowVectorSerializer Use NDArrayTextSerializer
org.nd4j.linalg.api.ops.impl.transforms.gradient.SELUDerivative Use SeluBp
org.nd4j.linalg.api.ops.impl.transforms.strict.SigmoidDerivative Use SigmoidDerivative
org.nd4j.linalg.api.ops.impl.transforms.gradient.SoftSignDerivative Use SoftSignBp
org.nd4j.linalg.dataset.api.iterator.StandardScaler Use NormalizerStandardize for equivalent functionality. NormalizerStandardize is more stable (for examples, when a column contains all the same values for every example) but otherwise provides equivalent functionality. See also NormalizerMinMaxScaler
org.nd4j.linalg.api.ops.impl.transforms.strict.TanhDerivative Use TanhDerivative.

Deprecated Fields

Field and Description
org.nd4j.linalg.factory.Nd4j.DTYPE Use ND4JSystemProperties.DTYPE
org.nd4j.linalg.factory.Nd4j.LOG_INIT_ENV_PROPERTY Use ND4JSystemProperties.LOG_INITIALIZATION
org.nd4j.versioncheck.VersionCheck.VERSION_CHECK_PROPERTY Use ND4JSystemProperties.VERSION_CHECK_PROPERTY
org.nd4j.linalg.memory.provider.BasicWorkspaceManager.WorkspaceDeallocatorThreadName

Deprecated Methods

Method and Description
org.tensorflow.framework.MemoryStats.Builder.addAllDevicePersistentTensorAllocIds(Iterable<? extends Long>)
org.tensorflow.framework.MemoryStats.Builder.addDevicePersistentTensorAllocIds(long)
org.nd4j.evaluation.regression.RegressionEvaluation.averagecorrelationR2() Use RegressionEvaluation.averagePearsonCorrelation() instead. For the R2 score use RegressionEvaluation.averageRSquared().
org.nd4j.linalg.factory.BlasWrapper.axpy(double, INDArray, INDArray)
org.nd4j.linalg.factory.BlasWrapper.axpy(float, INDArray, INDArray)
org.tensorflow.framework.MemoryStats.Builder.clearDevicePersistentMemorySize()
org.tensorflow.framework.CostGraphDef.Node.Builder.clearDevicePersistentMemorySize()
org.tensorflow.framework.MemoryStats.Builder.clearDevicePersistentTensorAllocIds()
org.tensorflow.framework.MemoryStats.Builder.clearDeviceTempMemorySize()
org.tensorflow.framework.CostGraphDef.Node.Builder.clearDeviceTempMemorySize()
org.tensorflow.distruntime.RegisterGraphRequest.Builder.clearHasControlFlow()
org.tensorflow.framework.CostGraphDef.Node.Builder.clearHostTempMemorySize()
org.tensorflow.framework.GraphDef.Builder.clearVersion()
org.nd4j.autodiff.samediff.SameDiff.constant(SDVariable, long...)
org.nd4j.autodiff.samediff.SameDiff.constant(String, SDVariable, long...)
org.nd4j.linalg.api.shape.Shape.cOrFortranOrder(int[], int[], int)
org.nd4j.evaluation.regression.RegressionEvaluation.correlationR2(int) Use RegressionEvaluation.pearsonCorrelation(int) instead. For the R2 score use RegressionEvaluation.rSquared(int).
org.nd4j.autodiff.functions.DifferentialFunctionFactory.cubeDerivative(SDVariable) Use DifferentialFunctionFactory.cubeBp(SDVariable, SDVariable)
org.nd4j.linalg.api.rng.distribution.Distribution.cumulativeProbability(double, double) As of 3.1. In 4.0, this method will be renamed probability(double x0, double x1).
