idx int64 0 41.2k | question stringlengths 73 5.81k | target stringlengths 5 918 |
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20,000 | public void aggregate ( Aggregate op , long key ) { int deviceId = Nd4j . getAffinityManager ( ) . getDeviceForCurrentThread ( ) ; if ( opCounter . get ( ) == null ) opCounter . set ( new AtomicLong ( 0 ) ) ; aggregates . get ( deviceId ) . add ( new AggregateDescriptor ( op , key , opCounter . get ( ) . getAndIncremen... | This method enqueues aggregate op for future invocation . Key value will be used to batch individual ops |
20,001 | public static String getModuleNameFor ( Op op ) { String moduleName = null ; if ( op instanceof ReduceOp ) { moduleName = "reduce" ; if ( op . opName ( ) . equals ( "cosinesimilarity" ) ) { moduleName = "reduce3" ; } else if ( op . opName ( ) . equals ( "euclidean" ) ) { moduleName = "reduce3" ; } else if ( op . opName... | For invoking a cuda kernel this returns the module opName for the given op |
20,002 | public static int convertMPtoCores ( int ccMajor , int ccMinor , int numberOfProcessors ) { if ( ccMajor == 1 ) return 8 ; if ( ccMajor == 2 && ccMinor == 1 ) return 48 ; if ( ccMajor == 2 ) return 32 ; if ( ccMajor == 3 ) return 192 ; if ( ccMajor == 5 ) return 128 ; return - 1 ; } | Returns number of SMs based on device compute capability and number of processors . |
20,003 | public Gradient [ ] calcGradient ( IActorCritic iac , Stack < MiniTrans < Integer > > rewards ) { MiniTrans < Integer > minTrans = rewards . pop ( ) ; int size = rewards . size ( ) ; boolean recurrent = getAsyncGlobal ( ) . getCurrent ( ) . isRecurrent ( ) ; int [ ] shape = getHistoryProcessor ( ) == null ? mdp . getOb... | calc the gradients based on the n - step rewards |
20,004 | public int numChunksSoFar ( String id ) { if ( ! chunks . containsKey ( id ) ) return 0 ; return chunks . get ( id ) . size ( ) ; } | Returns the number of chunks accumulated for a given id so far |
20,005 | public boolean allPresent ( String id ) { if ( ! chunks . containsKey ( id ) ) return false ; List < NDArrayMessageChunk > chunkList = chunks . get ( id ) ; return chunkList . size ( ) == chunkList . get ( 0 ) . getNumChunks ( ) ; } | Returns true if all chunks are present |
20,006 | public NDArrayMessage reassemble ( String id ) { List < NDArrayMessageChunk > chunkList = chunks . get ( id ) ; if ( chunkList . size ( ) != chunkList . get ( 0 ) . getNumChunks ( ) ) throw new IllegalStateException ( "Unable to reassemble message chunk " + id + " missing " + ( chunkList . get ( 0 ) . getNumChunks ( ) ... | Reassemble an ndarray message from a set of chunks |
20,007 | public FeedForwardLayer getLossLayer ( InputType type ) throws UnsupportedKerasConfigurationException { if ( type instanceof InputType . InputTypeFeedForward ) { this . layer = new LossLayer . Builder ( loss ) . name ( this . layerName ) . build ( ) ; } else if ( type instanceof InputType . InputTypeRecurrent ) { this ... | Get DL4J LossLayer . |
20,008 | public void uploadForDeployment ( String from , String to ) throws Exception { File fromFile = new File ( from ) ; if ( ! to . isEmpty ( ) && fromFile . isDirectory ( ) ) mkDir ( to ) ; else upload ( from , to ) ; } | Creates the directory for the file if necessary and uploads the file |
20,009 | private void mkDir ( String dir ) throws Exception { Session session = getSession ( ) ; session . connect ( ) ; Channel channel = session . openChannel ( "sftp" ) ; channel . connect ( ) ; ChannelSftp c = ( ChannelSftp ) channel ; if ( ! fileExists ( dir , c ) ) c . mkdir ( dir ) ; c . exit ( ) ; session . disconnect (... | creates the directory to upload to |
20,010 | private void upload ( String fileOrDir , String uploadRootDir ) throws Exception { if ( uploadRootDir . isEmpty ( ) ) uploadRootDir = "." ; File origin = new File ( fileOrDir ) ; if ( fileOrDir . endsWith ( ".tar" ) || fileOrDir . endsWith ( ".tar.gz" ) ) { upload ( new File ( fileOrDir ) , uploadRootDir ) ; untar ( up... | uploads the file or listed files in a directory |
20,011 | protected void init ( ) { if ( storage . size ( ) != vocabCache . numWords ( ) ) throw new RuntimeException ( "Number of words in Vocab isn't matching number of stored Vectors. vocab: [" + vocabCache . numWords ( ) + "]; storage: [" + storage . size ( ) + "]" ) ; for ( int i = 0 ; i < Nd4j . getAffinityManager ( ) . ge... | Init method validates configuration defined using |
