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shape function override (#161) 

Signed-off-by: raver119 <raver119@gmail.com>
master
raver119 2020-01-04 09:06:44 +03:00 committed by GitHub
parent 53d3bd1269
commit 451d9d57fd
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GPG Key ID: 4AEE18F83AFDEB23
14 changed files with 277 additions and 894 deletions
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1
libnd4j/blas/NativeOps.h
View File

@ -1734,6 +1734,7 @@ typedef nd4j::graph::RandomGenerator OpaqueRandomGenerator;
ND4J_EXPORT OpaqueContext* createGraphContext(int nodeId);
ND4J_EXPORT OpaqueRandomGenerator* getGraphContextRandomGenerator(OpaqueContext* ptr);
ND4J_EXPORT void ctxAllowHelpers(OpaqueContext* ptr, bool reallyAllow);
ND4J_EXPORT void ctxShapeFunctionOverride(OpaqueContext* ptr, bool reallyOverride);
ND4J_EXPORT void markGraphContextInplace(OpaqueContext* ptr, bool reallyInplace);
ND4J_EXPORT void setGraphContextCudaContext(OpaqueContext* ptr, void *stream, void *reductionPointer, void *allocationPointer);
ND4J_EXPORT void setGraphContextInputArray(OpaqueContext* ptr, int index, void *buffer, void *shapeInfo, void *specialBuffer, void *specialShapeInfo);

4
libnd4j/blas/cpu/NativeOps.cpp
View File

@ -3104,6 +3104,10 @@ const char* lastErrorMessage() {
return nd4j::LaunchContext::defaultContext()->errorReference()->errorMessage();
}
void ctxShapeFunctionOverride(OpaqueContext* ptr, bool reallyOverride) {
ptr->setShapeFunctionOverride(reallyOverride);
}
int binaryLevel() {
#ifdef CPU_FEATURES

4
libnd4j/blas/cuda/NativeOps.cu
View File

@ -3559,6 +3559,10 @@ const char* lastErrorMessage() {
return nd4j::LaunchContext::defaultContext()->errorReference()->errorMessage();
}
void ctxShapeFunctionOverride(OpaqueContext* ptr, bool reallyOverride) {
ptr->setShapeFunctionOverride(reallyOverride);
}
int binaryLevel() {
return 0;
}

7
libnd4j/include/graph/Context.h
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@ -64,6 +64,9 @@ namespace nd4j {
std::vector<NDArray*> _handles;
bool _helpersAllowed = true;
// in some cases we might be able to skip shape function for validation purposes
bool _shapeFunctionOverride = false;
public:
Context(ContextPrototype* prototype, VariableSpace* variableSpace);
@ -196,9 +199,11 @@ namespace nd4j {
void setCudaContext(Nd4jPointer cudaStream, Nd4jPointer reductionPointer, Nd4jPointer allocationPointer);
void allowHelpers(bool reallyAllow);
bool helpersAllowed();
void setShapeFunctionOverride(bool reallyOverride);
bool shapeFunctionOverride();
};
}
}

8
libnd4j/include/graph/impl/Context.cpp
View File

@ -484,6 +484,14 @@ namespace nd4j {
for (auto b:bArgs)
_bArgs.push_back(b);
}
void Context::setShapeFunctionOverride(bool reallyOverride) {
_shapeFunctionOverride = reallyOverride;
}
bool Context::shapeFunctionOverride() {
return _shapeFunctionOverride;
}
}
}

5
libnd4j/include/ops/declarable/impl/DeclarableOp.cpp
View File

@ -189,6 +189,11 @@ namespace nd4j {
shapeStart = std::chrono::system_clock::now();
}
// if we override shape function, we'll return size of fastPath
if (ctx.isFastPath() && ctx.shapeFunctionOverride()) {
return (int) ctx.fastpath_out().size();
}
auto outSha = this->calculateOutputShape(&inSha, ctx);
results = outSha->size();

6
nd4j/nd4j-backends/nd4j-api-parent/nd4j-api/src/main/java/org/nd4j/linalg/api/ops/OpContext.java
View File

@ -136,4 +136,10 @@ public interface OpContext extends AutoCloseable {
* @param reallyAllow
*/
void allowHelpers(boolean reallyAllow);
/**
* This methos allows to disape outputs validation via shape function
* @param reallyOverride
*/
void shapeFunctionOverride(boolean reallyOverride);
}

1
nd4j/nd4j-backends/nd4j-api-parent/nd4j-native-api/src/main/java/org/nd4j/nativeblas/NativeOps.java
View File

@ -1125,6 +1125,7 @@ public interface NativeOps {
void setGraphContextIArguments(OpaqueContext ptr, LongPointer arguments, int numberOfArguments);
void setGraphContextBArguments(OpaqueContext ptr, BooleanPointer arguments, int numberOfArguments);
void ctxAllowHelpers(OpaqueContext ptr, boolean reallyAllow);
void ctxShapeFunctionOverride(OpaqueContext ptr, boolean reallyOverride);
void deleteGraphContext(OpaqueContext ptr);
OpaqueRandomGenerator createRandomGenerator(long rootSeed, long nodeSeed);

7
nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/linalg/jcublas/ops/executioner/CudaExecutioner.java
View File

@ -2282,7 +2282,7 @@ public class CudaExecutioner extends DefaultOpExecutioner {
Nd4j.getExecutioner().commit();
//
boolean shapeOverride = false;
if (op.numOutputArguments() == 0 && !op.isInplaceCall()) {
try {
val list = this.calculateOutputShape(op);
@ -2292,6 +2292,7 @@ public class CudaExecutioner extends DefaultOpExecutioner {
for (val shape: list)
op.addOutputArgument(Nd4j.create(shape));
shapeOverride = true;
} catch (Exception e) {
throw new ND4JIllegalStateException("Op name " + op.opName() + " - no output arrays were provided and calculateOutputShape failed to execute", e);
}
@ -2302,6 +2303,10 @@ public class CudaExecutioner extends DefaultOpExecutioner {
val name = op.opName();
try (val context = (CudaOpContext) buildContext()) {
// optionally skip shape validation on op execution
if (shapeOverride)
context.shapeFunctionOverride(true);
context.markInplace(op.isInplaceCall());
// transferring rng state

