## Uses of Class
org.apache.sysds.common.Types.ValueType

- Packages that use Types.ValueType
  Package | Description
  --- | ---
  org.apache.sysds.api.jmlc |
  org.apache.sysds.api.mlcontext |
  org.apache.sysds.common |
  org.apache.sysds.hops |
  org.apache.sysds.hops.codegen |
  org.apache.sysds.hops.rewrite |
  org.apache.sysds.lops |
  org.apache.sysds.parser |
  org.apache.sysds.runtime.controlprogram |
  org.apache.sysds.runtime.controlprogram.caching |
  org.apache.sysds.runtime.controlprogram.context |
  org.apache.sysds.runtime.data |
  org.apache.sysds.runtime.instructions |
  org.apache.sysds.runtime.instructions.cp |
  org.apache.sysds.runtime.instructions.spark.data |
  org.apache.sysds.runtime.instructions.spark.utils |
  org.apache.sysds.runtime.io |
  org.apache.sysds.runtime.matrix.data |
  org.apache.sysds.runtime.transform.decode |
  org.apache.sysds.runtime.transform.encode |
  org.apache.sysds.runtime.transform.tokenize |
  org.apache.sysds.runtime.util |

- - ### Uses of Types.ValueType in org.apache.sysds.api.jmlc

    Method parameters in org.apache.sysds.api.jmlc with type arguments of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `void` | PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema)` Binds a frame object to a registered input variable.
    `void` | PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema, boolean reuse)` Binds a frame object to a registered input variable.
    `void` | PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema, List<String> colnames)` Binds a frame object to a registered input variable.
    `void` | PreparedScript.`setFrame(String varname, String[][] frame, List<Types.ValueType> schema, List<String> colnames, boolean reuse)` Binds a frame object to a registered input variable.

  - ### Uses of Types.ValueType in org.apache.sysds.api.mlcontext

    Methods in org.apache.sysds.api.mlcontext that return types with arguments of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `List<Types.ValueType>` | FrameSchema.`getSchema()` Obtain the frame schema

    Method parameters in org.apache.sysds.api.mlcontext with type arguments of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `void` | FrameSchema.`setSchema(List<Types.ValueType> schema)` Set the frame schema

    Constructor parameters in org.apache.sysds.api.mlcontext with type arguments of type Types.ValueType
    Constructor and Description
    `FrameSchema(List<Types.ValueType> schema)` Constructor that specifies the schema as a list of `ValueType` values.

  - ### Uses of Types.ValueType in org.apache.sysds.common

    Methods in org.apache.sysds.common that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static Types.ValueType` | Types.ValueType.`fromExternalString(String value)`
    `static Types.ValueType` | Types.ValueType.`valueOf(String name)` Returns the enum constant of this type with the specified name.
    `static Types.ValueType[]` | Types.ValueType.`values()` Returns an array containing the constants of this enum type, in the order they are declared.

  - ### Uses of Types.ValueType in org.apache.sysds.hops

    Methods in org.apache.sysds.hops that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType` | Hop.`getValueType()`

    Methods in org.apache.sysds.hops with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static Lop` | BinaryOp.`constructSPAppendLop(Hop left, Hop right, Types.DataType dt, Types.ValueType vt, boolean cbind, Hop current)`
    `static boolean` | OptimizerUtils.`isValidCPDimensions(Types.ValueType[] schema, String[] names)` Returns false if schema and names are not properly specified; other true Length to be > 0, and length of both to be equal.
    `void` | Hop.`setValueType(Types.ValueType vt)`

