Java Code Examples for org.nd4j.linalg.api.buffer.DataType#LONG
The following examples show how to use
org.nd4j.linalg.api.buffer.DataType#LONG .
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Example 1
| Source File: TensorflowConversion.java From deeplearning4j with Apache License 2.0 | 6 votes |
|
private DataType typeFor(int tensorflowType) {
switch(tensorflowType) {
case DT_DOUBLE: return DataType.DOUBLE;
case DT_FLOAT: return DataType.FLOAT;
case DT_HALF: return DataType.HALF;
case DT_INT16: return DataType.SHORT;
case DT_INT32: return DataType.INT;
case DT_INT64: return DataType.LONG;
case DT_STRING: return DataType.UTF8;
case DT_INT8: return DataType.BYTE;
case DT_UINT8: return DataType.UBYTE;
case DT_UINT16: return DataType.UINT16;
case DT_UINT32: return DataType.UINT32;
case DT_UINT64: return DataType.UINT64;
case DT_BFLOAT16: return DataType.BFLOAT16;
case DT_BOOL: return DataType.BOOL;
default: throw new IllegalArgumentException("Illegal type " + tensorflowType);
}
}
Example 2
| Source File: SpecialTests.java From deeplearning4j with Apache License 2.0 | 6 votes |
|
@Test
public void reproduceWorkspaceCrash_4(){
val conf = WorkspaceConfiguration.builder().build();
val ws = Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(conf, "WS");
val dtypes = new DataType[]{DataType.LONG, DataType.DOUBLE, DataType.FLOAT, DataType.HALF, DataType.INT, DataType.SHORT, DataType.BYTE, DataType.UBYTE, DataType.BOOL};
for (val dX : dtypes) {
for (val dZ: dtypes) {
try(val ws2 = Nd4j.getWorkspaceManager().getAndActivateWorkspace("WS")) {
val array = Nd4j.create(dX, 100, 100).assign(1);
// log.info("Trying to cast {} to {}", dX, dZ);
val casted = array.castTo(dZ);
val exp = Nd4j.create(dZ, 100, 100).assign(1);
assertEquals(exp, casted);
}
}
}
}
Example 3
| Source File: ArrayOptionsHelper.java From deeplearning4j with Apache License 2.0 | 6 votes |
|
public static DataType dataType(long opt) {
if (hasBitSet(opt, DTYPE_COMPRESSED_BIT))
return DataType.COMPRESSED;
else if (hasBitSet(opt, DTYPE_HALF_BIT))
return DataType.HALF;
else if (hasBitSet(opt, DTYPE_BFLOAT16_BIT))
return DataType.BFLOAT16;
else if (hasBitSet(opt, DTYPE_FLOAT_BIT))
return DataType.FLOAT;
else if (hasBitSet(opt, DTYPE_DOUBLE_BIT))
return DataType.DOUBLE;
else if (hasBitSet(opt, DTYPE_INT_BIT))
return hasBitSet(opt, DTYPE_UNSIGNED_BIT) ? DataType.UINT32 : DataType.INT;
else if (hasBitSet(opt, DTYPE_LONG_BIT))
return hasBitSet(opt, DTYPE_UNSIGNED_BIT) ? DataType.UINT64 : DataType.LONG;
else if (hasBitSet(opt, DTYPE_BOOL_BIT))
return DataType.BOOL;
else if (hasBitSet(opt, DTYPE_BYTE_BIT)) {
return hasBitSet(opt, DTYPE_UNSIGNED_BIT) ? DataType.UBYTE : DataType.BYTE; //Byte bit set for both UBYTE and BYTE
} else if (hasBitSet(opt, DTYPE_SHORT_BIT))
return hasBitSet(opt, DTYPE_UNSIGNED_BIT) ? DataType.UINT16 : DataType.SHORT;
else if (hasBitSet(opt, DTYPE_UTF8_BIT))
return DataType.UTF8;
else
throw new ND4JUnknownDataTypeException("Unknown extras set: [" + opt + "]");
}
Example 4
| Source File: SpecialTests.java From deeplearning4j with Apache License 2.0 | 6 votes |
|
@Test
public void reproduceWorkspaceCrash_3(){
val conf = WorkspaceConfiguration.builder().build();
val ws = Nd4j.getWorkspaceManager().getWorkspaceForCurrentThread(conf, "WS");
val dtypes = new DataType[]{DataType.DOUBLE, DataType.FLOAT, DataType.HALF, DataType.LONG, DataType.INT, DataType.SHORT, DataType.BYTE, DataType.UBYTE, DataType.BOOL};
for (val dX : dtypes) {
for (val dZ: dtypes) {
try(val ws2 = ws.notifyScopeEntered()) {
val array = Nd4j.create(dX, 2, 5).assign(1);
// log.info("Trying to cast {} to {}", dX, dZ);
val casted = array.castTo(dZ);
val exp = Nd4j.create(dZ, 2, 5).assign(1);
assertEquals(exp, casted);
Nd4j.getExecutioner().commit();
}
}
}
}
Example 5
| Source File: ArrowSerde.java From deeplearning4j with Apache License 2.0 | 6 votes |
|
/**
* Create thee databuffer type frm the given type,
* relative to the bytes in arrow in class:
* {@link Type}
* @param type the type to create the nd4j {@link DataType} from
* @param elementSize the element size
* @return the data buffer type
*/
public static DataType typeFromTensorType(byte type, int elementSize) {
if(type == Type.FloatingPoint) {
return DataType.FLOAT;
}
else if(type == Type.Decimal) {
return DataType.DOUBLE;
}
else if(type == Type.Int) {
if(elementSize == 4) {
return DataType.INT;
}
else if(elementSize == 8) {
return DataType.LONG;
}
}
else {
throw new IllegalArgumentException("Only valid types are Type.Decimal and Type.Int");
}
throw new IllegalArgumentException("Unable to determine data type");
}
Example 6
| Source File: ArgAmax.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
if(attributesForNode.containsKey("output_type")) {
outputType = TFGraphMapper.convertType(attributesForNode.get("output_type").getType());
} else {
outputType = DataType.LONG;
}
}
Example 7
| Source File: ArgMax.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
if(attributesForNode.containsKey("output_type")) {
outputType = TFGraphMapper.convertType(attributesForNode.get("output_type").getType());
} else {
outputType = DataType.LONG;
}
}
Example 8
| Source File: ArgAmin.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
if(attributesForNode.containsKey("output_type")) {
outputType = TFGraphMapper.convertType(attributesForNode.get("output_type").getType());
} else {
outputType = DataType.LONG;
}
}
Example 9
| Source File: JsonSerdeTests.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Test
public void testNDArrayTextSerializer() throws Exception {
for(char order : new char[]{'c', 'f'}) {
Nd4j.factory().setOrder(order);
for (DataType globalDT : new DataType[]{DataType.DOUBLE, DataType.FLOAT, DataType.HALF}) {
Nd4j.setDefaultDataTypes(globalDT, globalDT);
Nd4j.getRandom().setSeed(12345);
INDArray in = Nd4j.rand(DataType.DOUBLE, 3, 4).muli(20).subi(10);
val om = new ObjectMapper();
for (DataType dt : new DataType[]{DataType.DOUBLE, DataType.FLOAT, DataType.HALF, DataType.LONG, DataType.INT, DataType.SHORT,
DataType.BYTE, DataType.UBYTE, DataType.BOOL, DataType.UTF8}) {
INDArray arr;
if(dt == DataType.UTF8){
arr = Nd4j.create("aaaaa", "bbbb", "ccc", "dd", "e", "f", "g", "h", "i", "j", "k", "l").reshape('c', 3, 4);
} else {
arr = in.castTo(dt);
}
TestClass tc = new TestClass(arr);
String s = om.writeValueAsString(tc);
// System.out.println(dt);
// System.out.println(s);
// System.out.println("\n\n\n");
TestClass deserialized = om.readValue(s, TestClass.class);
assertEquals(dt.toString(), tc, deserialized);
}
}
}
}
Example 10
| Source File: ArgMin.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String, AttrValue> attributesForNode, GraphDef graph) {
if(attributesForNode.containsKey("output_type")) {
outputType = TFGraphMapper.convertType(attributesForNode.get("output_type").getType());
} else {
outputType = DataType.LONG;
}
}
Example 11
| Source File: CustomOpsTests.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
@Test
public void testSizeTypes(){
List<DataType> failed = new ArrayList<>();
for(DataType dt : new DataType[]{DataType.LONG, DataType.INT, DataType.SHORT, DataType.BYTE,
DataType.UINT64, DataType.UINT32, DataType.UINT16, DataType.UBYTE,
DataType.DOUBLE, DataType.FLOAT, DataType.HALF, DataType.BFLOAT16}) {
INDArray in = Nd4j.create(DataType.FLOAT, 100);
INDArray out = Nd4j.scalar(dt, 0);
INDArray e = Nd4j.scalar(dt, 100);
DynamicCustomOp op = DynamicCustomOp.builder("size")
.addInputs(in)
.addOutputs(out)
.build();
try {
Nd4j.exec(op);
assertEquals(e, out);
} catch (Throwable t){
failed.add(dt);
}
}
if(!failed.isEmpty()){
fail("Failed datatypes: " + failed.toString());
}
}
Example 12
| Source File: ArrayOptionsHelper.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
public static DataType convertToDataType(org.tensorflow.framework.DataType dataType) {
switch (dataType) {
case DT_UINT16:
return DataType.UINT16;
case DT_UINT32:
return DataType.UINT32;