20,012 | public double similarity ( String label1 , String label2 ) { if ( label1 == null || label2 == null ) { log . debug ( "LABELS: " + label1 + ": " + ( label1 == null ? "null" : "exists" ) + ";" + label2 + " vec2:" + ( label2 == null ? "null" : "exists" ) ) ; return Double . NaN ; } INDArray vec1 = getWordVectorMatrix ( la... | Returns the similarity of 2 words |
20,013 | public void processMessage ( ) { CbowRequestMessage cbrm = new CbowRequestMessage ( rowsA , rowsB , w1 , codes , negSamples , alpha , 119 ) ; if ( negSamples > 0 ) { int negatives [ ] = Arrays . copyOfRange ( rowsB , codes . length , rowsB . length ) ; cbrm . setNegatives ( negatives ) ; } cbrm . setFrameId ( - 119L ) ... | This method calculates dot of gives rows with averaging applied to rowsA as required by CBoW |
20,014 | public INDArray hash ( INDArray data ) { if ( data . shape ( ) [ 1 ] != inDimension ) { throw new ND4JIllegalStateException ( String . format ( "Invalid shape: Requested INDArray shape %s, this table expects dimension %d" , Arrays . toString ( data . shape ( ) ) , inDimension ) ) ; } INDArray projected = data . mmul ( ... | Returns hash values for a particular query |
20,015 | INDArray rawBucketOf ( INDArray query ) { INDArray pattern = hash ( query ) ; INDArray res = Nd4j . zeros ( DataType . BOOL , index . shape ( ) ) ; Nd4j . getExecutioner ( ) . exec ( new BroadcastEqualTo ( index , pattern , res , - 1 ) ) ; return res . castTo ( Nd4j . defaultFloatingPointType ( ) ) . min ( - 1 ) ; } | data elements in the same bucket as the query without entropy |
20,016 | INDArray bucketData ( INDArray query ) { INDArray mask = bucket ( query ) ; int nRes = mask . sum ( 0 ) . getInt ( 0 ) ; INDArray res = Nd4j . create ( new int [ ] { nRes , inDimension } ) ; int j = 0 ; for ( int i = 0 ; i < nRes ; i ++ ) { while ( mask . getInt ( j ) == 0 && j < mask . length ( ) - 1 ) { j += 1 ; } if... | data elements in the same entropy bucket as the query |
20,017 | public static INDArray deserializeRawJson ( String serializedRawArray ) { String cleanedRawArray = serializedRawArray ; JsonArray jsonArray = JSON_PARSER . parse ( cleanedRawArray ) . getAsJsonArray ( ) ; List < Integer > dimensions = new ArrayList < > ( ) ; dimensions . add ( jsonArray . size ( ) ) ; getSizeMultiDimen... | Deserialize an ndarray form json |
20,018 | public void memcpy ( DataBuffer dstBuffer , DataBuffer srcBuffer ) { CudaContext context = ( CudaContext ) AtomicAllocator . getInstance ( ) . getDeviceContext ( ) . getContext ( ) ; if ( dstBuffer instanceof CompressedDataBuffer && ! ( srcBuffer instanceof CompressedDataBuffer ) ) { AllocationPoint srcPoint = AtomicAl... | This method provides basic memcpy functionality with respect to target environment |
20,019 | public void release ( Pointer pointer , MemoryKind kind ) { if ( kind == MemoryKind . DEVICE ) { NativeOpsHolder . getInstance ( ) . getDeviceNativeOps ( ) . freeDevice ( pointer , 0 ) ; pointer . setNull ( ) ; } else if ( kind == MemoryKind . HOST ) { NativeOpsHolder . getInstance ( ) . getDeviceNativeOps ( ) . freeHo... | This method releases previously allocated memory chunk |
20,020 | public T get ( int deviceId ) { try { locksMap . get ( deviceId ) . readLock ( ) . lock ( ) ; return backingMap . get ( deviceId ) ; } finally { locksMap . get ( deviceId ) . readLock ( ) . unlock ( ) ; } } | This method returns object local to target device |
20,021 | public void set ( int deviceId , T object ) { try { locksMap . get ( deviceId ) . writeLock ( ) . lock ( ) ; backingMap . put ( deviceId , object ) ; } finally { locksMap . get ( deviceId ) . writeLock ( ) . unlock ( ) ; } } | This method sets object for specific device |
20,022 | public void clear ( ) { int deviceId = Nd4j . getAffinityManager ( ) . getDeviceForCurrentThread ( ) ; try { locksMap . get ( deviceId ) . writeLock ( ) . lock ( ) ; backingMap . remove ( deviceId ) ; } finally { locksMap . get ( deviceId ) . writeLock ( ) . unlock ( ) ; } } | This method removes object stored for current device |
20,023 | protected void getDeviceBuffers ( CudaContext context , int deviceId ) { NativeOps nativeOps = NativeOpsHolder . getInstance ( ) . getDeviceNativeOps ( ) ; int sizeOf = 8 ; val reductionPointer = nativeOps . mallocDevice ( 16384 * sizeOf , deviceId , 0 ) ; if ( reductionPointer == null ) throw new IllegalStateException... | This method is used to allocate |