    Constructors in org.apache.sysds.hops with parameters of type Types.ValueType
    Constructor and Description
    `AggBinaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp2 innOp, Types.AggOp outOp, Hop in1, Hop in2)`
    `AggUnaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.AggOp o, Types.Direction idx, Hop inp)`
    `BinaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp2 o, Hop inp1, Hop inp2)`
    `DataOp(String l, Types.DataType dt, Types.ValueType vt, Hop in, Types.OpOpData dop, String fname)`
    `DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, HashMap<String,Hop> params)` READ operation for Matrix / SQL operation for tensor This constructor supports expressions in parameters
    `DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, Hop in, HashMap<String,Hop> inputParameters)` WRITE operation for Matrix This constructor supports expression in parameters
    `DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, String fname, long dim1, long dim2, long nnz, int blen)` READ operation for Matrix w/ dim1, dim2.
    `DataOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpData dop, String fname, long dim1, long dim2, long nnz, MatrixObject.UpdateType update, int blen)`
    `DnnOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOpDnn o, ArrayList<Hop> inp)` Create a hop from the builtin expression
    `Hop(String l, Types.DataType dt, Types.ValueType vt)`
    `IndexingOp(String l, Types.DataType dt, Types.ValueType vt, Hop inpMatrix, Hop inpRowL, Hop inpRowU, Hop inpColL, Hop inpColU, boolean passedRowsLEU, boolean passedColsLEU)`
    `LeftIndexingOp(String l, Types.DataType dt, Types.ValueType vt, Hop inpMatrixLeft, Hop inpMatrixRight, Hop inpRowL, Hop inpRowU, Hop inpColL, Hop inpColU, boolean passedRowsLEU, boolean passedColsLEU)`
    `MultiThreadedHop(String name, Types.DataType dt, Types.ValueType vt)`
    `NaryOp(String name, Types.DataType dataType, Types.ValueType valueType, Types.OpOpN op, Hop... inputs)` NaryOp constructor.
    `ParameterizedBuiltinOp(String l, Types.DataType dt, Types.ValueType vt, Types.ParamBuiltinOp op, LinkedHashMap<String,Hop> inputParameters)` Creates a new HOP for a function call
    `QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV)`
    `QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV, boolean flag1, boolean flag2)` Constructor for wsigmoid.
    `QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inW, Hop inU, Hop inV, boolean umult, Types.OpOp1 uop, Types.OpOp2 sop)`
    `QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV, Hop inW, boolean post)` Constructor for wsloss.
    `QuaternaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp4 o, Hop inX, Hop inU, Hop inV, Hop inW, int baseType, boolean flag1, boolean flag2)`
    `ReorgOp(String l, Types.DataType dt, Types.ValueType vt, Types.ReOrgOp o, ArrayList<Hop> inp)`
    `ReorgOp(String l, Types.DataType dt, Types.ValueType vt, Types.ReOrgOp o, Hop inp)`
    `TernaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp3 o, Hop inp1, Hop inp2, Hop inp3)`
    `TernaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp3 o, Hop inp1, Hop inp2, Hop inp3, Hop inp4, Hop inp5, Hop inp6)`
    `UnaryOp(String l, Types.DataType dt, Types.ValueType vt, Types.OpOp1 o, Hop inp)`

  - ### Uses of Types.ValueType in org.apache.sysds.hops.codegen

    Constructors in org.apache.sysds.hops.codegen with parameters of type Types.ValueType
    Constructor and Description
    `SpoofFusedOp(String name, Types.DataType dt, Types.ValueType vt, Class<?> cla, SpoofCompiler.GeneratorAPI api, String genVarName, boolean dist, SpoofFusedOp.SpoofOutputDimsType type)`

  - ### Uses of Types.ValueType in org.apache.sysds.hops.rewrite

    Methods in org.apache.sysds.hops.rewrite with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static Hop` | HopRewriteUtils.`createDataGenOpByVal(Hop rowInput, Hop colInput, Hop dimsInput, Types.DataType dt, Types.ValueType vt, double value)`

  - ### Uses of Types.ValueType in org.apache.sysds.lops

    Methods in org.apache.sysds.lops that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType` | Lop.`getValueType()` get value type of the output that is produced by this lop

    Methods in org.apache.sysds.lops with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static SortKeys` | SortKeys.`constructSortByValueLop(Lop input1, Lop input2, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `static SortKeys` | SortKeys.`constructSortByValueLop(Lop input1, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `static Data` | Data.`createLiteralLop(Types.ValueType vt, String literalValue)` Method to create literal LOPs.
    `void` | AppendG.`init(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `void` | AppendGAlignedSP.`init(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt)`
    `void` | Append.`init(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt)`
    `void` | AppendM.`init(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `void` | AppendR.`init(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `String` | Lop.`prepOperand(String label, Types.DataType dt, Types.ValueType vt)` Method to prepare instruction operand with given parameters.
    `String` | Lop.`prepOperand(String label, Types.DataType dt, Types.ValueType vt, boolean literal)` Method to prepare instruction operand with given parameters.
    `void` | Lop.`setValueType(Types.ValueType vt)` set value type of the output that is produced by this lop