org.nd4j.linalg.api.rng.distribution.impl.TruncatedNormalDistribution.cumulativeProbability(double, double) See org.apache.commons.math3.distribution.RealDistribution#cumulativeProbability(double, double)
org.nd4j.linalg.api.rng.distribution.impl.OrthogonalDistribution.cumulativeProbability(double, double) See org.apache.commons.math3.distribution.RealDistribution#cumulativeProbability(double, double)
org.nd4j.linalg.api.rng.distribution.impl.NormalDistribution.cumulativeProbability(double, double) See org.apache.commons.math3.distribution.RealDistribution#cumulativeProbability(double, double)
org.nd4j.linalg.api.rng.distribution.impl.LogNormalDistribution.cumulativeProbability(double, double) See org.apache.commons.math3.distribution.RealDistribution#cumulativeProbability(double, double)
org.nd4j.linalg.api.rng.distribution.impl.ConstantDistribution.cumulativeProbability(double, double) See org.apache.commons.math3.distribution.RealDistribution#cumulativeProbability(double, double)
org.nd4j.linalg.dataset.api.DataSet.dataSetBatches(int) prefer DataSet.batchBy(int)
org.nd4j.evaluation.IEvaluation.evalTimeSeries(INDArray, INDArray) Use IEvaluation.eval(INDArray, INDArray)
org.nd4j.evaluation.IEvaluation.evalTimeSeries(INDArray, INDArray, INDArray) Use IEvaluation.eval(INDArray, INDArray, INDArray)
org.nd4j.autodiff.samediff.SameDiff.exec(Map<String, INDArray>, List<String>) See SameDiff.output(Map, List) and SameDiff.batchOutput()
org.nd4j.autodiff.samediff.SameDiff.exec(Map<String, INDArray>, String...) See SameDiff.output(Map, String...) and SameDiff.batchOutput()
org.nd4j.autodiff.samediff.SameDiff.execAll(Map<String, INDArray>) See SameDiff.outputAll(Map) and SameDiff.batchOutput()
org.nd4j.autodiff.samediff.SameDiff.execAndEndResult()
org.nd4j.autodiff.samediff.SameDiff.execSingle(Map<String, INDArray>, String) See SameDiff.outputSingle(Map, String) and SameDiff.batchOutput()
org.nd4j.linalg.factory.BlasWrapper.gemm(double, INDArray, INDArray, double, INDArray)
org.nd4j.linalg.factory.BlasWrapper.gemm(float, INDArray, INDArray, float, INDArray)
org.nd4j.linalg.factory.BlasWrapper.gemv(double, INDArray, INDArray, double, INDArray)
org.nd4j.linalg.factory.BlasWrapper.gemv(float, INDArray, INDArray, float, INDArray)
org.nd4j.linalg.factory.BlasWrapper.ger(double, INDArray, INDArray, INDArray)
org.tensorflow.framework.NodeDefOrBuilder.getAttr()
org.tensorflow.framework.NodeDef.getAttr()
org.tensorflow.framework.NodeDef.Builder.getAttr()
org.tensorflow.framework.NameAttrListOrBuilder.getAttr()
org.tensorflow.framework.NameAttrList.getAttr()
org.tensorflow.framework.NameAttrList.Builder.getAttr()
org.tensorflow.framework.FunctionDefOrBuilder.getAttr()
org.tensorflow.framework.FunctionDef.getAttr()
org.tensorflow.framework.FunctionDef.Builder.getAttr()
tensorflow.eager.EagerServiceOuterClass.OperationOrBuilder.getAttrs()
tensorflow.eager.EagerServiceOuterClass.Operation.getAttrs()
tensorflow.eager.EagerServiceOuterClass.Operation.Builder.getAttrs()
org.tensorflow.framework.MetaGraphDefOrBuilder.getCollectionDef()
org.tensorflow.framework.MetaGraphDef.getCollectionDef()
org.tensorflow.framework.MetaGraphDef.Builder.getCollectionDef()
org.nd4j.linalg.dataset.DataSet.getColumnNames()
org.tensorflow.framework.ConfigProtoOrBuilder.getDeviceCount()
org.tensorflow.framework.ConfigProto.getDeviceCount()
org.tensorflow.framework.ConfigProto.Builder.getDeviceCount()