5
nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/linalg/jcublas/ops/executioner/CudaOpContext.java
View File

@ -141,4 +141,9 @@ public class CudaOpContext extends BaseOpContext implements OpContext {
public void allowHelpers(boolean reallyAllow) {
nativeOps.ctxAllowHelpers(context, reallyAllow);
}
@Override
public void shapeFunctionOverride(boolean reallyOverride) {
nativeOps.ctxShapeFunctionOverride(context, reallyOverride);
}
}

428
nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/nativeblas/Nd4jCuda.java
View File

@ -3100,6 +3100,7 @@ public native void deleteShapeBuffer(OpaqueConstantDataBuffer ptr);
public native OpaqueContext createGraphContext(int nodeId);
public native OpaqueRandomGenerator getGraphContextRandomGenerator(OpaqueContext ptr);
public native void ctxAllowHelpers(OpaqueContext ptr, @Cast("bool") boolean reallyAllow);
public native void ctxShapeFunctionOverride(OpaqueContext ptr, @Cast("bool") boolean reallyOverride);
public native void markGraphContextInplace(OpaqueContext ptr, @Cast("bool") boolean reallyInplace);
public native void setGraphContextCudaContext(OpaqueContext ptr, Pointer stream, Pointer reductionPointer, Pointer allocationPointer);
public native void setGraphContextInputArray(OpaqueContext ptr, int index, Pointer buffer, Pointer shapeInfo, Pointer specialBuffer, Pointer specialShapeInfo);
@ -3634,25 +3635,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
// #include <execution/AffinityManager.h>
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal NDArray mmul(@Const @ByRef NDArray arg0, @Const @ByRef NDArray arg1);
@ -3903,9 +3886,9 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* axis - axis along which to repeat elements
* repeats - number of repetitions
*/
public native NDArray repeat(int axis, @StdVector IntPointer repeats);
public native NDArray repeat(int axis, @StdVector IntBuffer repeats);
public native NDArray repeat(int axis, @StdVector int[] repeats);
public native @ByVal NDArray repeat(int axis, @StdVector IntPointer repeats);
public native @ByVal NDArray repeat(int axis, @StdVector IntBuffer repeats);
public native @ByVal NDArray repeat(int axis, @StdVector int[] repeats);
/**
* This method fills this array with zeros
@ -3918,14 +3901,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* @param array
* @return
*/
public static native @ByVal NDArray quantize(@ByRef NDArray array);
/**
* This method returns quantized copy of given array
*
* @param array
* @return
*/
public static native @ByVal NDArray quantize(@Const @ByRef NDArray array);
/**
* fill target array by repeating current array
@ -3946,10 +3922,9 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
/**
* cast array elements to given dtype
*/
public native @ByVal NDArray cast(@Cast("nd4j::DataType") int dtype);
public native NDArray cast(@Cast("nd4j::DataType") int dtype);
public native void cast(NDArray target, @Cast("nd4j::DataType") int dtype);
public native void cast(@ByRef NDArray target, @Cast("nd4j::DataType") int dtype);
/**
* returns _context
@ -4120,26 +4095,12 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
/**
* this method assigns given value to all elements in array
*/
public native void assign(double value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(double value);
public native void assign(float value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(float value);
public native void assign(@Cast("const float16") short value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const float16") short value);
public native void assign(@Cast("const Nd4jLong") long value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const Nd4jLong") long value);
public native void assign(int value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(int value);
public native void assign(@Cast("const uint8_t") byte value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const uint8_t") byte value);
public native void assign(@Cast("const bool") boolean value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const bool") boolean value);
/**
* returns new copy of this array, optionally in different order
*/
public native NDArray dup(byte newOrder/*='a'*/);
public native NDArray dup();
public native @ByVal NDArray dup(byte newOrder/*='a'*/);
public native @ByVal NDArray dup();
/**
* returns sum of all elements of array
@ -4176,9 +4137,9 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* index - the number of array to be returned among set of possible arrays
* dimensions - array of dimensions to point on
*/
public native NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntPointer dimensions);
public native NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntBuffer dimensions);
public native NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector int[] dimensions);
public native @ByVal NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntPointer dimensions);
public native @ByVal NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntBuffer dimensions);
public native @ByVal NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector int[] dimensions);
/**
* returns the number of arrays pointing on specified dimension(s)
@ -4200,54 +4161,54 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* add given row vector to all rows of this array
* row - row vector to add
*/
public native void addiRowVector(@Const NDArray row);
public native void addiRowVector(@Const @ByRef NDArray row);
/**
* add given row vector to all rows of this array, store result in target
* row - row vector to add
* target - where to store result
*/
public native void addRowVector(@Const NDArray row, NDArray target);
public native void addRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* subtract given row vector from all rows of this array, store result in target
* row - row vector to subtract
* target - where to store result
*/
public native void subRowVector(@Const NDArray row, NDArray target);
public native void subRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* multiply all rows of this array on given row vector, store result in target
* row - row vector to multiply on
* target - where to store result
*/
public native void mulRowVector(@Const NDArray row, NDArray target);
public native void mulRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* divide all rows of this array on given row vector, store result in target
* row - row vector to divide on
* target - where to store result
*/
public native void divRowVector(@Const NDArray row, NDArray target);
public native void divRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* add given column vector to all columns of this array, store result in target
* column - column vector to add
* target - where to store result
*/
public native void addColumnVector(@Const NDArray column, NDArray target);
public native void addColumnVector(@Const @ByRef NDArray column, @ByRef NDArray target);
/**
* add given column vector to all columns of this array, this array becomes affected (in-place operation)
* column - column vector to add
*/
public native void addiColumnVector(@Const NDArray column);
public native void addiColumnVector(@Const @ByRef NDArray column);
/**
* multiply all columns of this array on given column vector, this array becomes affected (in-place operation)
* column - column vector to multiply on