20,024 | public void updateProperties ( InputStream inputStream ) { try { conf . load ( inputStream ) ; conf . putAll ( System . getProperties ( ) ) ; } catch ( IOException e ) { log . warn ( "Error loading system properties from input stream" , e ) ; } } | Load the additional properties from an input stream and load all system properties |
20,025 | public static synchronized Map < String , OpDef > opDescs ( ) { if ( DESCRIPTORS != null ) { return DESCRIPTORS ; } try ( InputStream contents = new ClassPathResource ( "ops.proto" ) . getInputStream ( ) ; BufferedInputStream bis2 = new BufferedInputStream ( contents ) ; BufferedReader reader = new BufferedReader ( new... | Get the op descriptors for tensorflow |
20,026 | public void processMessage ( ) { VectorAggregation aggregation = new VectorAggregation ( rowIndex , ( short ) voidConfiguration . getNumberOfShards ( ) , getShardIndex ( ) , storage . getArray ( key ) . getRow ( rowIndex ) . dup ( ) ) ; aggregation . setOriginatorId ( this . getOriginatorId ( ) ) ; clipboard . pin ( ag... | This message is possible to get only as Shard |
20,027 | private BufferedImage restoreRGBImage ( INDArray tensor3D ) { INDArray arrayR = null ; INDArray arrayG = null ; INDArray arrayB = null ; if ( tensor3D . shape ( ) [ 0 ] == 3 ) { arrayR = tensor3D . tensorAlongDimension ( 2 , 2 , 1 ) ; arrayG = tensor3D . tensorAlongDimension ( 1 , 2 , 1 ) ; arrayB = tensor3D . tensorAl... | Returns RGB image out of 3D tensor |
20,028 | private BufferedImage renderImageGrayscale ( INDArray array ) { BufferedImage imageToRender = new BufferedImage ( array . columns ( ) , array . rows ( ) , BufferedImage . TYPE_BYTE_GRAY ) ; for ( int x = 0 ; x < array . columns ( ) ; x ++ ) { for ( int y = 0 ; y < array . rows ( ) ; y ++ ) { imageToRender . getRaster (... | Renders 2D INDArray into BufferedImage |
20,029 | public void append ( byte [ ] utf8 , int start , int len ) { setCapacity ( length + len , true ) ; System . arraycopy ( utf8 , start , bytes , length , len ) ; length += len ; } | Append a range of bytes to the end of the given text |
20,030 | public void write ( DataOutput out ) throws IOException { WritableUtils . writeVInt ( out , length ) ; out . write ( bytes , 0 , length ) ; } | serialize write this object to out length uses zero - compressed encoding |
20,031 | public static void validateUTF8 ( byte [ ] utf8 , int start , int len ) throws MalformedInputException { int count = start ; int leadByte = 0 ; int length = 0 ; int state = LEAD_BYTE ; while ( count < start + len ) { int aByte = ( ( int ) utf8 [ count ] & 0xFF ) ; switch ( state ) { case LEAD_BYTE : leadByte = aByte ; ... | Check to see if a byte array is valid utf - 8 |
20,032 | public static int bytesToCodePoint ( ByteBuffer bytes ) { bytes . mark ( ) ; byte b = bytes . get ( ) ; bytes . reset ( ) ; int extraBytesToRead = bytesFromUTF8 [ ( b & 0xFF ) ] ; if ( extraBytesToRead < 0 ) return - 1 ; int ch = 0 ; switch ( extraBytesToRead ) { case 5 : ch += ( bytes . get ( ) & 0xFF ) ; ch <<= 6 ; c... | Returns the next code point at the current position in the buffer . The buffer s position will be incremented . Any mark set on this buffer will be changed by this method! |
20,033 | public static int utf8Length ( String string ) { CharacterIterator iter = new StringCharacterIterator ( string ) ; char ch = iter . first ( ) ; int size = 0 ; while ( ch != CharacterIterator . DONE ) { if ( ( ch >= 0xD800 ) && ( ch < 0xDC00 ) ) { char trail = iter . next ( ) ; if ( ( trail > 0xDBFF ) && ( trail < 0xE00... | For the given string returns the number of UTF - 8 bytes required to encode the string . |
20,034 | public long getApproximateFreeMemory ( int deviceId ) { val externalAllocations = getTotalMemory ( deviceId ) - getFreeMemory ( deviceId ) ; val active = getActiveMemory ( deviceId ) ; val free = getTotalMemory ( deviceId ) - ( active + externalAllocations ) ; return free ; } | This method returns approximate free memory on specified device |
20,035 | public long getPreciseFreeMemory ( int deviceId ) { val extFree = NativeOpsHolder . getInstance ( ) . getDeviceNativeOps ( ) . getDeviceFreeMemory ( deviceId ) ; return extFree ; } | This method returns precise amount of free memory on specified device |
20,036 | public double nrm2 ( INDArray arr ) { switch ( arr . data ( ) . dataType ( ) ) { case DOUBLE : DefaultOpExecutioner . validateDataType ( DataType . DOUBLE , arr ) ; return dnrm2 ( arr . length ( ) , arr , 1 ) ; case FLOAT : DefaultOpExecutioner . validateDataType ( DataType . FLOAT , arr ) ; return snrm2 ( arr . length... | Computes the Euclidean norm of a vector . |