org.tensorflow.framework.MemoryStatsOrBuilder.getDevicePersistentMemorySize()
org.tensorflow.framework.MemoryStats.getDevicePersistentMemorySize()
org.tensorflow.framework.MemoryStats.Builder.getDevicePersistentMemorySize()
org.tensorflow.framework.CostGraphDef.NodeOrBuilder.getDevicePersistentMemorySize()
org.tensorflow.framework.CostGraphDef.Node.getDevicePersistentMemorySize()
org.tensorflow.framework.CostGraphDef.Node.Builder.getDevicePersistentMemorySize()
org.tensorflow.framework.MemoryStatsOrBuilder.getDevicePersistentTensorAllocIds(int)
org.tensorflow.framework.MemoryStats.getDevicePersistentTensorAllocIds(int)
org.tensorflow.framework.MemoryStats.Builder.getDevicePersistentTensorAllocIds(int)
org.tensorflow.framework.MemoryStatsOrBuilder.getDevicePersistentTensorAllocIdsCount()
org.tensorflow.framework.MemoryStats.getDevicePersistentTensorAllocIdsCount()
org.tensorflow.framework.MemoryStats.Builder.getDevicePersistentTensorAllocIdsCount()
org.tensorflow.framework.MemoryStatsOrBuilder.getDevicePersistentTensorAllocIdsList()
org.tensorflow.framework.MemoryStats.getDevicePersistentTensorAllocIdsList()
org.tensorflow.framework.MemoryStats.Builder.getDevicePersistentTensorAllocIdsList()
org.tensorflow.framework.MemoryStatsOrBuilder.getDeviceTempMemorySize()
org.tensorflow.framework.MemoryStats.getDeviceTempMemorySize()
org.tensorflow.framework.MemoryStats.Builder.getDeviceTempMemorySize()
org.tensorflow.framework.CostGraphDef.NodeOrBuilder.getDeviceTempMemorySize()
org.tensorflow.framework.CostGraphDef.Node.getDeviceTempMemorySize()
org.tensorflow.framework.CostGraphDef.Node.Builder.getDeviceTempMemorySize()
tensorflow.DevicePropertiesProtos.DevicePropertiesOrBuilder.getEnvironment()
tensorflow.DevicePropertiesProtos.DeviceProperties.getEnvironment()
tensorflow.DevicePropertiesProtos.DeviceProperties.Builder.getEnvironment()
org.tensorflow.framework.ValuesDefOrBuilder.getExternalValues()
org.tensorflow.framework.ValuesDef.getExternalValues()
org.tensorflow.framework.ValuesDef.Builder.getExternalValues()
org.tensorflow.distruntime.RegisterGraphRequestOrBuilder.getHasControlFlow()
org.tensorflow.distruntime.RegisterGraphRequest.getHasControlFlow()
org.tensorflow.distruntime.RegisterGraphRequest.Builder.getHasControlFlow()
org.tensorflow.framework.CostGraphDef.NodeOrBuilder.getHostTempMemorySize()
org.tensorflow.framework.CostGraphDef.Node.getHostTempMemorySize()
org.tensorflow.framework.CostGraphDef.Node.Builder.getHostTempMemorySize()
org.tensorflow.framework.SignatureDefOrBuilder.getInputs()
org.tensorflow.framework.SignatureDef.getInputs()
org.tensorflow.framework.SignatureDef.Builder.getInputs()
org.nd4j.linalg.dataset.api.DataSet.getLabelNames()
org.nd4j.linalg.dataset.DataSet.getLabelNames()
org.tensorflow.framework.NodeDef.Builder.getMutableAttr()
org.tensorflow.framework.NameAttrList.Builder.getMutableAttr()
org.tensorflow.framework.FunctionDef.Builder.getMutableAttr()
tensorflow.eager.EagerServiceOuterClass.Operation.Builder.getMutableAttrs()
org.tensorflow.framework.MetaGraphDef.Builder.getMutableCollectionDef()
org.tensorflow.framework.ConfigProto.Builder.getMutableDeviceCount()
tensorflow.DevicePropertiesProtos.DeviceProperties.Builder.getMutableEnvironment()
org.tensorflow.framework.ValuesDef.Builder.getMutableExternalValues()
org.tensorflow.framework.SignatureDef.Builder.getMutableInputs()
org.tensorflow.framework.SignatureDef.Builder.getMutableOutputs()