*/
public native void muliColumnVector(@Const NDArray column);
public native void muliColumnVector(@Const @ByRef NDArray column);
/**
* returns number of bytes used by _buffer & _shapeInfo
@ -4324,12 +4285,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native void tile(@ByRef NDArray target);
/**
* returns an array which is result of broadcasting of this and other arrays
* other - input array
*/
public native NDArray broadcast(@Const @ByRef NDArray other);
/**
* check whether array is identity matrix
*/
@ -4340,7 +4295,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native @Cast("bool") boolean isUnitary();
/**
* operator returns subarray with buffer pointing at this->_buffer with offset defined by given intervals
* idx - intervals of indexes which define the subarrays to point on, idx has form {dim0Start,dim0End, dim1Start,dim1End, ....} and length (2 * this->rankOf())
@ -4386,25 +4340,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
public native void getSubArrShapeAndOffsets(@StdVector int[] dimsToExclude, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrShapeInfo, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrOffsets, @Cast("bool") boolean keepUnitiesInShape/*=false*/);
public native void getSubArrShapeAndOffsets(@StdVector int[] dimsToExclude, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrShapeInfo, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrOffsets);
/**
* addition operator: array + other
* other - input array to add
*/
public native @ByVal @Name("operator +") NDArray add(@Const @ByRef NDArray other);
/**
* addition operator: array + scalar
* scalar - input scalar to add
*/
/**
* friend functions which implement addition operator: scalar + array
* scalar - input scalar to add
*/
//template <typename T>
//friend NDArray nd4j::operator+(const T scalar, const NDArray& arr);
/**
* addition unary operator array += other
* other - input array to add
@ -4417,39 +4352,11 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native @Name("operator -=") void subtractPut(@Const @ByRef NDArray other);
/**
* subtraction operator: array - other
* other - input array to subtract
*/
public native @ByVal @Name("operator -") NDArray subtract(@Const @ByRef NDArray other);
/**
* subtraction operator: array - scalar
* scalar - input scalar to subtract
*/
/**
* negative operator, it changes sign of all array elements on opposite
*/
public native @ByVal @Name("operator -") NDArray subtract();
/**
* friend functions which implement subtraction operator: scalar - array
* scalar - input scalar to subtract
*/
//friend NDArray nd4j::operator-(const float scalar, const NDArray& arr);
/**
* pairwise multiplication operator: array * other
* other - input array to multiply on
*/
public native @ByVal @Name("operator *") NDArray multiply(@Const @ByRef NDArray other);
/**
* multiplication operator: array * scalar
* scalar - input scalar to multiply on
*/
/**
* pairwise multiplication unary operator array *= other
* other - input array to multiply on
@ -4461,17 +4368,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* scalar - input scalar to multiply on
*/
/**
* pairwise division operator: array / other
* other - input array to divide on
*/
public native @ByVal @Name("operator /") NDArray divide(@Const @ByRef NDArray other);
/**
* division operator: array / scalar
* scalar - input scalar to divide each array element on
*/
/**
* pairwise division unary operator: array /= other
* other - input array to divide on
@ -4510,7 +4406,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* return vector with buffer which points on corresponding diagonal elements of array
* type - means of vector to be returned: column ('c') or row ('r')
*/
public native NDArray diagonal(byte type );
public native @ByVal NDArray diagonal(byte type );
/**
* fill target matrix with given value in one or two directions from main diagonal:
@ -4533,13 +4429,13 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
public native @ByVal NDArray tileToShape(@Cast("const Nd4jLong*") LongPointer shapeInfo);
public native @ByVal NDArray tileToShape(@Cast("const Nd4jLong*") LongBuffer shapeInfo);
public native @ByVal NDArray tileToShape(@Cast("const Nd4jLong*") long[] shapeInfo);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongPointer shape, NDArray target/*=nullptr*/);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongBuffer shape, NDArray target/*=nullptr*/);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector long[] shape, NDArray target/*=nullptr*/);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongPointer shape, @ByRef NDArray target);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongBuffer shape, @ByRef NDArray target);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector long[] shape, @ByRef NDArray target);
// #ifndef __JAVACPP_HACK__
// #endif
public native NDArray asT(@Cast("nd4j::DataType") int dtype);
public native @ByVal NDArray asT(@Cast("nd4j::DataType") int dtype);
public native void linspace(double start);
@ -4551,17 +4447,15 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native double getTrace();
public native ResultSet multipleTensorsAlongDimension(@StdVector IntPointer indices, @StdVector IntPointer dimensions);
public native ResultSet multipleTensorsAlongDimension(@StdVector IntBuffer indices, @StdVector IntBuffer dimensions);
public native ResultSet multipleTensorsAlongDimension(@StdVector int[] indices, @StdVector int[] dimensions);
public native @ByVal ResultSet multipleTensorsAlongDimension(@StdVector IntPointer indices, @StdVector IntPointer dimensions);
public native @ByVal ResultSet multipleTensorsAlongDimension(@StdVector IntBuffer indices, @StdVector IntBuffer dimensions);
public native @ByVal ResultSet multipleTensorsAlongDimension(@StdVector int[] indices, @StdVector int[] dimensions);
public native ResultSet allTensorsAlongDimension(@StdVector IntPointer dimensions);
public native ResultSet allTensorsAlongDimension(@StdVector IntBuffer dimensions);
public native ResultSet allTensorsAlongDimension(@StdVector int[] dimensions);
public native @ByVal ResultSet allTensorsAlongDimension(@StdVector IntPointer dimensions);
public native @ByVal ResultSet allTensorsAlongDimension(@StdVector IntBuffer dimensions);
public native @ByVal ResultSet allTensorsAlongDimension(@StdVector int[] dimensions);
//ResultSet allTensorsAlongDims(const std::vector<int>& dimensions) const;
public native ResultSet allExamples();
public native @ByVal ResultSet allExamples();
/**
* set _shapeInfo
@ -4669,7 +4563,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
/**
* returns true if these two NDArrays have same rank, dimensions, strides, ews and order
*/
public native @Cast("bool") boolean isSameShapeStrict(@Const NDArray other);
public native @Cast("bool") boolean isSameShapeStrict(@Const @ByRef NDArray other);
/**
* returns true if buffer && shapeInfo were defined (non nullptr)
@ -4728,11 +4622,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native void p(@Cast("const Nd4jLong") long i, @Cast("const Nd4jLong") long j, @Cast("const Nd4jLong") long k, @Cast("const Nd4jLong") long l, @Const @ByRef NDArray value);
/**
* creates array which points on certain sub-range of this array, sub-range is defined by given indices
*/
/**
* returns true if array is 2D