    Constructors in org.apache.sysds.lops with parameters of type Types.ValueType
    Constructor and Description
    `Append(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, boolean cbind, Types.ExecType et)`
    `AppendG(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, boolean cbind, Types.ExecType et)`
    `AppendGAlignedSP(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, boolean cbind)`
    `AppendM(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, boolean cbind, boolean partitioned, Types.ExecType et)`
    `AppendR(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean cbind, Types.ExecType et)`
    `Binary(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to perform a binary operation.
    `Binary(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `BinaryM(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean colVector)` Constructor to perform a binary operation.
    `BinaryScalar(Lop input1, Lop input2, Types.OpOp2 op, Types.DataType dt, Types.ValueType vt)` Constructor to perform a scalar operation
    `BinaryUAggChain(Lop input1, Types.OpOp2 bop, Types.AggOp uaop, Types.Direction uadir, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a map mult chain without weights
    `CentralMoment(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `CentralMoment(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `Checkpoint(Lop input, Types.DataType dt, Types.ValueType vt, String level)` TODO change string parameter storage.level to StorageLevel as soon as we can assume that Spark libraries are always available.
    `Compression(Lop input, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `CoVariance(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `CoVariance(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `CoVariance(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `CSVReBlock(Lop input, int blen, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `Ctable(Lop[] inputLops, Ctable.OperationTypes op, Types.DataType dt, Types.ValueType vt, boolean ignoreZeros, boolean outputEmptyBlocks, Types.ExecType et)`
    `Ctable(Lop[] inputLops, Ctable.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `CumulativeOffsetBinary(Lop data, Lop offsets, Types.DataType dt, Types.ValueType vt, double init, boolean broadcast, Types.AggOp op, Types.ExecType et)`
    `CumulativeOffsetBinary(Lop data, Lop offsets, Types.DataType dt, Types.ValueType vt, Types.AggOp op, Types.ExecType et)`
    `CumulativePartialAggregate(Lop input, Types.DataType dt, Types.ValueType vt, Types.AggOp op, Types.ExecType et)`
    `Data(Types.OpOpData op, Lop input, HashMap<String,Lop> inputParametersLops, String name, String literal, Types.DataType dt, Types.ValueType vt, Types.FileFormat fmt)` Constructor to setup read or write LOP In case of write: `input` must be provided.
    `DataGen(Types.OpOpDG op, DataIdentifier id, HashMap<String,Lop> inputParametersLops, String baseDir, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Creates a new Rand-LOP.
    `DeCompression(Lop input, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `DnnTransform(Lop input1, Lop input2, Lop input3, Types.OpOpDnn op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `DnnTransform(Lop input1, Lop input2, Types.OpOpDnn op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `DnnTransform(Lop input, Types.OpOpDnn op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k, double intermediateMemBudget)` Constructor when we have one input.
    `Federated(HashMap<String,Lop> inputLops, Types.DataType dataType, Types.ValueType valueType)`
    `GroupedAggregate(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `GroupedAggregate(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean broadcastGroups)`
    `GroupedAggregate(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `GroupedAggregateM(HashMap<String,Lop> inputParameterLops, Types.DataType dt, Types.ValueType vt, boolean partitioned, Types.ExecType et)`
    `LeftIndex(Lop lhsInput, Lop rhsInput, Lop rowL, Lop rowU, Lop colL, Lop colU, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `LeftIndex(Lop lhsInput, Lop rhsInput, Lop rowL, Lop rowU, Lop colL, Lop colU, Types.DataType dt, Types.ValueType vt, Types.ExecType et, LeftIndex.LixCacheType type)`
    `Lop(Lop.Type t, Types.DataType dt, Types.ValueType vt)` Constructor to be invoked by base class.
    `MapMult(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean rightCache, boolean partitioned, boolean emptyBlocks, AggBinaryOp.SparkAggType aggtype)` Constructor to setup a partial Matrix-Vector Multiplication for Spark
    `MapMultChain(Lop input1, Lop input2, Lop input3, MapMultChain.ChainType chain, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a map mult chain with weights
    `MapMultChain(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a map mult chain without weights
    `MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean isLeftTransposed, boolean isRightTransposed)`
    `MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `MatMultCP(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k, boolean isLeftTransposed, boolean isRightTransposed)`
    `MMCJ(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean outputEmptyBlocks, AggBinaryOp.SparkAggType aggtype, Types.ExecType et)`
    `MMCJ(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, MMCJ.MMCJType type, Types.ExecType et)` Constructor to perform a cross product operation.
    `MMRJ(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to perform a cross product operation.
    `MMTSJ(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et, MMTSJ.MMTSJType type)`
    `MMTSJ(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et, MMTSJ.MMTSJType type, boolean multiPass)`