org.tensorflow.framework.RewriterConfig.CustomGraphOptimizer.Builder.getMutableParameterMap()
org.tensorflow.framework.FunctionDef.Builder.getMutableRet()
org.tensorflow.framework.MetaGraphDef.Builder.getMutableSignatureDef()
org.tensorflow.distruntime.JobDef.Builder.getMutableTasks()
org.nd4j.autodiff.samediff.SameDiff.getOriginalShapeForPlaceHolder(String)
org.tensorflow.framework.SignatureDefOrBuilder.getOutputs()
org.tensorflow.framework.SignatureDef.getOutputs()
org.tensorflow.framework.SignatureDef.Builder.getOutputs()
org.tensorflow.framework.RewriterConfig.CustomGraphOptimizerOrBuilder.getParameterMap()
org.tensorflow.framework.RewriterConfig.CustomGraphOptimizer.getParameterMap()
org.tensorflow.framework.RewriterConfig.CustomGraphOptimizer.Builder.getParameterMap()
org.nd4j.linalg.api.ops.executioner.OpExecutioner.getProfilingMode()
org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.getProfilingMode()
org.tensorflow.framework.FunctionDefOrBuilder.getRet()
org.tensorflow.framework.FunctionDef.getRet()
org.tensorflow.framework.FunctionDef.Builder.getRet()
org.tensorflow.framework.MetaGraphDefOrBuilder.getSignatureDef()
org.tensorflow.framework.MetaGraphDef.getSignatureDef()
org.tensorflow.framework.MetaGraphDef.Builder.getSignatureDef()
org.tensorflow.distruntime.JobDefOrBuilder.getTasks()
org.tensorflow.distruntime.JobDef.getTasks()
org.tensorflow.distruntime.JobDef.Builder.getTasks()
org.tensorflow.framework.GraphDefOrBuilder.getVersion()
org.tensorflow.framework.GraphDef.getVersion()
org.tensorflow.framework.GraphDef.Builder.getVersion()
org.nd4j.autodiff.functions.DifferentialFunctionFactory.hardTanhDerivative(SDVariable) Use DifferentialFunctionFactory.hardTanhBp(SDVariable, SDVariable)
org.nd4j.autodiff.samediff.SameDiff.ifStatement(SameDiffConditional, SameDiffFunctionDefinition, SameDiffFunctionDefinition, SameDiffFunctionDefinition, SDVariable[]) Use SDBaseOps.ifCond(String, String, SameDiffNoArgSingleLambda, SameDiffNoArgSingleLambda, SameDiffNoArgSingleLambda)
org.nd4j.autodiff.samediff.SameDiff.invoke(Op, SDVariable, SDVariable)
org.nd4j.linalg.api.ops.ReduceOp.isComplexAccumulation()
org.nd4j.linalg.api.rng.distribution.Distribution.isSupportLowerBoundInclusive() to be removed in 4.0
org.nd4j.linalg.api.rng.distribution.Distribution.isSupportUpperBoundInclusive() to be removed in 4.0
org.nd4j.linalg.api.ndarray.BaseNDArray.isValid()
org.nd4j.linalg.dataset.api.DataSet.iterateWithMiniBatches()
org.nd4j.autodiff.functions.DifferentialFunctionFactory.leakyReluDerivative(SDVariable, double) Use DifferentialFunctionFactory.leakyReluBp(SDVariable, SDVariable, double)
org.nd4j.linalg.api.ndarray.BaseNDArray.linearIndex(long)
org.nd4j.linalg.dataset.api.DataSetUtil.mergePerOutputMasks2d(long[], INDArray[], INDArray[]) USe DataSetUtil.mergeMasks2d(long[], INDArray[], INDArray[])
org.nd4j.linalg.dataset.api.DataSet.normalizeZeroMeanZeroUnitVariance() Use NormalizerStandardize
org.nd4j.linalg.dataset.DataSet.normalizeZeroMeanZeroUnitVariance()
org.nd4j.linalg.api.shape.Shape.offset(DataBuffer)
org.nd4j.linalg.api.shape.Shape.offset(int[])
org.nd4j.linalg.api.shape.Shape.offset(IntBuffer)
org.nd4j.linalg.api.shape.Shape.offset(long[])
org.nd4j.linalg.api.shape.Shape.offset(LongBuffer)
org.nd4j.autodiff.samediff.internal.AbstractSession.output(List<String>, Map<String, T>, MultiDataSet, Collection<String>, boolean, At) Use AbstractSession.output(List, Map, MultiDataSet, Collection, List, At).