*/
@ -4803,59 +4692,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native @Cast("bool") boolean isS();
/**
* inline accessing operator for matrix, i - absolute index
*/
//FORCEINLINE NDArray operator()(const Nd4jLong i) const;
/**
* inline modifying operator for matrix, i - absolute index
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong i);
/**
* inline accessing operator for 2D array, i - row, j - column
*/
//FORCEINLINE NDArray operator()(const Nd4jLong i, const Nd4jLong j) const;
/**
* inline modifying operator for 2D array, i - row, j - column
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong i, const Nd4jLong j);
/**
* inline accessing operator for 3D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const;
/**
* inline modifying operator for 3D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k);
/**
* inline modifying operator for 4D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w);
/**
* inline accessing operator for 4D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) const;
/**
* inline modifying operator for ND array
* idx - array with corresponding indexes, for example {2,10,0,5,...,8}, number of indexes should be equal to array rank
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong* idx);
/**
* inline accessing operator for ND array
* idx - array with corresponding indexes, for example {2,10,0,5,...,8}, number of indexes should be equal to array rank
*/
//FORCEINLINE NDArray operator()(const Nd4jLong* idx) const;
public native @Cast("bool") boolean isAttached();
public native NDArray detach();
@ -4933,199 +4769,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
//////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////
// accessing operator for matrix, i - absolute index
/*
NDArray NDArray::operator()(const Nd4jLong i) const {
if (i >= shape::length(_shapeInfo))
throw std::invalid_argument("NDArray::operator(i): input index is out of array length !");
auto ews = shape::elementWiseStride(_shapeInfo);
char order = ordering();
if(ews == 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
} else if(ews > 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * ews * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
} else {
Nd4jLong idx[MAX_RANK];
shape::ind2subC(rankOf(), shapeOf(), i, idx);
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
}
*/
//////////////////////////////////////////////////////////////////////////
// modifying operator for matrix, i - absolute index
/*
NDArray& NDArray::operator()(const Nd4jLong i) {
if (i >= shape::length(_shapeInfo))
throw std::invalid_argument("NDArray::operator(i): input index is out of array length !");
auto ews = shape::elementWiseStride(_shapeInfo);
auto order = ordering();
if(ews == 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
// FIXME: bad
return result;
} else if(ews > 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * ews * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
} else {
Nd4jLong idx[MAX_RANK];
shape::ind2subC(rankOf(), shapeOf(), i, idx);
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
}*/
//////////////////////////////////////////////////////////////////////////
// accessing operator for 2D matrix, i - row, j - column
/*
NDArray NDArray::operator()(const Nd4jLong i, const Nd4jLong j) const {
if (rankOf() != 2 || i >= shapeOf()[0] || j >= shapeOf()[1])
throw std::invalid_argument("NDArray::operator(i,j): one of input indexes is out of array length or rank!=2 !");
Nd4jLong coords[2] = {i, j};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
// TODO: do we really want a view here?
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
// modifying operator for 2D matrix, i - row, j - column
/*
NDArray& NDArray::operator()(const Nd4jLong i, const Nd4jLong j) {
if (rankOf() != 2 || i >= shapeOf()[0] || j >= shapeOf()[1])
throw std::invalid_argument("NDArray::operator(i,j): one of input indexes is out of array length or rank!=2 !");
Nd4jLong coords[2] = {i, j};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
//FIXME: bad, will crash!
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
// accessing operator for 3D array, i - row, j - column
/*
NDArray NDArray::operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const {
if (rankOf() != 3 || i >= shapeOf()[0] || j >= shapeOf()[1] || j >= shapeOf()[2])
throw std::invalid_argument("NDArray::operator(i,j,k): one of input indexes is out of array length or rank!=3 !");
Nd4jLong coords[3] = {i, j, k};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
// modifying operator for 3D array
/*
NDArray& NDArray::operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) {
if (rankOf() != 3 || i >= shapeOf()[0] || j >= shapeOf()[1] || k >= shapeOf()[2])
throw std::invalid_argument("NDArray::operator(i,j,k): one of input indexes is out of array length or rank!=3 !");
Nd4jLong coords[3] = {i, j, k};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
//FIXME: bad, will crash!
return result;
}
*/
/*
NDArray NDArray::operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) const {
if (rankOf() != 4 || t >= shapeOf()[0] || u >= shapeOf()[1] || v >= shapeOf()[2] || w >= shapeOf()[3])
throw std::invalid_argument("NDArray::operator(t,u,v,w): one of input indexes is out of array length or rank!=4 !");
Nd4jLong coords[4] = {t, u, v, w};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
/*
NDArray& NDArray::operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) {
if (rankOf() != 4 || t >= shapeOf()[0] || u >= shapeOf()[1] || v >= shapeOf()[2] || w >= shapeOf()[3])
throw std::invalid_argument("NDArray::operator(t,u,v,w): one of input indexes is out of array length or rank!=4 !");
Nd4jLong coords[4] = {t, u, v, w};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
// FIXME
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
/*
NDArray NDArray::operator()(const Nd4jLong* idx) const {
for(int i = 0; i < rankOf(); ++i)
if (idx[i] >= sizeAt(i))
throw std::invalid_argument("NDArray::operator(const Nd4jLong* idx): input index is out of dimension length !");
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
/*
NDArray& NDArray::operator()(const Nd4jLong* idx) {
for(int i = 0; i < rankOf(); ++i)
if (idx[i] >= sizeAt(i))
throw std::invalid_argument("NDArray::operator(const Nd4jLong* idx): input index is out of dimension length !");
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
// FIXME
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
@ -6778,9 +6421,11 @@ NDArray& NDArray::operator()(const Nd4jLong* idx) {
public native void setCudaContext(@Cast("Nd4jPointer") Pointer cudaStream, @Cast("Nd4jPointer") Pointer reductionPointer, @Cast("Nd4jPointer") Pointer allocationPointer);
public native void allowHelpers(@Cast("bool") boolean reallyAllow);
public native @Cast("bool") boolean helpersAllowed();
public native void setShapeFunctionOverride(@Cast("bool") boolean reallyOverride);
public native @Cast("bool") boolean shapeFunctionOverride();
}
@ -10630,6 +10275,7 @@ public static final int PREALLOC_SIZE = 33554432;
// #include <ops/declarable/headers/tests.h>
// #include <ops/declarable/headers/kernels.h>
// #include <ops/declarable/headers/BarnesHutTsne.h>
// #include <ops/declarable/headers/images.h>
// #include <dll.h>
// #include <helpers/shape.h>
// #include <helpers/TAD.h>