    `MMTSJ(Lop input1, Types.DataType dt, Types.ValueType vt, Types.ExecType et, MMTSJ.MMTSJType type, boolean multiPass, int k)`
    `MMZip(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, boolean tRewrite, Types.ExecType et)`
    `Nary(Types.OpOpN operationType, Types.DataType dt, Types.ValueType vt, Lop[] inputLops, Types.ExecType et)`
    `ParameterizedBuiltin(HashMap<String,Lop> paramLops, Types.ParamBuiltinOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `ParameterizedBuiltin(HashMap<String,Lop> paramLops, Types.ParamBuiltinOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bRmEmptyBC)`
    `ParameterizedBuiltin(HashMap<String,Lop> paramLops, Types.ParamBuiltinOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `PartialAggregate(Lop input, Types.AggOp op, Types.Direction direct, Types.DataType dt, Types.ValueType vt, AggBinaryOp.SparkAggType aggtype, Types.ExecType et)`
    `PartialAggregate(Lop input, Types.AggOp op, Types.Direction direct, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `PickByCount(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, PickByCount.OperationTypes op, Types.ExecType et)`
    `PickByCount(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt, PickByCount.OperationTypes op, Types.ExecType et, boolean inMemoryInput)`
    `PMapMult(Lop input1, Lop input2, Types.DataType dt, Types.ValueType vt)`
    `PMMJ(Lop pminput, Lop rightinput, Lop nrow, Types.DataType dt, Types.ValueType vt, boolean partitioned, boolean emptyBlocks, Types.ExecType et)` Constructor to setup a Permutation Matrix Multiplication
    `ReBlock(Lop input, int blen, Types.DataType dt, Types.ValueType vt, boolean outputEmptyBlocks, Types.ExecType et)`
    `RightIndex(Lop input, Lop rowL, Lop rowU, Lop colL, Lop colU, Lop rowDim, Lop colDim, Types.DataType dt, Types.ValueType vt, AggBinaryOp.SparkAggType aggtype, Types.ExecType et)`
    `RightIndex(Lop input, Lop rowL, Lop rowU, Lop colL, Lop colU, Lop rowDim, Lop colDim, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `RightIndex(Lop input, Lop rowL, Lop rowU, Lop colL, Lop colU, Lop rowDim, Lop colDim, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean forleft)`
    `SortKeys(Lop input, boolean desc, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `SortKeys(Lop input1, Lop input2, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `SortKeys(Lop input, SortKeys.OperationTypes op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `SpoofFused(ArrayList<Lop> inputs, Types.DataType dt, Types.ValueType vt, Class<?> cla, SpoofCompiler.GeneratorAPI api, String genVarName, int k, Types.ExecType etype)`
    `Sql(HashMap<String,Lop> inputParametersLops, Types.DataType dt, Types.ValueType vt)`
    `Ternary(Types.OpOp3 op, Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int numThreads)`
    `TernaryAggregate(Lop input1, Lop input2, Lop input3, Types.AggOp aggOp, Types.OpOp2 binOp, Types.Direction direction, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, boolean outputEmptyBlock, Types.ExecType et)`
    `Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bSortIndInMem)`
    `Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bSortIndInMem, int k)`
    `Transform(Lop[] inputs, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `Transform(Lop input, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)`
    `Transform(Lop input, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, boolean bSortIndInMem)`
    `Transform(Lop input, Types.ReOrgOp op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int k)`
    `UAggOuterChain(Lop input1, Lop input2, Types.AggOp uaop, Types.Direction uadir, Types.OpOp2 bop, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to setup a unaryagg outer chain
    `Unary(Lop input1, Lop input2, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int numThreads)` Constructor to perform a unary operation with 2 inputs
    `Unary(Lop input1, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et, int numThreads, boolean inplace)` Constructor to perform a unary operation with 1 input.
    `UnaryCP(Lop input, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt)`
    `UnaryCP(Lop input, Types.OpOp1 op, Types.DataType dt, Types.ValueType vt, Types.ExecType et)` Constructor to perform a scalar operation
    `WeightedCrossEntropy(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedCrossEntropy.WCeMMType wt, Types.ExecType et)`
    `WeightedCrossEntropyR(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedCrossEntropy.WCeMMType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
    `WeightedDivMM(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedDivMM.WDivMMType wt, Types.ExecType et)`
    `WeightedDivMMR(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedDivMM.WDivMMType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
    `WeightedSigmoid(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedSigmoid.WSigmoidType wt, Types.ExecType et)`
    `WeightedSigmoidR(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedSigmoid.WSigmoidType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
    `WeightedSquaredLoss(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedSquaredLoss.WeightsType wt, Types.ExecType et)`
    `WeightedSquaredLossR(Lop input1, Lop input2, Lop input3, Lop input4, Types.DataType dt, Types.ValueType vt, WeightedSquaredLoss.WeightsType wt, boolean cacheU, boolean cacheV, Types.ExecType et)`
    `WeightedUnaryMM(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedUnaryMM.WUMMType wt, Types.OpOp1 op, Types.ExecType et)`
    `WeightedUnaryMMR(Lop input1, Lop input2, Lop input3, Types.DataType dt, Types.ValueType vt, WeightedUnaryMM.WUMMType wt, Types.OpOp1 op, boolean cacheU, boolean cacheV, Types.ExecType et)`