20,037 | public double asum ( INDArray arr ) { switch ( arr . data ( ) . dataType ( ) ) { case DOUBLE : DefaultOpExecutioner . validateDataType ( DataType . DOUBLE , arr ) ; return dasum ( arr . length ( ) , arr , 1 ) ; case FLOAT : DefaultOpExecutioner . validateDataType ( DataType . FLOAT , arr ) ; return sasum ( arr . length... | Compute the sum of magnitude of the vector elements |
20,038 | public int iamin ( INDArray arr ) { switch ( arr . data ( ) . dataType ( ) ) { case DOUBLE : DefaultOpExecutioner . validateDataType ( DataType . DOUBLE , arr ) ; return idamin ( arr . length ( ) , arr , 1 ) ; case FLOAT : DefaultOpExecutioner . validateDataType ( DataType . FLOAT , arr ) ; return isamin ( arr . length... | Find the index of the element with maximum absolute value |
20,039 | public void axpy ( long n , double alpha , INDArray x , INDArray y ) { BaseSparseNDArray sparseX = ( BaseSparseNDArray ) x ; DataBuffer pointers = sparseX . getVectorCoordinates ( ) ; switch ( x . data ( ) . dataType ( ) ) { case DOUBLE : DefaultOpExecutioner . validateDataType ( DataType . DOUBLE , x ) ; DefaultOpExec... | Adds a scalar multiple of compressed sparse vector to a full - storage vector . |
20,040 | public void scal ( long N , double alpha , INDArray X ) { switch ( X . data ( ) . dataType ( ) ) { case DOUBLE : dscal ( N , alpha , X , 1 ) ; break ; case FLOAT : sscal ( N , alpha , X , 1 ) ; break ; case HALF : hscal ( N , alpha , X , 1 ) ; break ; default : throw new UnsupportedOperationException ( ) ; } } | Computes the product of a vector by a scalar . |
20,041 | public static void createHtmlAnalysisFile ( DataAnalysis dataAnalysis , File output ) throws Exception { String str = createHtmlAnalysisString ( dataAnalysis ) ; FileUtils . writeStringToFile ( output , str , StandardCharsets . UTF_8 ) ; } | Render a data analysis object as a HTML file . This will produce a summary table along charts for numerical columns |
20,042 | public String getLabel ( String path ) { if ( labelGenerator != null ) { return labelGenerator . getLabelForPath ( path ) . toString ( ) ; } if ( fileNameMap != null && fileNameMap . containsKey ( path ) ) return fileNameMap . get ( path ) ; return ( new File ( path ) ) . getParentFile ( ) . getName ( ) ; } | Get the label from the given path |
20,043 | protected void accumulateLabel ( String path ) { String name = getLabel ( path ) ; if ( ! labels . contains ( name ) ) labels . add ( name ) ; } | Accumulate the label from the path |
20,044 | public static INDArray symmetricGeneralizedEigenvalues ( INDArray A , boolean calculateVectors ) { INDArray eigenvalues = Nd4j . create ( A . rows ( ) ) ; Nd4j . getBlasWrapper ( ) . syev ( 'V' , 'L' , ( calculateVectors ? A : A . dup ( ) ) , eigenvalues ) ; return eigenvalues ; } | Compute generalized eigenvalues of the problem A x = L x . Matrix A is modified in the process holding eigenvectors as columns after execution . |
20,045 | public static INDArray symmetricGeneralizedEigenvalues ( INDArray A , INDArray B ) { Preconditions . checkArgument ( A . isMatrix ( ) && A . isSquare ( ) , "Argument A must be a square matrix: has shape %s" , A . shape ( ) ) ; Preconditions . checkArgument ( B . isMatrix ( ) && B . isSquare ( ) , "Argument B must be a ... | Compute generalized eigenvalues of the problem A x = L B x . The data will be unchanged no eigenvectors returned . |
20,046 | private boolean streamHasMoreTokens ( ) { if ( streamTokenizer . ttype != StreamTokenizer . TT_EOF ) { try { streamTokenizer . nextToken ( ) ; } catch ( IOException e1 ) { throw new RuntimeException ( e1 ) ; } } return streamTokenizer . ttype != StreamTokenizer . TT_EOF && streamTokenizer . ttype != - 1 ; } | Checks if underlying stream has any tokens left |
20,047 | public boolean hasMoreTokens ( ) { log . info ( "Tokens size: [" + tokens . size ( ) + "], position: [" + position . get ( ) + "]" ) ; if ( ! tokens . isEmpty ( ) ) return position . get ( ) < tokens . size ( ) ; else return streamHasMoreTokens ( ) ; } | Checks if any prebuffered tokens left otherswise checks underlying stream |
20,048 | public List < String > getTokens ( ) { if ( ! tokens . isEmpty ( ) ) return tokens ; log . info ( "Starting prebuffering..." ) ; while ( streamHasMoreTokens ( ) ) { tokens . add ( nextTokenFromStream ( ) ) ; } log . info ( "Tokens prefetch finished. Tokens size: [" + tokens . size ( ) + "]" ) ; return tokens ; } | Returns all tokens as list of Strings |