5
nd4j/nd4j-backends/nd4j-backend-impls/nd4j-native/src/main/java/org/nd4j/linalg/cpu/nativecpu/ops/CpuOpContext.java
View File

@ -110,4 +110,9 @@ public class CpuOpContext extends BaseOpContext implements OpContext {
public void allowHelpers(boolean reallyAllow) {
nativeOps.ctxAllowHelpers(context, reallyAllow);
}
@Override
public void shapeFunctionOverride(boolean reallyOverride) {
nativeOps.ctxShapeFunctionOverride(context, reallyOverride);
}
}

7
nd4j/nd4j-backends/nd4j-backend-impls/nd4j-native/src/main/java/org/nd4j/linalg/cpu/nativecpu/ops/NativeOpExecutioner.java
View File

@ -1691,6 +1691,7 @@ public class NativeOpExecutioner extends DefaultOpExecutioner {
@Override
public INDArray[] exec(@NonNull CustomOp op) {
boolean shapeOverride = false;
if (op.numOutputArguments() == 0 && !op.isInplaceCall()) {
try {
val list = this.calculateOutputShape(op);
@ -1699,6 +1700,8 @@ public class NativeOpExecutioner extends DefaultOpExecutioner {
for (LongShapeDescriptor shape : list)
op.addOutputArgument(Nd4j.create(shape, false));
shapeOverride = true;
} catch (ND4JIllegalStateException e){
throw e;
} catch (Exception e) {
@ -1709,6 +1712,10 @@ public class NativeOpExecutioner extends DefaultOpExecutioner {
val name = op.opName();
try (val context = buildContext()) {
// optionally skip shape validation on op execution
if (shapeOverride)
context.shapeFunctionOverride(true);
context.markInplace(op.isInplaceCall());
// transferring rng state

465
nd4j/nd4j-backends/nd4j-backend-impls/nd4j-native/src/main/java/org/nd4j/nativeblas/Nd4jCpu.java
View File