case DT_UINT64:
return DataType.UINT64;
case DT_BOOL:
return DataType.BOOL;
case DT_BFLOAT16:
return DataType.BFLOAT16;
case DT_FLOAT:
return DataType.FLOAT;
case DT_INT32:
return DataType.INT;
case DT_INT64:
return DataType.LONG;
case DT_INT8:
return DataType.BYTE;
case DT_INT16:
return DataType.SHORT;
case DT_DOUBLE:
return DataType.DOUBLE;
case DT_UINT8:
return DataType.UBYTE;
case DT_HALF:
return DataType.HALF;
case DT_STRING:
return DataType.UTF8;
default:
throw new UnsupportedOperationException("Unknown TF data type: [" + dataType.name() + "]");
}
}
Example 13
| Source File: PythonUtils.java From deeplearning4j with Apache License 2.0 | 5 votes |
|
public static NumpyArray mapToNumpyArray(Map map) {
String dtypeName = (String) map.get("dtype");
DataType dtype;
if (dtypeName.equals("float64")) {
dtype = DataType.DOUBLE;
} else if (dtypeName.equals("float32")) {
dtype = DataType.FLOAT;
} else if (dtypeName.equals("int16")) {
dtype = DataType.SHORT;
} else if (dtypeName.equals("int32")) {
dtype = DataType.INT;
} else if (dtypeName.equals("int64")) {
dtype = DataType.LONG;
} else {
throw new RuntimeException("Unsupported array type " + dtypeName + ".");
}
List shapeList = (List) map.get("shape");
long[] shape = new long[shapeList.size()];
for (int i = 0; i < shape.length; i++) {
shape[i] = (Long) shapeList.get(i);
}
List strideList = (List) map.get("shape");
long[] stride = new long[strideList.size()];
for (int i = 0; i < stride.length; i++) {
stride[i] = (Long) strideList.get(i);
}
long address = (Long) map.get("address");
NumpyArray numpyArray = new NumpyArray(address, shape, stride, dtype, true);
return numpyArray;
}
Example 14
| Source File: BaseCpuDataBuffer.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
public void actualizePointerAndIndexer() {
val cptr = ptrDataBuffer.primaryBuffer();
// skip update if pointers are equal
if (cptr != null && pointer != null && cptr.address() == pointer.address())
return;
val t = dataType();
if (t == DataType.BOOL) {
pointer = new PagedPointer(cptr, length).asBoolPointer();
setIndexer(BooleanIndexer.create((BooleanPointer) pointer));
} else if (t == DataType.UBYTE) {
pointer = new PagedPointer(cptr, length).asBytePointer();
setIndexer(UByteIndexer.create((BytePointer) pointer));
} else if (t == DataType.BYTE) {
pointer = new PagedPointer(cptr, length).asBytePointer();
setIndexer(ByteIndexer.create((BytePointer) pointer));
} else if (t == DataType.UINT16) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(UShortIndexer.create((ShortPointer) pointer));
} else if (t == DataType.SHORT) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(ShortIndexer.create((ShortPointer) pointer));
} else if (t == DataType.UINT32) {
pointer = new PagedPointer(cptr, length).asIntPointer();
setIndexer(UIntIndexer.create((IntPointer) pointer));
} else if (t == DataType.INT) {
pointer = new PagedPointer(cptr, length).asIntPointer();
setIndexer(IntIndexer.create((IntPointer) pointer));
} else if (t == DataType.UINT64) {
pointer = new PagedPointer(cptr, length).asLongPointer();
setIndexer(LongIndexer.create((LongPointer) pointer));
} else if (t == DataType.LONG) {
pointer = new PagedPointer(cptr, length).asLongPointer();
setIndexer(LongIndexer.create((LongPointer) pointer));
} else if (t == DataType.BFLOAT16) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(Bfloat16Indexer.create((ShortPointer) pointer));
} else if (t == DataType.HALF) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(HalfIndexer.create((ShortPointer) pointer));
} else if (t == DataType.FLOAT) {
pointer = new PagedPointer(cptr, length).asFloatPointer();
setIndexer(FloatIndexer.create((FloatPointer) pointer));
} else if (t == DataType.DOUBLE) {
pointer = new PagedPointer(cptr, length).asDoublePointer();
setIndexer(DoubleIndexer.create((DoublePointer) pointer));
} else if (t == DataType.UTF8) {
pointer = new PagedPointer(cptr, length()).asBytePointer();