20,049 | public String [ ] columnNames ( ) { return getInputSchema ( ) . getColumnNames ( ) . toArray ( new String [ getInputSchema ( ) . getColumnNames ( ) . size ( ) ] ) ; } | Returns column names this op is meant to run on |
20,050 | public INDArray getGradient ( INDArray gradient , int iteration ) { if ( historicalGradient == null ) throw new IllegalStateException ( "Updater has not been initialized with view state" ) ; historicalGradient . addi ( gradient . mul ( gradient ) ) ; INDArray sqrtHistory = sqrt ( historicalGradient . dup ( gradientResh... | Gets feature specific learning rates Adagrad keeps a history of gradients being passed in . Note that each gradient passed in becomes adapted over time hence the opName adagrad |
20,051 | public static MissionSpec loadMissionXML ( String filename ) { MissionSpec mission = null ; try { String xml = new String ( Files . readAllBytes ( Paths . get ( filename ) ) ) ; mission = new MissionSpec ( xml , true ) ; } catch ( Exception e ) { throw new RuntimeException ( e ) ; } return mission ; } | Convenience method to load a Malmo mission specification from an XML - file |
20,052 | public DataBuffer createDouble ( double [ ] data , boolean copy , MemoryWorkspace workspace ) { return new CudaDoubleDataBuffer ( data , copy , workspace ) ; } | Creates a double data buffer |
20,053 | public RecordReader createReader ( InputSplit split ) throws IOException , InterruptedException { RecordReader reader = new ListStringRecordReader ( ) ; reader . initialize ( split ) ; return reader ; } | Creates a reader from an input split |
20,054 | public boolean matches ( SameDiff sameDiff , DifferentialFunction rootFn ) { if ( ! root . matches ( sameDiff , rootFn ) ) { return false ; } SDVariable [ ] inputs = rootFn . args ( ) ; int inCount = inputs == null ? 0 : inputs . length ; if ( inputCount != null ) { if ( inCount != this . inputCount ) return false ; } ... | Determine if the subgraph starting with the root function matches the predicate |
20,055 | public SubGraph getSubGraph ( SameDiff sd , DifferentialFunction rootFn ) { Preconditions . checkState ( matches ( sd , rootFn ) , "Root function does not match predicate" ) ; List < DifferentialFunction > childNodes = new ArrayList < > ( ) ; if ( ! opInputSubgraphPredicates . isEmpty ( ) ) { for ( Map . Entry < Intege... | Get the SubGraph that matches the predicate |
20,056 | public void create ( ) { RunInstancesRequest runInstancesRequest = new RunInstancesRequest ( ) . withImageId ( amiId ) . withInstanceType ( size ) . withKeyName ( keyPair ) . withMinCount ( 1 ) . withSecurityGroupIds ( securityGroupId ) . withMaxCount ( numBoxes ) ; AmazonEC2 ec2 = getEc2 ( ) ; ec2 . setRegion ( com . ... | Create the instances |
20,057 | public void subDivide ( ) { MemoryWorkspace workspace = workspaceMode == WorkspaceMode . NONE ? new DummyWorkspace ( ) : Nd4j . getWorkspaceManager ( ) . getWorkspaceForCurrentThread ( workspaceConfigurationExternal , workspaceExternal ) ; try ( MemoryWorkspace ws = workspace . notifyScopeEntered ( ) ) { INDArray newCo... | Subdivide the node in to 4 children |
20,058 | public static IActivation getIActivationFromConfig ( Map < String , Object > layerConfig , KerasLayerConfiguration conf ) throws InvalidKerasConfigurationException , UnsupportedKerasConfigurationException { return getActivationFromConfig ( layerConfig , conf ) . getActivationFunction ( ) ; } | Get activation function from Keras layer configuration . |
20,059 | public static Activation getActivationFromConfig ( Map < String , Object > layerConfig , KerasLayerConfiguration conf ) throws InvalidKerasConfigurationException , UnsupportedKerasConfigurationException { Map < String , Object > innerConfig = KerasLayerUtils . getInnerLayerConfigFromConfig ( layerConfig , conf ) ; if (... | Get activation enum value from Keras layer configuration . |
20,060 | protected void postInit ( ) { Collection < TrainingListener > oldListeners = new ArrayList < > ( ) ; Collection < TrainingListener > replicatedListeners = new ArrayList < > ( ) ; if ( parallelWrapper . getListeners ( ) != null ) { oldListeners . addAll ( parallelWrapper . getListeners ( ) ) ; } configureListeners ( uui... | This method does post - initialization configuration of Model . Good place to configure listeners and all such a things |
20,061 | public void free ( AllocationPoint point ) { if ( point . getAllocationStatus ( ) == AllocationStatus . DEVICE ) { super . free ( point ) ; } else { AllocationShape shape = point . getShape ( ) ; long reqMemory = AllocationUtils . getRequiredMemory ( shape ) ; if ( reqMemory > CudaEnvironment . getInstance ( ) . getCon... | This method frees specific chunk of memory described by AllocationPoint passed in . |