org.nd4j.linalg.convolution.Convolution.outSize(int, int, int, int, int, boolean)
org.nd4j.linalg.profiler.OpProfiler.processBlasCall(String)
org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.profilingHookIn(CustomOp)
org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.profilingHookIn(Op, DataBuffer...)
org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.profilingHookOut(CustomOp, long)
org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.profilingHookOut(Op, long)
org.nd4j.autodiff.samediff.SameDiff.putOrUpdateShapeForVarName(String, long[], boolean)
org.nd4j.autodiff.samediff.SameDiff.putShapeForVarName(String, long[])
org.nd4j.linalg.factory.Nd4j.rand(DataType, char, int...) use Nd4j.rand(org.nd4j.linalg.api.buffer.DataType, char, long...)
org.nd4j.linalg.factory.Nd4j.rand(DataType, int[], char) use {@link Nd4j#rand(org.nd4j.linalg.api.buffer.DataType, char, long...))
org.nd4j.linalg.factory.Nd4j.rand(int[], Distribution) use Nd4j.rand(org.nd4j.linalg.api.rng.distribution.Distribution, long...)
org.nd4j.linalg.factory.Nd4j.rand(int[], double, double, Random) use Nd4j.rand(double, double, org.nd4j.linalg.api.rng.Random, long...)
org.nd4j.linalg.factory.Nd4j.rand(int[], long) use Nd4j.rand(long, long...)
org.nd4j.linalg.factory.Nd4j.rand(int[], Random) use Nd4j.rand(org.nd4j.linalg.api.rng.Random, long...)
org.nd4j.linalg.factory.Nd4j.rand(long[], Distribution) use Nd4j.rand(org.nd4j.linalg.api.rng.distribution.Distribution, long...)
org.nd4j.linalg.factory.Nd4j.rand(long[], double, double, Random) use Nd4j.rand(double, double, org.nd4j.linalg.api.rng.Random, long...)
org.nd4j.linalg.factory.Nd4j.randn(int[], long) use Nd4j.randn(long, long...)
org.nd4j.linalg.factory.Nd4j.randn(int[], Random) use Nd4j.randn(org.nd4j.linalg.api.rng.Random, long...)
org.nd4j.linalg.factory.Nd4j.randn(long[], Random) use Nd4j.randn(org.nd4j.linalg.api.rng.Random, long...)
org.nd4j.autodiff.functions.DifferentialFunction.resolvePropertiesFromSameDiffBeforeExecution() Will be removed in the future. Ops should support array arguments. Should not bs used or overridden.
org.nd4j.linalg.dataset.api.preprocessor.NormalizerStandardize.save(File...) use NormalizerSerializer instead Save the current means and standard deviations to the file system
org.nd4j.linalg.dataset.api.preprocessor.NormalizerMinMaxScaler.save(File...) use instead
org.nd4j.linalg.dataset.api.preprocessor.MultiNormalizerStandardize.save(List<File>, List<File>) use MultiStandardizeSerializerStrategy instead Save the current means and standard deviations to the file system
org.nd4j.linalg.factory.BlasWrapper.saxpy(double, INDArray, INDArray)
org.nd4j.linalg.factory.BlasWrapper.saxpy(float, INDArray, INDArray)
org.nd4j.linalg.factory.BlasWrapper.scal(double, INDArray)
org.nd4j.linalg.factory.BlasWrapper.scal(float, INDArray)
org.nd4j.linalg.factory.Nd4j.scatterUpdate(ScatterUpdate.UpdateOp, INDArray, INDArray, INDArray, int...)