@ -3103,6 +3103,7 @@ public native void deleteShapeBuffer(OpaqueConstantDataBuffer ptr);
public native OpaqueContext createGraphContext(int nodeId);
public native OpaqueRandomGenerator getGraphContextRandomGenerator(OpaqueContext ptr);
public native void ctxAllowHelpers(OpaqueContext ptr, @Cast("bool") boolean reallyAllow);
public native void ctxShapeFunctionOverride(OpaqueContext ptr, @Cast("bool") boolean reallyOverride);
public native void markGraphContextInplace(OpaqueContext ptr, @Cast("bool") boolean reallyInplace);
public native void setGraphContextCudaContext(OpaqueContext ptr, Pointer stream, Pointer reductionPointer, Pointer allocationPointer);
public native void setGraphContextInputArray(OpaqueContext ptr, int index, Pointer buffer, Pointer shapeInfo, Pointer specialBuffer, Pointer specialShapeInfo);
@ -3637,25 +3638,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
// #include <execution/AffinityManager.h>
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator -") NDArray subtract(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator +") NDArray add(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator *") NDArray multiply(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(float arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(@Cast("const float16") short arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(double arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal @Name("operator /") NDArray divide(int arg0, @Const @ByRef NDArray arg1);
@Namespace("nd4j") public static native @ByVal NDArray mmul(@Const @ByRef NDArray arg0, @Const @ByRef NDArray arg1);
@ -3906,9 +3889,9 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* axis - axis along which to repeat elements
* repeats - number of repetitions
*/
public native NDArray repeat(int axis, @StdVector IntPointer repeats);
public native NDArray repeat(int axis, @StdVector IntBuffer repeats);
public native NDArray repeat(int axis, @StdVector int[] repeats);
public native @ByVal NDArray repeat(int axis, @StdVector IntPointer repeats);
public native @ByVal NDArray repeat(int axis, @StdVector IntBuffer repeats);
public native @ByVal NDArray repeat(int axis, @StdVector int[] repeats);
/**
* This method fills this array with zeros
@ -3921,14 +3904,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* @param array
* @return
*/
public static native @ByVal NDArray quantize(@ByRef NDArray array);
/**
* This method returns quantized copy of given array
*
* @param array
* @return
*/
public static native @ByVal NDArray quantize(@Const @ByRef NDArray array);
/**
* fill target array by repeating current array
@ -3949,10 +3925,9 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
/**
* cast array elements to given dtype
*/
public native @ByVal NDArray cast(@Cast("nd4j::DataType") int dtype);
public native NDArray cast(@Cast("nd4j::DataType") int dtype);
public native void cast(NDArray target, @Cast("nd4j::DataType") int dtype);
public native void cast(@ByRef NDArray target, @Cast("nd4j::DataType") int dtype);
/**
* returns _context
@ -4123,26 +4098,12 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
/**
* this method assigns given value to all elements in array
*/
public native void assign(double value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(double value);
public native void assign(float value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(float value);
public native void assign(@Cast("const float16") short value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const float16") short value);
public native void assign(@Cast("const Nd4jLong") long value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const Nd4jLong") long value);
public native void assign(int value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(int value);
public native void assign(@Cast("const uint8_t") byte value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const uint8_t") byte value);
public native void assign(@Cast("const bool") boolean value, @Cast("bool") boolean allowParallelism/*=true*/);
public native void assign(@Cast("const bool") boolean value);
/**
* returns new copy of this array, optionally in different order
*/
public native NDArray dup(byte newOrder/*='a'*/);
public native NDArray dup();
public native @ByVal NDArray dup(byte newOrder/*='a'*/);
public native @ByVal NDArray dup();
/**
* returns sum of all elements of array
@ -4179,9 +4140,9 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* index - the number of array to be returned among set of possible arrays
* dimensions - array of dimensions to point on
*/
public native NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntPointer dimensions);
public native NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntBuffer dimensions);
public native NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector int[] dimensions);
public native @ByVal NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntPointer dimensions);
public native @ByVal NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector IntBuffer dimensions);
public native @ByVal NDArray tensorAlongDimension(@Cast("Nd4jLong") long index, @StdVector int[] dimensions);
/**
* returns the number of arrays pointing on specified dimension(s)
@ -4203,54 +4164,54 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* add given row vector to all rows of this array
* row - row vector to add
*/
public native void addiRowVector(@Const NDArray row);
public native void addiRowVector(@Const @ByRef NDArray row);
/**
* add given row vector to all rows of this array, store result in target
* row - row vector to add
* target - where to store result
*/
public native void addRowVector(@Const NDArray row, NDArray target);
public native void addRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* subtract given row vector from all rows of this array, store result in target
* row - row vector to subtract
* target - where to store result
*/
public native void subRowVector(@Const NDArray row, NDArray target);
public native void subRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* multiply all rows of this array on given row vector, store result in target
* row - row vector to multiply on
* target - where to store result
*/
public native void mulRowVector(@Const NDArray row, NDArray target);
public native void mulRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* divide all rows of this array on given row vector, store result in target
* row - row vector to divide on
* target - where to store result
*/
public native void divRowVector(@Const NDArray row, NDArray target);
public native void divRowVector(@Const @ByRef NDArray row, @ByRef NDArray target);
/**
* add given column vector to all columns of this array, store result in target
* column - column vector to add
* target - where to store result
*/
public native void addColumnVector(@Const NDArray column, NDArray target);
public native void addColumnVector(@Const @ByRef NDArray column, @ByRef NDArray target);
/**
* add given column vector to all columns of this array, this array becomes affected (in-place operation)
* column - column vector to add
*/
public native void addiColumnVector(@Const NDArray column);
public native void addiColumnVector(@Const @ByRef NDArray column);
/**
* multiply all columns of this array on given column vector, this array becomes affected (in-place operation)
* column - column vector to multiply on
*/
public native void muliColumnVector(@Const NDArray column);
public native void muliColumnVector(@Const @ByRef NDArray column);
/**
* returns number of bytes used by _buffer & _shapeInfo
@ -4327,12 +4288,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native void tile(@ByRef NDArray target);
/**