setIndexer(ByteIndexer.create((BytePointer) pointer));
} else
throw new IllegalArgumentException("Unknown datatype: " + dataType());
}
Example 15
| Source File: BaseCpuDataBuffer.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
/**
*
* @param length
* @param elementSize
*/
public BaseCpuDataBuffer(long length, int elementSize) {
if (length < 1)
throw new IllegalArgumentException("Length must be >= 1");
initTypeAndSize();
allocationMode = AllocUtil.getAllocationModeFromContext();
this.length = length;
this.underlyingLength = length;
this.elementSize = (byte) elementSize;
if (dataType() != DataType.UTF8)
ptrDataBuffer = OpaqueDataBuffer.allocateDataBuffer(length, dataType(), false);
if (dataType() == DataType.DOUBLE) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asDoublePointer();
indexer = DoubleIndexer.create((DoublePointer) pointer);
} else if (dataType() == DataType.FLOAT) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asFloatPointer();
setIndexer(FloatIndexer.create((FloatPointer) pointer));
} else if (dataType() == DataType.INT32) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asIntPointer();
setIndexer(IntIndexer.create((IntPointer) pointer));
} else if (dataType() == DataType.LONG) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asLongPointer();
setIndexer(LongIndexer.create((LongPointer) pointer));
} else if (dataType() == DataType.SHORT) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asShortPointer();
setIndexer(ShortIndexer.create((ShortPointer) pointer));
} else if (dataType() == DataType.BYTE) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asBytePointer();
setIndexer(ByteIndexer.create((BytePointer) pointer));
} else if (dataType() == DataType.UBYTE) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asBytePointer();
setIndexer(UByteIndexer.create((BytePointer) pointer));
} else if (dataType() == DataType.UTF8) {
ptrDataBuffer = OpaqueDataBuffer.allocateDataBuffer(length, INT8, false);
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asBytePointer();
setIndexer(ByteIndexer.create((BytePointer) pointer));
} else if(dataType() == DataType.FLOAT16){
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asShortPointer();
setIndexer(HalfIndexer.create((ShortPointer) pointer));
} else if(dataType() == DataType.BFLOAT16){
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asShortPointer();
setIndexer(Bfloat16Indexer.create((ShortPointer) pointer));
} else if(dataType() == DataType.BOOL){
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asBoolPointer();
setIndexer(BooleanIndexer.create((BooleanPointer) pointer));
} else if(dataType() == DataType.UINT16){
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asShortPointer();
setIndexer(UShortIndexer.create((ShortPointer) pointer));
} else if(dataType() == DataType.UINT32){
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asIntPointer();
setIndexer(UIntIndexer.create((IntPointer) pointer));
} else if (dataType() == DataType.UINT64) {
pointer = new PagedPointer(ptrDataBuffer.primaryBuffer(), length).asLongPointer();
setIndexer(LongIndexer.create((LongPointer) pointer));
}
Nd4j.getDeallocatorService().pickObject(this);
}
Example 16
| Source File: CudaLongDataBuffer.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
/**
* Initialize the opType of this buffer
*/
@Override
protected void initTypeAndSize() {
type = DataType.LONG;
elementSize = 8;
}
Example 17
| Source File: BaseCudaDataBuffer.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
public void actualizePointerAndIndexer() {
val cptr = ptrDataBuffer.primaryBuffer();
// skip update if pointers are equal
if (cptr != null && pointer != null && cptr.address() == pointer.address())
return;
val t = dataType();
if (t == DataType.BOOL) {
pointer = new PagedPointer(cptr, length).asBoolPointer();
setIndexer(BooleanIndexer.create((BooleanPointer) pointer));
} else if (t == DataType.UBYTE) {
pointer = new PagedPointer(cptr, length).asBytePointer();