org.nd4j.linalg.api.ops.executioner.OpExecutioner.scatterUpdate(ScatterUpdate.UpdateOp, INDArray, INDArray, INDArray, int[])
org.nd4j.autodiff.functions.DifferentialFunctionFactory.seluDerivative(SDVariable) Use DifferentialFunctionFactory.seluBp(SDVariable, SDVariable)
org.nd4j.linalg.dataset.DataSet.setColumnNames(List<String>)
org.nd4j.linalg.factory.Nd4j.setDataType(DataType) use Nd4j.setDefaultDataTypes(DataType, DataType). Equivalent to setDefaultDataTypes(dtype, (dtype.isFPType() ? dtype : defaultFloatingPointType()))
org.tensorflow.framework.MemoryStats.Builder.setDevicePersistentMemorySize(long)
org.tensorflow.framework.CostGraphDef.Node.Builder.setDevicePersistentMemorySize(long)
org.tensorflow.framework.MemoryStats.Builder.setDevicePersistentTensorAllocIds(int, long)
org.tensorflow.framework.MemoryStats.Builder.setDeviceTempMemorySize(long)
org.tensorflow.framework.CostGraphDef.Node.Builder.setDeviceTempMemorySize(long)
org.tensorflow.distruntime.RegisterGraphRequest.Builder.setHasControlFlow(boolean)
org.tensorflow.framework.CostGraphDef.Node.Builder.setHostTempMemorySize(long)
org.nd4j.linalg.api.shape.Shape.setOrder(IntBuffer, char)
org.nd4j.linalg.api.ops.executioner.OpExecutioner.setProfilingMode(OpExecutioner.ProfilingMode)
org.nd4j.linalg.api.ops.executioner.DefaultOpExecutioner.setProfilingMode(OpExecutioner.ProfilingMode)
org.tensorflow.framework.GraphDef.Builder.setVersion(int)
org.nd4j.linalg.factory.Nd4j.sizeOfDataType() Use DataType.width()
org.nd4j.autodiff.functions.DifferentialFunctionFactory.softsignDerivative(SDVariable) Use DifferentialFunctionFactory.softsignBp(SDVariable, SDVariable)
org.nd4j.linalg.factory.BlasWrapper.syevr(char, char, char, INDArray, double, double, int, int, double, INDArray, INDArray, int[])
org.nd4j.linalg.factory.BlasWrapper.syevr(char, char, char, INDArray, float, float, int, int, float, INDArray, INDArray, int[])
org.nd4j.linalg.dataset.api.DataSetUtil.tailor3d2d(DataSet, boolean)
org.nd4j.autodiff.functions.DifferentialFunctionFactory.tanhRationalDerivative(SDVariable)
org.nd4j.autodiff.functions.DifferentialFunctionFactory.tanhRectifiedDerivative(SDVariable)
onnx.OnnxOperators.OperatorProto.OperatorStatus.valueOf(int) Use OnnxOperators.OperatorProto.OperatorStatus.forNumber(int) instead.
onnx.OnnxMl.Version.valueOf(int) Use OnnxMl.Version.forNumber(int) instead.
onnx.OnnxMl.AttributeProto.AttributeType.valueOf(int) Use OnnxMl.AttributeProto.AttributeType.forNumber(int) instead.
onnx.OnnxMl.TensorProto.DataType.valueOf(int) Use OnnxMl.TensorProto.DataType.forNumber(int) instead.
onnx.OnnxMl.TensorShapeProto.Dimension.ValueCase.valueOf(int) Use OnnxMl.TensorShapeProto.Dimension.ValueCase.forNumber(int) instead.
onnx.OnnxMl.TypeProto.ValueCase.valueOf(int) Use OnnxMl.TypeProto.ValueCase.forNumber(int) instead.
onnx.Onnx.Version.valueOf(int) Use Onnx.Version.forNumber(int) instead.
onnx.Onnx.AttributeProto.AttributeType.valueOf(int) Use Onnx.AttributeProto.AttributeType.forNumber(int) instead.
onnx.Onnx.TensorProto.DataType.valueOf(int) Use Onnx.TensorProto.DataType.forNumber(int) instead.
onnx.Onnx.TensorShapeProto.Dimension.ValueCase.valueOf(int) Use Onnx.TensorShapeProto.Dimension.ValueCase.forNumber(int) instead.