  - ### Uses of Types.ValueType in org.apache.sysds.parser

    Methods in org.apache.sysds.parser that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static Types.ValueType` | Expression.`computeValueType(Expression expression1, Expression expression2, boolean cast)` Compute value type based on expressions.
    `static Types.ValueType` | Expression.`computeValueType(Expression expr1, Types.ValueType v1, Types.ValueType v2, boolean cast)`
    `static Types.ValueType` | Expression.`computeValueType(Identifier identifier1, Identifier identifier2, boolean cast)` Compute value type based on identifiers.
    `Types.ValueType` | Identifier.`getValueType()`

    Methods in org.apache.sysds.parser with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static Types.ValueType` | Expression.`computeValueType(Expression expr1, Types.ValueType v1, Types.ValueType v2, boolean cast)`
    `static Builtins` | BuiltinFunctionExpression.`getValueTypeCastOperator(Types.ValueType vt)` Convert a value type (double, int, or boolean) to a built-in function operator.
    `void` | Identifier.`setValueType(Types.ValueType vt)`

    Constructors in org.apache.sysds.parser with parameters of type Types.ValueType
    Constructor and Description
    `DataIdentifier(String name, Types.DataType dt, Types.ValueType vt)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.controlprogram

    Methods in org.apache.sysds.runtime.controlprogram with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `ScalarObject` | ProgramBlock.`executePredicate(ArrayList<Instruction> inst, Hop hops, boolean requiresRecompile, Types.ValueType retType, ExecutionContext ec)` Executes given predicate instructions (incl recompilation if required)

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.controlprogram.caching

    Methods in org.apache.sysds.runtime.controlprogram.caching that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType[]` | FrameObject.`getSchema()`
    `Types.ValueType[]` | FrameObject.`getSchema(int cl, int cu)` Obtain schema of value types
    `Types.ValueType[]` | FrameObject.`mergeSchemas(FrameObject fo)` Creates a new collection which contains the schema of the current frame object concatenated with the schema of the passed frame object.

    Methods in org.apache.sysds.runtime.controlprogram.caching with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `void` | FrameObject.`setSchema(Types.ValueType[] schema)`

    Constructors in org.apache.sysds.runtime.controlprogram.caching with parameters of type Types.ValueType
    Constructor and Description
    `FrameObject(String fname, MetaData meta, Types.ValueType[] schema)`
    `MatrixObject(Types.ValueType vt, String file)` Constructor that takes the value type and the HDFS filename.
    `MatrixObject(Types.ValueType vt, String file, MetaData mtd)` Constructor that takes the value type, HDFS filename and associated metadata.
    `MatrixObject(Types.ValueType vt, String file, MetaData mtd, MatrixBlock data)` Constructor that takes the value type, HDFS filename and associated metadata and a MatrixBlock used for creation after serialization
    `TensorObject(Types.ValueType vt, String fname)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.controlprogram.context

    Methods in org.apache.sysds.runtime.controlprogram.context with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `ScalarObject` | ExecutionContext.`getScalarInput(String name, Types.ValueType vt, boolean isLiteral)`
    `static FrameBlock` | SparkExecutionContext.`toFrameBlock(org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> rdd, Types.ValueType[] schema, int rlen, int clen)`
    `static FrameBlock` | SparkExecutionContext.`toFrameBlock(RDDObject rdd, Types.ValueType[] schema, int rlen, int clen)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.data

    Fields in org.apache.sysds.runtime.data declared as Types.ValueType
    Modifier and Type | Field and Description
    --- | ---
    `static Types.ValueType` | TensorBlock.`DEFAULT_VTYPE`

    Methods in org.apache.sysds.runtime.data that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType` | DataTensorBlock.`getColValueType(int col)`
    `Types.ValueType[]` | TensorBlock.`getSchema()` Get the schema if this `TensorBlock` is heterogeneous.
    `Types.ValueType[]` | DataTensorBlock.`getSchema()`
    `Types.ValueType` | TensorBlock.`getValueType()` Get the `ValueType` if this `TensorBlock` is homogeneous.
    `Types.ValueType` | BasicTensorBlock.`getValueType()`
    `static Types.ValueType` | TensorBlock.`resultValueType(Types.ValueType in1, Types.ValueType in2)`

    Methods in org.apache.sysds.runtime.data with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static DenseBlock` | DenseBlockFactory.`createDenseBlock(Types.ValueType vt, DenseBlock.Type type, int[] dims)`
    `static DenseBlock` | DenseBlockFactory.`createDenseBlock(Types.ValueType vt, int[] dims)`
    `void` | DataTensorBlock.`reset(int[] dims, Types.ValueType[] schema)`
    `static Types.ValueType` | TensorBlock.`resultValueType(Types.ValueType in1, Types.ValueType in2)`