* returns an array which is result of broadcasting of this and other arrays
* other - input array
*/
public native NDArray broadcast(@Const @ByRef NDArray other);
/**
* check whether array is identity matrix
*/
@ -4343,7 +4298,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native @Cast("bool") boolean isUnitary();
/**
* operator returns subarray with buffer pointing at this->_buffer with offset defined by given intervals
* idx - intervals of indexes which define the subarrays to point on, idx has form {dim0Start,dim0End, dim1Start,dim1End, ....} and length (2 * this->rankOf())
@ -4389,25 +4343,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
public native void getSubArrShapeAndOffsets(@StdVector int[] dimsToExclude, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrShapeInfo, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrOffsets, @Cast("bool") boolean keepUnitiesInShape/*=false*/);
public native void getSubArrShapeAndOffsets(@StdVector int[] dimsToExclude, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrShapeInfo, @Cast("Nd4jLong*&") @ByPtrRef long[] subArrOffsets);
/**
* addition operator: array + other
* other - input array to add
*/
public native @ByVal @Name("operator +") NDArray add(@Const @ByRef NDArray other);
/**
* addition operator: array + scalar
* scalar - input scalar to add
*/
/**
* friend functions which implement addition operator: scalar + array
* scalar - input scalar to add
*/
//template <typename T>
//friend NDArray nd4j::operator+(const T scalar, const NDArray& arr);
/**
* addition unary operator array += other
* other - input array to add
@ -4420,39 +4355,11 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native @Name("operator -=") void subtractPut(@Const @ByRef NDArray other);
/**
* subtraction operator: array - other
* other - input array to subtract
*/
public native @ByVal @Name("operator -") NDArray subtract(@Const @ByRef NDArray other);
/**
* subtraction operator: array - scalar
* scalar - input scalar to subtract
*/
/**
* negative operator, it changes sign of all array elements on opposite
*/
public native @ByVal @Name("operator -") NDArray subtract();
/**
* friend functions which implement subtraction operator: scalar - array
* scalar - input scalar to subtract
*/
//friend NDArray nd4j::operator-(const float scalar, const NDArray& arr);
/**
* pairwise multiplication operator: array * other
* other - input array to multiply on
*/
public native @ByVal @Name("operator *") NDArray multiply(@Const @ByRef NDArray other);
/**
* multiplication operator: array * scalar
* scalar - input scalar to multiply on
*/
/**
* pairwise multiplication unary operator array *= other
* other - input array to multiply on
@ -4464,17 +4371,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* scalar - input scalar to multiply on
*/
/**
* pairwise division operator: array / other
* other - input array to divide on
*/
public native @ByVal @Name("operator /") NDArray divide(@Const @ByRef NDArray other);
/**
* division operator: array / scalar
* scalar - input scalar to divide each array element on
*/
/**
* pairwise division unary operator: array /= other
* other - input array to divide on
@ -4513,7 +4409,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
* return vector with buffer which points on corresponding diagonal elements of array
* type - means of vector to be returned: column ('c') or row ('r')
*/
public native NDArray diagonal(byte type );
public native @ByVal NDArray diagonal(byte type );
/**
* fill target matrix with given value in one or two directions from main diagonal:
@ -4536,13 +4432,13 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
public native @ByVal NDArray tileToShape(@Cast("const Nd4jLong*") LongPointer shapeInfo);
public native @ByVal NDArray tileToShape(@Cast("const Nd4jLong*") LongBuffer shapeInfo);
public native @ByVal NDArray tileToShape(@Cast("const Nd4jLong*") long[] shapeInfo);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongPointer shape, NDArray target/*=nullptr*/);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongBuffer shape, NDArray target/*=nullptr*/);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector long[] shape, NDArray target/*=nullptr*/);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongPointer shape, @ByRef NDArray target);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector LongBuffer shape, @ByRef NDArray target);
public native void tileToShape(@Cast("Nd4jLong*") @StdVector long[] shape, @ByRef NDArray target);
// #ifndef __JAVACPP_HACK__
// #endif
public native NDArray asT(@Cast("nd4j::DataType") int dtype);
public native @ByVal NDArray asT(@Cast("nd4j::DataType") int dtype);
public native void linspace(double start);
@ -4554,17 +4450,15 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native double getTrace();
public native ResultSet multipleTensorsAlongDimension(@StdVector IntPointer indices, @StdVector IntPointer dimensions);
public native ResultSet multipleTensorsAlongDimension(@StdVector IntBuffer indices, @StdVector IntBuffer dimensions);
public native ResultSet multipleTensorsAlongDimension(@StdVector int[] indices, @StdVector int[] dimensions);
public native @ByVal ResultSet multipleTensorsAlongDimension(@StdVector IntPointer indices, @StdVector IntPointer dimensions);
public native @ByVal ResultSet multipleTensorsAlongDimension(@StdVector IntBuffer indices, @StdVector IntBuffer dimensions);
public native @ByVal ResultSet multipleTensorsAlongDimension(@StdVector int[] indices, @StdVector int[] dimensions);
public native ResultSet allTensorsAlongDimension(@StdVector IntPointer dimensions);
public native ResultSet allTensorsAlongDimension(@StdVector IntBuffer dimensions);
public native ResultSet allTensorsAlongDimension(@StdVector int[] dimensions);
public native @ByVal ResultSet allTensorsAlongDimension(@StdVector IntPointer dimensions);
public native @ByVal ResultSet allTensorsAlongDimension(@StdVector IntBuffer dimensions);
public native @ByVal ResultSet allTensorsAlongDimension(@StdVector int[] dimensions);
//ResultSet allTensorsAlongDims(const std::vector<int>& dimensions) const;
public native ResultSet allExamples();
public native @ByVal ResultSet allExamples();
/**
* set _shapeInfo
@ -4672,7 +4566,7 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
/**
* returns true if these two NDArrays have same rank, dimensions, strides, ews and order
*/
public native @Cast("bool") boolean isSameShapeStrict(@Const NDArray other);
public native @Cast("bool") boolean isSameShapeStrict(@Const @ByRef NDArray other);
/**
* returns true if buffer && shapeInfo were defined (non nullptr)
@ -4731,11 +4625,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native void p(@Cast("const Nd4jLong") long i, @Cast("const Nd4jLong") long j, @Cast("const Nd4jLong") long k, @Cast("const Nd4jLong") long l, @Const @ByRef NDArray value);
/**
* creates array which points on certain sub-range of this array, sub-range is defined by given indices
*/
/**
* returns true if array is 2D
*/
@ -4806,59 +4695,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
*/
public native @Cast("bool") boolean isS();
/**
* inline accessing operator for matrix, i - absolute index
*/
//FORCEINLINE NDArray operator()(const Nd4jLong i) const;
/**
* inline modifying operator for matrix, i - absolute index
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong i);
/**
* inline accessing operator for 2D array, i - row, j - column
*/
//FORCEINLINE NDArray operator()(const Nd4jLong i, const Nd4jLong j) const;
/**
* inline modifying operator for 2D array, i - row, j - column
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong i, const Nd4jLong j);
/**
* inline accessing operator for 3D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const;