20,062 | public static INDArray convertArrowVector ( FieldVector fieldVector , ColumnType type ) { DataBuffer buffer = null ; int cols = fieldVector . getValueCount ( ) ; ByteBuffer direct = ByteBuffer . allocateDirect ( fieldVector . getDataBuffer ( ) . capacity ( ) ) ; direct . order ( ByteOrder . nativeOrder ( ) ) ; fieldVec... | Convert a field vector to a column vector |
20,063 | public static List < Writable > toArrowWritablesSingle ( List < FieldVector > fieldVectors , Schema schema ) { return toArrowWritables ( fieldVectors , schema ) . get ( 0 ) ; } | Return a singular record based on the converted writables result . |
20,064 | public static Field field ( String name , ArrowType arrowType ) { return new Field ( name , FieldType . nullable ( arrowType ) , new ArrayList < Field > ( ) ) ; } | Shortcut method for returning a field given an arrow type and name with no sub fields |
20,065 | public static List < FieldVector > toArrowColumns ( final BufferAllocator bufferAllocator , final Schema schema , List < List < Writable > > dataVecRecord ) { int numRows = dataVecRecord . size ( ) ; List < FieldVector > ret = createFieldVectors ( bufferAllocator , schema , numRows ) ; for ( int j = 0 ; j < schema . nu... | Given a buffer allocator and datavec schema convert the passed in batch of records to a set of arrow columns |
20,066 | public static void assertNInNOutSet ( String layerType , String layerName , long layerIndex , long nIn , long nOut ) { if ( nIn <= 0 || nOut <= 0 ) { if ( layerName == null ) layerName = "(name not set)" ; throw new DL4JInvalidConfigException ( layerType + " (index=" + layerIndex + ", name=" + layerName + ") nIn=" + nI... | Asserts that the layer nIn and nOut values are set for the layer |
20,067 | public static void assertNOutSet ( String layerType , String layerName , long layerIndex , long nOut ) { if ( nOut <= 0 ) { if ( layerName == null ) layerName = "(name not set)" ; throw new DL4JInvalidConfigException ( layerType + " (index=" + layerIndex + ", name=" + layerName + ") nOut=" + nOut + "; nOut must be > 0"... | Asserts that the layer nOut value is set for the layer |
20,068 | public SDVariable jaccardDistance ( SDVariable x , SDVariable y , int ... dimensions ) { return jaccardDistance ( null , x , y , dimensions ) ; } | Jaccard similarity reduction operation . The output contains the Jaccard distance for each tensor along the specified dimensions . |
20,069 | public SDVariable [ ] normalizeMoments ( String [ ] name , SDVariable counts , SDVariable means , SDVariable variances , double shift ) { SDVariable [ ] res = f ( ) . normalizeMoments ( counts , means , variances , shift ) ; return sd . updateVariableNamesAndReferences ( res , name ) ; } | Calculate the mean and variance from the sufficient statistics |
20,070 | public void createCluster ( ) { AmazonElasticMapReduce emr = sparkEmrClientBuilder . build ( ) ; Optional < ClusterSummary > csr = findClusterWithName ( emr , sparkClusterName ) ; if ( csr . isPresent ( ) ) { String msg = String . format ( "A cluster with name %s and id %s is already deployed" , sparkClusterName , csr ... | Creates the current cluster |
20,071 | public boolean isReadyForNext ( ) { if ( objectMapper == null ) objectMapper = new ObjectMapper ( ) ; try { int masterStream = Integer . parseInt ( ndarraySendUrl . split ( ":" ) [ 2 ] ) ; SubscriberState subscriberState = objectMapper . readValue ( Unirest . get ( String . format ( "http://%s:%d/state/%d" , masterStat... | Returns true if the client is ready for a next array or not |
20,072 | public boolean masterStarted ( ) { if ( objectMapper == null ) objectMapper = new ObjectMapper ( ) ; try { String type = objectMapper . readValue ( Unirest . get ( String . format ( "http://%s:%d/opType" , masterStatusHost , masterStatusPort ) ) . asJson ( ) . getBody ( ) . toString ( ) , ServerTypeJson . class ) . get... | Sends a post request to the status server to determine if the master node is started . |
20,073 | public INDArray getArray ( ) { if ( subscriber == null ) { running = new AtomicBoolean ( true ) ; subscriber = AeronNDArraySubscriber . startSubscriber ( aeron , subscriberHost , subscriberPort , this , subscriberStream , running ) ; log . debug ( "Started parameter server client on " + subscriber . connectionUrl ( ) )... | Get an ndarray from the designated ndarray retrieve url . This will pull the current ndarray from the master |