onnx.Onnx.TypeProto.ValueCase.valueOf(int) Use Onnx.TypeProto.ValueCase.forNumber(int) instead.
org.tensorflow.framework.TensorSliceProto.Extent.HasLengthCase.valueOf(int) Use TensorSliceProto.Extent.HasLengthCase.forNumber(int) instead.
org.tensorflow.framework.TensorInfo.EncodingCase.valueOf(int) Use TensorInfo.EncodingCase.forNumber(int) instead.
org.tensorflow.framework.Summary.Value.ValueCase.valueOf(int) Use Summary.Value.ValueCase.forNumber(int) instead.
org.tensorflow.framework.RunOptions.TraceLevel.valueOf(int) Use RunOptions.TraceLevel.forNumber(int) instead.
org.tensorflow.framework.RewriterConfig.Toggle.valueOf(int) Use RewriterConfig.Toggle.forNumber(int) instead.
org.tensorflow.framework.RewriterConfig.NumIterationsType.valueOf(int) Use RewriterConfig.NumIterationsType.forNumber(int) instead.
org.tensorflow.framework.RewriterConfig.MemOptType.valueOf(int) Use RewriterConfig.MemOptType.forNumber(int) instead.
org.tensorflow.framework.OptimizerOptions.Level.valueOf(int) Use OptimizerOptions.Level.forNumber(int) instead.
org.tensorflow.framework.OptimizerOptions.GlobalJitLevel.valueOf(int) Use OptimizerOptions.GlobalJitLevel.forNumber(int) instead.
org.tensorflow.framework.GraphTransferInfo.Destination.valueOf(int) Use GraphTransferInfo.Destination.forNumber(int) instead.
org.tensorflow.framework.DataType.valueOf(int) Use DataType.forNumber(int) instead.
org.tensorflow.framework.ControlFlowContextDef.CtxtCase.valueOf(int) Use ControlFlowContextDef.CtxtCase.forNumber(int) instead.
org.tensorflow.framework.CollectionDef.KindCase.valueOf(int) Use CollectionDef.KindCase.forNumber(int) instead.
org.tensorflow.framework.Code.valueOf(int) Use Code.forNumber(int) instead.
org.tensorflow.framework.AttrValue.ValueCase.valueOf(int) Use AttrValue.ValueCase.forNumber(int) instead.
org.tensorflow.framework.ApiDef.Visibility.valueOf(int) Use ApiDef.Visibility.forNumber(int) instead.
org.tensorflow.util.SaverDef.CheckpointFormatVersion.valueOf(int) Use SaverDef.CheckpointFormatVersion.forNumber(int) instead.
org.tensorflow.util.BundleHeaderProto.Endianness.valueOf(int) Use BundleHeaderProto.Endianness.forNumber(int) instead.
tensorflow.eager.EagerServiceOuterClass.QueueItem.ItemCase.valueOf(int) Use EagerServiceOuterClass.QueueItem.ItemCase.forNumber(int) instead.
org.nd4j.autodiff.samediff.SameDiff.whileStatement(SameDiffConditional, SameDiffFunctionDefinition, SameDiffFunctionDefinition, SDVariable[]) Use SDBaseOps.whileLoop(String[], String, SDVariable[], SameDiffSingleLambda, SameDiffLambda)
org.nd4j.linalg.factory.Nd4j.writeTxt(INDArray, String, int) Defaults to scientific notation with 18 digits after the decimal Use Nd4j.writeTxt(INDArray, String)
org.nd4j.linalg.factory.Nd4j.writeTxt(INDArray, String, String) custom col and higher dimension separators are no longer supported; uses "," Use Nd4j.writeTxt(INDArray, String)
org.nd4j.linalg.factory.Nd4j.writeTxt(INDArray, String, String, int) Precision is no longer used. Split is no longer used. Defaults to scientific notation with 18 digits after the decimal Use Nd4j.writeTxt(INDArray, String)

Deprecated Enum Constants

Enum Constant and Description
org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction.CUSTOM
org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction.EXPLL
org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction.RMSE_XENT