    Constructors in org.apache.sysds.runtime.data with parameters of type Types.ValueType
    Constructor and Description
    `BasicTensorBlock(int[] dims, Types.ValueType vt, double val)`
    `BasicTensorBlock(Types.ValueType vt, int[] dims)`
    `BasicTensorBlock(Types.ValueType vt, int[] dims, boolean sp)`
    `BasicTensorBlock(Types.ValueType vt, int[] dims, boolean sp, long estnnz)`
    `DataTensorBlock(int ncols, Types.ValueType vt)`
    `DataTensorBlock(Types.ValueType[] schema)`
    `DataTensorBlock(Types.ValueType[] schema, int[] dims)`
    `DataTensorBlock(Types.ValueType[] schema, int[] dims, String[][] data)`
    `DataTensorBlock(Types.ValueType vt, int[] dims)`
    `TensorBlock(Types.ValueType[] schema, int[] dims)` Create a data `TensorBlock` with the given schema and the given dimensions.
    `TensorBlock(Types.ValueType vt, int[] dims)` Create a basic `TensorBlock` with the given `ValueType` and the given dimensions.

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.instructions

    Methods in org.apache.sysds.runtime.instructions with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static String` | InstructionUtils.`createLiteralOperand(String val, Types.ValueType vt)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.instructions.cp

    Methods in org.apache.sysds.runtime.instructions.cp that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType` | Data.`getValueType()`
    `Types.ValueType` | CPOperand.`getValueType()`

    Methods in org.apache.sysds.runtime.instructions.cp with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static LiteralOp` | ScalarObjectFactory.`createLiteralOp(Types.ValueType vt, String value)`
    `static ScalarObject` | ScalarObjectFactory.`createScalarObject(Types.ValueType vt, double value)`
    `static ScalarObject` | ScalarObjectFactory.`createScalarObject(Types.ValueType vt, LiteralOp lit)`
    `static ScalarObject` | ScalarObjectFactory.`createScalarObject(Types.ValueType vt, Object obj)`
    `static ScalarObject` | ScalarObjectFactory.`createScalarObject(Types.ValueType vt, ScalarObject so)`
    `static ScalarObject` | ScalarObjectFactory.`createScalarObject(Types.ValueType vt, String value)`

    Constructors in org.apache.sysds.runtime.instructions.cp with parameters of type Types.ValueType
    Constructor and Description
    `CPOperand(String name, Types.ValueType vt, Types.DataType dt)`
    `CPOperand(String name, Types.ValueType vt, Types.DataType dt, boolean literal)`
    `ScalarObject(Types.ValueType vt)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.instructions.spark.data

    Constructors in org.apache.sysds.runtime.instructions.spark.data with parameters of type Types.ValueType
    Constructor and Description
    `FrameReblockBuffer(int buffersize, long rlen, long clen, Types.ValueType[] schema)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.instructions.spark.utils

    Methods in org.apache.sysds.runtime.instructions.spark.utils with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>` | FrameRDDConverterUtils.`binaryBlockToDataFrame(org.apache.spark.sql.SparkSession sparkSession, org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> in, DataCharacteristics mc, Types.ValueType[] schema)`
    `static org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>` | FrameRDDConverterUtils.`binaryBlockToDataFrame(org.apache.spark.sql.SQLContext sqlContext, org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock> in, DataCharacteristics mc, Types.ValueType[] schema)` Deprecated.
    `static int` | FrameRDDConverterUtils.`convertDFSchemaToFrameSchema(org.apache.spark.sql.types.StructType dfschema, String[] colnames, Types.ValueType[] fschema, boolean containsID)` NOTE: regarding the support of vector columns, we make the following schema restriction: single vector column, which allows inference of the vector length without data access and covers the common case.
    `static org.apache.spark.sql.types.StructType` | FrameRDDConverterUtils.`convertFrameSchemaToDFSchema(Types.ValueType[] fschema, boolean containsID)` This function will convert Frame schema into DataFrame schema
    `static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` | FrameRDDConverterUtils.`csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> input, DataCharacteristics mc, Types.ValueType[] schema, boolean hasHeader, String delim, boolean fill, double fillValue, Set<String> naStrings)`
    `static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` | FrameRDDConverterUtils.`csvToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaRDD<String> input, DataCharacteristics mcOut, Types.ValueType[] schema, boolean hasHeader, String delim, boolean fill, double fillValue, Set<String> naStrings)`
    `static org.apache.spark.api.java.JavaRDD<org.apache.spark.sql.Row>` | FrameRDDConverterUtils.`csvToRowRDD(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaRDD<String> dataRdd, String delim, Types.ValueType[] schema)`
    `static org.apache.spark.api.java.JavaRDD<org.apache.spark.sql.Row>` | FrameRDDConverterUtils.`csvToRowRDD(org.apache.spark.api.java.JavaSparkContext sc, String fnameIn, String delim, Types.ValueType[] schema)`
    `static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` | FrameRDDConverterUtils.`textCellToBinaryBlock(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaPairRDD<org.apache.hadoop.io.LongWritable,org.apache.hadoop.io.Text> in, DataCharacteristics mcOut, Types.ValueType[] schema)`
    `static org.apache.spark.api.java.JavaPairRDD<Long,FrameBlock>` | FrameRDDConverterUtils.`textCellToBinaryBlockLongIndex(org.apache.spark.api.java.JavaSparkContext sc, org.apache.spark.api.java.JavaPairRDD<Long,org.apache.hadoop.io.Text> input, DataCharacteristics mc, Types.ValueType[] schema)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.io