20,074 | public void apply ( InMemoryLookupTable table ) { for ( Map . Entry < Integer , Set < INDArray > > entry : changes . entrySet ( ) ) { Set < INDArray > changes = entry . getValue ( ) ; INDArray toChange = table . getSyn0 ( ) . slice ( entry . getKey ( ) ) ; for ( INDArray syn1 : changes ) Nd4j . getBlasWrapper ( ) . lev... | Take the changes and apply them to the given table |
20,075 | public DataSet loadFromMetaData ( List < RecordMetaData > list ) throws IOException { if ( underlying == null ) { Record r = recordReader . loadFromMetaData ( list . get ( 0 ) ) ; initializeUnderlying ( r ) ; } List < RecordMetaData > l = new ArrayList < > ( list . size ( ) ) ; for ( RecordMetaData m : list ) { l . add... | Load a multiple examples to a DataSet using the provided RecordMetaData instances . |
20,076 | public static < V , E > Graph < V , E > loadGraph ( String path , EdgeLineProcessor < E > lineProcessor , VertexFactory < V > vertexFactory , int numVertices , boolean allowMultipleEdges ) throws IOException { Graph < V , E > graph = new Graph < > ( numVertices , allowMultipleEdges , vertexFactory ) ; try ( BufferedRea... | Load a graph into memory using a given EdgeLineProcessor . Assume one edge per line |
20,077 | public static < V , E > Graph < V , E > loadGraph ( String vertexFilePath , String edgeFilePath , VertexLoader < V > vertexLoader , EdgeLineProcessor < E > edgeLineProcessor , boolean allowMultipleEdges ) throws IOException { List < Vertex < V > > vertices = vertexLoader . loadVertices ( vertexFilePath ) ; Graph < V , ... | Load graph assuming vertices are in one file and edges are in another file . |
20,078 | public static INDArray normalizeZeroMeanAndUnitVariance ( INDArray toNormalize ) { INDArray columnMeans = toNormalize . mean ( 0 ) ; INDArray columnStds = toNormalize . std ( 0 ) ; toNormalize . subiRowVector ( columnMeans ) ; columnStds . addi ( Nd4j . EPS_THRESHOLD ) ; toNormalize . diviRowVector ( columnStds ) ; ret... | Normalize data to zero mean and unit variance substract by the mean and divide by the standard deviation |
20,079 | public static INDArray pow ( INDArray ndArray , INDArray power , boolean dup ) { INDArray result = ( dup ? ndArray . ulike ( ) : ndArray ) ; return exec ( new PowPairwise ( ndArray , power , result ) ) ; } | Element - wise power function - x^y performed element - wise |
20,080 | public static INDArray tan ( INDArray ndArray , boolean dup ) { return exec ( dup ? new Tan ( ndArray , ndArray . ulike ( ) ) : new Tan ( ndArray ) ) ; } | Element - wise tan function . Copies the array |
20,081 | public static INDArray log ( INDArray ndArray , double base , boolean duplicate ) { return Nd4j . getExecutioner ( ) . exec ( new LogX ( ndArray , duplicate ? ndArray . ulike ( ) : ndArray , base ) ) ; } | Log on arbitrary base |
20,082 | public static INDArray sign ( INDArray toSign , boolean dup ) { return exec ( dup ? new Sign ( toSign , toSign . ulike ( ) ) : new Sign ( toSign ) ) ; } | Signum function of this ndarray |
20,083 | public static INDArray max ( INDArray ndArray , double k , boolean dup ) { return exec ( dup ? new ScalarMax ( ndArray , null , ndArray . ulike ( ) , k ) : new ScalarMax ( ndArray , k ) ) ; } | Maximum function with a scalar |
20,084 | public static INDArray min ( INDArray ndArray , double k , boolean dup ) { return exec ( dup ? new ScalarMin ( ndArray , null , ndArray . ulike ( ) , k ) : new ScalarMin ( ndArray , k ) ) ; } | Minimum function with a scalar |
20,085 | public static INDArray min ( INDArray first , INDArray second ) { return min ( first , second , true ) ; } | Element wise minimum function between 2 INDArrays |
20,086 | public void destroyWorkspace ( boolean extended ) { if ( workspace . getHostPointer ( ) != null && workspace . getHostPointer ( ) . getOriginalPointer ( ) != null && workspace . getHostPointer ( ) . getOriginalPointer ( ) instanceof BytePointer ) workspace . getHostPointer ( ) . getOriginalPointer ( ) . deallocate ( ) ... | This method basically deallocates workspace memory |
20,087 | public MemoryWorkspace notifyScopeBorrowed ( ) { if ( isBorrowed . get ( ) ) throw new ND4JIllegalStateException ( "Workspace [" + id + "]: Can't borrow from borrowed workspace" ) ; borrowingWorkspace = Nd4j . getMemoryManager ( ) . getCurrentWorkspace ( ) ; isBorrowed . set ( true ) ; Nd4j . getMemoryManager ( ) . set... | This method TEMPORARY enters this workspace without reset applied |