setIndexer(UByteIndexer.create((BytePointer) pointer));
} else if (t == DataType.BYTE) {
pointer = new PagedPointer(cptr, length).asBytePointer();
setIndexer(ByteIndexer.create((BytePointer) pointer));
} else if (t == DataType.UINT16) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(UShortIndexer.create((ShortPointer) pointer));
} else if (t == DataType.SHORT) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(ShortIndexer.create((ShortPointer) pointer));
} else if (t == DataType.UINT32) {
pointer = new PagedPointer(cptr, length).asIntPointer();
setIndexer(UIntIndexer.create((IntPointer) pointer));
} else if (t == DataType.INT) {
pointer = new PagedPointer(cptr, length).asIntPointer();
setIndexer(IntIndexer.create((IntPointer) pointer));
} else if (t == DataType.UINT64) {
pointer = new PagedPointer(cptr, length).asLongPointer();
setIndexer(LongIndexer.create((LongPointer) pointer));
} else if (t == DataType.LONG) {
pointer = new PagedPointer(cptr, length).asLongPointer();
setIndexer(LongIndexer.create((LongPointer) pointer));
} else if (t == DataType.BFLOAT16) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(Bfloat16Indexer.create((ShortPointer) pointer));
} else if (t == DataType.HALF) {
pointer = new PagedPointer(cptr, length).asShortPointer();
setIndexer(HalfIndexer.create((ShortPointer) pointer));
} else if (t == DataType.FLOAT) {
pointer = new PagedPointer(cptr, length).asFloatPointer();
setIndexer(FloatIndexer.create((FloatPointer) pointer));
} else if (t == DataType.DOUBLE) {
pointer = new PagedPointer(cptr, length).asDoublePointer();
setIndexer(DoubleIndexer.create((DoublePointer) pointer));
} else if (t == DataType.UTF8) {
pointer = new PagedPointer(cptr, length()).asBytePointer();
setIndexer(ByteIndexer.create((BytePointer) pointer));
} else
throw new IllegalArgumentException("Unknown datatype: " + dataType());
}
Example 18
| Source File: BaseReduceLongOp.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
@Override
public DataType resultType() {
return DataType.LONG;
}
Example 19
| Source File: BaseReduceLongOp.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
@Override
public DataType resultType(OpContext oc) {
return DataType.LONG;
}
Example 20
| Source File: PythonObject.java From deeplearning4j with Apache License 2.0 | 4 votes |
|
public NumpyArray toNumpy() throws PythonException{
PyObject np = PyImport_ImportModule("numpy");
PyObject ndarray = PyObject_GetAttrString(np, "ndarray");
if (PyObject_IsInstance(nativePythonObject, ndarray) != 1){
throw new PythonException("Object is not a numpy array! Use Python.ndarray() to convert object to a numpy array.");
}
Py_DecRef(ndarray);
Py_DecRef(np);
Pointer objPtr = new Pointer(nativePythonObject);
PyArrayObject npArr = new PyArrayObject(objPtr);
Pointer ptr = PyArray_DATA(npArr);
long[] shape = new long[PyArray_NDIM(npArr)];
SizeTPointer shapePtr = PyArray_SHAPE(npArr);
if (shapePtr != null)
shapePtr.get(shape, 0, shape.length);
long[] strides = new long[shape.length];
SizeTPointer stridesPtr = PyArray_STRIDES(npArr);
if (stridesPtr != null)
stridesPtr.get(strides, 0, strides.length);
int npdtype = PyArray_TYPE(npArr);
DataType dtype;
switch (npdtype){
case NPY_DOUBLE:
dtype = DataType.DOUBLE; break;
case NPY_FLOAT:
dtype = DataType.FLOAT; break;
case NPY_SHORT:
dtype = DataType.SHORT; break;
case NPY_INT:
dtype = DataType.INT32; break;
case NPY_LONG:
dtype = DataType.LONG; break;
case NPY_UINT:
dtype = DataType.UINT32; break;
case NPY_BYTE:
dtype = DataType.INT8; break;
case NPY_UBYTE:
dtype = DataType.UINT8; break;
case NPY_BOOL:
dtype = DataType.BOOL; break;
case NPY_HALF:
dtype = DataType.FLOAT16; break;
case NPY_LONGLONG:
dtype = DataType.INT64; break;
case NPY_USHORT:
dtype = DataType.UINT16; break;
case NPY_ULONG:
case NPY_ULONGLONG:
dtype = DataType.UINT64; break;
default:
throw new PythonException("Unsupported array data type: " + npdtype);
}
return new NumpyArray(ptr.address(), shape, strides, dtype);
}