    Methods in org.apache.sysds.runtime.io that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType[]` | FrameReader.`getDefSchema(long clen)`

    Methods in org.apache.sysds.runtime.io with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static FrameBlock[]` | FrameWriter.`createFrameBlocksForReuse(Types.ValueType[] schema, String[] names, long rlen)`
    `FrameBlock` | FrameReader.`readFrameFromHDFS(String fname, Types.ValueType[] schema, long rlen, long clen)`
    `FrameBlock` | FrameReaderJSONL.`readFrameFromHDFS(String fname, Types.ValueType[] schema, Map<String,Integer> schemaMap, long rlen, long clen)`
    `FrameBlock` | FrameReaderProto.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `abstract FrameBlock` | FrameReader.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `FrameBlock` | FrameReaderTextCell.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `FrameBlock` | FrameReaderTextCSV.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `FrameBlock` | FrameReaderBinaryBlock.`readFrameFromHDFS(String fname, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `FrameBlock` | FrameReader.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, long rlen, long clen)`
    `FrameBlock` | FrameReaderProto.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `abstract FrameBlock` | FrameReader.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `FrameBlock` | FrameReaderTextCell.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `FrameBlock` | FrameReaderTextCSV.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `FrameBlock` | FrameReaderBinaryBlock.`readFrameFromInputStream(InputStream is, Types.ValueType[] schema, String[] names, long rlen, long clen)`
    `abstract TensorBlock` | TensorReader.`readTensorFromHDFS(String fname, long[] dims, int blen, Types.ValueType[] schema)`
    `TensorBlock` | TensorReaderTextCell.`readTensorFromHDFS(String fname, long[] dims, int blen, Types.ValueType[] schema)`
    `TensorBlock` | TensorReaderBinaryBlock.`readTensorFromHDFS(String fname, long[] dims, int blen, Types.ValueType[] schema)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.matrix.data

    Methods in org.apache.sysds.runtime.matrix.data that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType[]` | FrameBlock.`getSchema()` Returns the schema of the frame block.

    Methods in org.apache.sysds.runtime.matrix.data with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Iterator<Object[]>` | FrameBlock.`getObjectRowIterator(Types.ValueType[] schema)` Get a row iterator over the frame where all fields are encoded as boxed objects according to the value types of the provided target schema.
    `void` | FrameBlock.`setSchema(Types.ValueType[] schema)` Sets the schema of the frame block.

    Constructors in org.apache.sysds.runtime.matrix.data with parameters of type Types.ValueType
    Constructor and Description
    `FrameBlock(int ncols, Types.ValueType vt)`
    `FrameBlock(Types.ValueType[] schema)`
    `FrameBlock(Types.ValueType[] schema, String[] names)`
    `FrameBlock(Types.ValueType[] schema, String[][] data)`
    `FrameBlock(Types.ValueType[] schema, String[] names, String[][] data)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.transform.decode

    Methods in org.apache.sysds.runtime.transform.decode that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType[]` | Decoder.`getSchema()`

    Methods in org.apache.sysds.runtime.transform.decode with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static Decoder` | DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta)`
    `static Decoder` | DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int clen)`
    `static Decoder` | DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int minCol, int maxCol)`
    `static Decoder` | DecoderFactory.`createDecoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int clen, int minCol, int maxCol)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.transform.encode

    Methods in org.apache.sysds.runtime.transform.encode with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static MultiColumnEncoder` | EncoderFactory.`createEncoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta)`
    `static MultiColumnEncoder` | EncoderFactory.`createEncoder(String spec, String[] colnames, Types.ValueType[] schema, FrameBlock meta, int minCol, int maxCol)`
    `static MultiColumnEncoder` | EncoderFactory.`createEncoder(String spec, String[] colnames, Types.ValueType[] schema, int clen, FrameBlock meta)`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.transform.tokenize

    Methods in org.apache.sysds.runtime.transform.tokenize that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `Types.ValueType[]` | TokenizerPostPosition.`getOutSchema()`
    `Types.ValueType[]` | TokenizerPostCount.`getOutSchema()`
    `Types.ValueType[]` | TokenizerPost.`getOutSchema()`
    `Types.ValueType[]` | TokenizerPostHash.`getOutSchema()`
    `Types.ValueType[]` | Tokenizer.`getSchema()`