20,088 | public KerasModelBuilder modelJsonFilename ( String modelJsonFilename ) throws IOException { checkForExistence ( modelJsonFilename ) ; this . modelJson = new String ( Files . readAllBytes ( Paths . get ( modelJsonFilename ) ) ) ; return this ; } | Set model architecture from file name pointing to model JSON string . |
20,089 | public KerasModelBuilder modelYamlFilename ( String modelYamlFilename ) throws IOException { checkForExistence ( modelYamlFilename ) ; this . modelJson = new String ( Files . readAllBytes ( Paths . get ( modelYamlFilename ) ) ) ; return this ; } | Set model architecture from file name pointing to model YAML string . |
20,090 | public KerasModelBuilder modelJsonInputStream ( InputStream modelJsonInputStream ) throws IOException { ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream ( ) ; IOUtils . copy ( modelJsonInputStream , byteArrayOutputStream ) ; this . modelJson = new String ( byteArrayOutputStream . toByteArray ( ) ... | Set model architecture from input stream of model JSON . |
20,091 | public KerasModelBuilder modelYamlInputStream ( InputStream modelYamlInputStream ) throws IOException { ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream ( ) ; IOUtils . copy ( modelYamlInputStream , byteArrayOutputStream ) ; this . modelJson = new String ( byteArrayOutputStream . toByteArray ( ) ... | Set model architecture from input stream of model YAML . |
20,092 | public KerasModelBuilder trainingJsonInputStream ( InputStream trainingJsonInputStream ) throws IOException { ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream ( ) ; IOUtils . copy ( trainingJsonInputStream , byteArrayOutputStream ) ; this . trainingJson = new String ( byteArrayOutputStream . toBy... | Provide training configuration as file input stream from JSON |
20,093 | public KerasModelBuilder trainingYamlInputStream ( InputStream trainingYamlInputStream ) throws IOException { ByteArrayOutputStream byteArrayOutputStream = new ByteArrayOutputStream ( ) ; IOUtils . copy ( trainingYamlInputStream , byteArrayOutputStream ) ; this . trainingYaml = new String ( byteArrayOutputStream . toBy... | Provide training configuration as file input stream from YAML |
20,094 | public KerasModelBuilder weightsHdf5FilenameNoRoot ( String weightsHdf5Filename ) throws IOException { checkForExistence ( weightsHdf5Filename ) ; this . weightsArchive = new Hdf5Archive ( weightsHdf5Filename ) ; return this ; } | Set weights of the model by providing the file name of the corresponding weights HDF5 file . The root of the HDF5 group containing weights won t be set by this method . |
20,095 | public KerasModelBuilder weightsHdf5Filename ( String weightsHdf5Filename ) throws IOException { checkForExistence ( weightsHdf5Filename ) ; this . weightsArchive = new Hdf5Archive ( weightsHdf5Filename ) ; this . weightsRoot = config . getTrainingWeightsRoot ( ) ; return this ; } | Set weights of the model by providing the file name of the corresponding weights HDF5 file . The root of the HDF5 group containing weights will be read and set from the configuration of this model builder instance . |
20,096 | public void close ( ) { if ( trainingArchive != null && trainingArchive != weightsArchive ) { trainingArchive . close ( ) ; trainingArchive = null ; } if ( weightsArchive != null ) { weightsArchive . close ( ) ; weightsArchive = null ; } } | Close all HDF5 archives for this model builder . |
20,097 | protected double ddoti ( long N , INDArray X , DataBuffer indx , INDArray Y ) { return cblas_ddoti ( ( int ) N , ( DoublePointer ) X . data ( ) . addressPointer ( ) , ( IntPointer ) indx . addressPointer ( ) , ( DoublePointer ) Y . data ( ) . addressPointer ( ) ) ; } | Computes the dot product of a compressed sparse double vector by a full - storage real vector . |
20,098 | protected double sdoti ( long N , INDArray X , DataBuffer indx , INDArray Y ) { return cblas_sdoti ( ( int ) N , ( FloatPointer ) X . data ( ) . addressPointer ( ) , ( IntPointer ) indx . addressPointer ( ) , ( FloatPointer ) Y . data ( ) . addressPointer ( ) ) ; } | Computes the dot product of a compressed sparse float vector by a full - storage real vector . |
20,099 | protected double dnrm2 ( long N , INDArray X , int incx ) { return cblas_dnrm2 ( ( int ) N , ( DoublePointer ) X . data ( ) . addressPointer ( ) , incx ) ; } | Computes the Euclidean norm of a double vector |
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