  - ### Uses of Types.ValueType in org.apache.sysds.runtime.util

    Methods in org.apache.sysds.runtime.util that return Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static Types.ValueType[]` | UtilFunctions.`copyOf(Types.ValueType[] schema1, Types.ValueType[] schema2)`
    `static Types.ValueType[]` | UtilFunctions.`nCopies(int n, Types.ValueType vt)`
    `static Types.ValueType[]` | UtilFunctions.`stringToValueType(String[] schemaValues)` Generates a ValueType array from a String array

    Methods in org.apache.sysds.runtime.util with parameters of type Types.ValueType
    Modifier and Type | Method and Description
    --- | ---
    `static int` | UtilFunctions.`compareTo(Types.ValueType vt, Object in1, Object in2)`
    `static MatrixBlock` | Py4jConverterUtils.`convertPy4JArrayToMB(byte[] data, int rlen, int clen, boolean isSparse, Types.ValueType valueType)`
    `static MatrixBlock` | Py4jConverterUtils.`convertPy4JArrayToMB(byte[] data, int rlen, int clen, Types.ValueType valueType)`
    `static FrameBlock` | DataConverter.`convertToFrameBlock(MatrixBlock mb, Types.ValueType vt)` Converts a matrix block into a frame block of a given value type.
    `static FrameBlock` | DataConverter.`convertToFrameBlock(MatrixBlock mb, Types.ValueType[] schema)`
    `static FrameBlock` | DataConverter.`convertToFrameBlock(String[][] data, Types.ValueType[] schema)`
    `static FrameBlock` | DataConverter.`convertToFrameBlock(String[][] data, Types.ValueType[] schema, String[] colnames)`
    `static TensorBlock` | DataConverter.`convertToTensorBlock(MatrixBlock mb, Types.ValueType vt, boolean toBasicTensor)`
    `static Types.ValueType[]` | UtilFunctions.`copyOf(Types.ValueType[] schema1, Types.ValueType[] schema2)`
    `static Types.ValueType[]` | UtilFunctions.`copyOf(Types.ValueType[] schema1, Types.ValueType[] schema2)`
    `static Object` | UtilFunctions.`doubleToObject(Types.ValueType vt, double in)`
    `static Object` | UtilFunctions.`doubleToObject(Types.ValueType vt, double in, boolean sparse)`
    `static int` | UtilFunctions.`frequency(Types.ValueType[] schema, Types.ValueType vt)`
    `static int` | UtilFunctions.`frequency(Types.ValueType[] schema, Types.ValueType vt)`
    `static FrameBlock` | UtilFunctions.`generateRandomFrameBlock(int rows, int cols, Types.ValueType[] schema, Random random)` Generates a random FrameBlock with given parameters.
    `static Object` | UtilFunctions.`generateRandomValueFromValueType(Types.ValueType valueType, Random random)` Generates a random value for a given Value Type
    `static String` | HDFSTool.`metaDataToString(Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
    `static String` | HDFSTool.`metaDataToString(Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
    `static Types.ValueType[]` | UtilFunctions.`nCopies(int n, Types.ValueType vt)`
    `static double` | UtilFunctions.`objectToDouble(Types.ValueType vt, Object in)`
    `static Object` | UtilFunctions.`objectToObject(Types.ValueType vt, Object in)`
    `static Object` | UtilFunctions.`objectToObject(Types.ValueType vt, Object in, boolean ignoreNull)`
    `static Object` | HDFSTool.`readObjectFromHDFSFile(String filename, Types.ValueType vt)`
    `static ScalarObject` | HDFSTool.`readScalarObjectFromHDFSFile(String fname, Types.ValueType vt)`
    `static TensorBlock` | DataConverter.`readTensorFromHDFS(String dir, Types.FileFormat fmt, long[] dims, int blen, Types.ValueType[] schema)`
    `static Object` | UtilFunctions.`stringToObject(Types.ValueType vt, String in)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics mc, Types.FileFormat fmt)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, DataCharacteristics mc, Types.FileFormat fmt, PrivacyConstraint privacyConstraint)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics dc, Types.FileFormat fmt, FileFormatProperties formatProperties, PrivacyConstraint privacyConstraint)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt, PrivacyConstraint privacyConstraint)`
    `static void` | HDFSTool.`writeMetaDataFile(String mtdfile, Types.ValueType vt, Types.ValueType[] schema, Types.DataType dt, DataCharacteristics mc, Types.FileFormat fmt, PrivacyConstraint privacyConstraint)`
    `static void` | HDFSTool.`writeScalarMetaDataFile(String mtdfile, Types.ValueType vt)`
    `static void` | HDFSTool.`writeScalarMetaDataFile(String mtdfile, Types.ValueType vt, PrivacyConstraint privacyConstraint)`

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