/**
* inline modifying operator for 3D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k);
/**
* inline modifying operator for 4D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w);
/**
* inline accessing operator for 4D array, i - height, j - width, k - depth
*/
//FORCEINLINE NDArray operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) const;
/**
* inline modifying operator for ND array
* idx - array with corresponding indexes, for example {2,10,0,5,...,8}, number of indexes should be equal to array rank
*/
//FORCEINLINE NDArray& operator()(const Nd4jLong* idx);
/**
* inline accessing operator for ND array
* idx - array with corresponding indexes, for example {2,10,0,5,...,8}, number of indexes should be equal to array rank
*/
//FORCEINLINE NDArray operator()(const Nd4jLong* idx) const;
public native @Cast("bool") boolean isAttached();
public native NDArray detach();
@ -4936,199 +4772,6 @@ public native @Cast("bool") boolean isOptimalRequirementsMet();
//////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////////////////////////////////////
// accessing operator for matrix, i - absolute index
/*
NDArray NDArray::operator()(const Nd4jLong i) const {
if (i >= shape::length(_shapeInfo))
throw std::invalid_argument("NDArray::operator(i): input index is out of array length !");
auto ews = shape::elementWiseStride(_shapeInfo);
char order = ordering();
if(ews == 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
} else if(ews > 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * ews * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
} else {
Nd4jLong idx[MAX_RANK];
shape::ind2subC(rankOf(), shapeOf(), i, idx);
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
}
*/
//////////////////////////////////////////////////////////////////////////
// modifying operator for matrix, i - absolute index
/*
NDArray& NDArray::operator()(const Nd4jLong i) {
if (i >= shape::length(_shapeInfo))
throw std::invalid_argument("NDArray::operator(i): input index is out of array length !");
auto ews = shape::elementWiseStride(_shapeInfo);
auto order = ordering();
if(ews == 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
// FIXME: bad
return result;
} else if(ews > 1 && order == 'c') {
auto cast = reinterpret_cast<int8_t *>(_buffer) + (i * ews * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
} else {
Nd4jLong idx[MAX_RANK];
shape::ind2subC(rankOf(), shapeOf(), i, idx);
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
}*/
//////////////////////////////////////////////////////////////////////////
// accessing operator for 2D matrix, i - row, j - column
/*
NDArray NDArray::operator()(const Nd4jLong i, const Nd4jLong j) const {
if (rankOf() != 2 || i >= shapeOf()[0] || j >= shapeOf()[1])
throw std::invalid_argument("NDArray::operator(i,j): one of input indexes is out of array length or rank!=2 !");
Nd4jLong coords[2] = {i, j};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
// TODO: do we really want a view here?
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
// modifying operator for 2D matrix, i - row, j - column
/*
NDArray& NDArray::operator()(const Nd4jLong i, const Nd4jLong j) {
if (rankOf() != 2 || i >= shapeOf()[0] || j >= shapeOf()[1])
throw std::invalid_argument("NDArray::operator(i,j): one of input indexes is out of array length or rank!=2 !");
Nd4jLong coords[2] = {i, j};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
//FIXME: bad, will crash!
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
// accessing operator for 3D array, i - row, j - column
/*
NDArray NDArray::operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) const {
if (rankOf() != 3 || i >= shapeOf()[0] || j >= shapeOf()[1] || j >= shapeOf()[2])
throw std::invalid_argument("NDArray::operator(i,j,k): one of input indexes is out of array length or rank!=3 !");
Nd4jLong coords[3] = {i, j, k};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
// modifying operator for 3D array
/*
NDArray& NDArray::operator()(const Nd4jLong i, const Nd4jLong j, const Nd4jLong k) {
if (rankOf() != 3 || i >= shapeOf()[0] || j >= shapeOf()[1] || k >= shapeOf()[2])
throw std::invalid_argument("NDArray::operator(i,j,k): one of input indexes is out of array length or rank!=3 !");
Nd4jLong coords[3] = {i, j, k};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
//FIXME: bad, will crash!
return result;
}
*/
/*
NDArray NDArray::operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) const {
if (rankOf() != 4 || t >= shapeOf()[0] || u >= shapeOf()[1] || v >= shapeOf()[2] || w >= shapeOf()[3])
throw std::invalid_argument("NDArray::operator(t,u,v,w): one of input indexes is out of array length or rank!=4 !");
Nd4jLong coords[4] = {t, u, v, w};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
/*
NDArray& NDArray::operator()(const Nd4jLong t, const Nd4jLong u, const Nd4jLong v, const Nd4jLong w) {
if (rankOf() != 4 || t >= shapeOf()[0] || u >= shapeOf()[1] || v >= shapeOf()[2] || w >= shapeOf()[3])
throw std::invalid_argument("NDArray::operator(t,u,v,w): one of input indexes is out of array length or rank!=4 !");
Nd4jLong coords[4] = {t, u, v, w};
auto xOffset = shape::getOffset(getShapeInfo(), coords);
// FIXME
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
/*
NDArray NDArray::operator()(const Nd4jLong* idx) const {
for(int i = 0; i < rankOf(); ++i)
if (idx[i] >= sizeAt(i))
throw std::invalid_argument("NDArray::operator(const Nd4jLong* idx): input index is out of dimension length !");
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
/*
NDArray& NDArray::operator()(const Nd4jLong* idx) {
for(int i = 0; i < rankOf(); ++i)
if (idx[i] >= sizeAt(i))
throw std::invalid_argument("NDArray::operator(const Nd4jLong* idx): input index is out of dimension length !");
auto xOffset = shape::getOffset(getShapeInfo(), idx);
auto cast = reinterpret_cast<int8_t *>(_buffer) + (xOffset * this->sizeOfT());
NDArray result(cast, nd4j::ShapeBuilders::createScalarShapeInfo(this->dataType(), this->getWorkspace()));
// FIXME
return result;
}
*/
//////////////////////////////////////////////////////////////////////////
@ -6781,9 +6424,11 @@ NDArray& NDArray::operator()(const Nd4jLong* idx) {
public native void setCudaContext(@Cast("Nd4jPointer") Pointer cudaStream, @Cast("Nd4jPointer") Pointer reductionPointer, @Cast("Nd4jPointer") Pointer allocationPointer);
public native void allowHelpers(@Cast("bool") boolean reallyAllow);
public native @Cast("bool") boolean helpersAllowed();
public native void setShapeFunctionOverride(@Cast("bool") boolean reallyOverride);
public native @Cast("bool") boolean shapeFunctionOverride();
}
@ -11193,7 +10838,9 @@ public static final int TAD_THRESHOLD = TAD_THRESHOLD();
// #if defined(_MSC_VER) || defined(_WIN64) || defined(_WIN32) || defined(__CLION_IDE__) || defined(__VSCODE__)
// #define NOT_EXCLUDED(NAME) 1>0
// #else
// for now we don't want minifier mechanics working
//#define NOT_EXCLUDED(NAME) defined(LIBND4J_ALL_OPS) || defined(NAME)
// #define NOT_EXCLUDED(NAME) 1>0
// #endif
// #ifdef __JAVACPP_HACK__
@ -12368,6 +12015,7 @@ public static final int TAD_THRESHOLD = TAD_THRESHOLD();
// #include <ops/declarable/headers/tests.h>
// #include <ops/declarable/headers/kernels.h>
// #include <ops/declarable/headers/BarnesHutTsne.h>
// #include <ops/declarable/headers/images.h>
// #include <dll.h>
// #include <helpers/shape.h>
// #include <helpers/TAD.h>
@ -17115,7 +16763,7 @@ public static final int TAD_THRESHOLD = TAD_THRESHOLD();
* This operation calculates hash code, optionally along dimension
*/
// #if NOT_EXCLUDED(OP_hashcode)
@Namespace("nd4j::ops") public static class hashcode extends DeclarableReductionOp {
@Namespace("nd4j::ops") public static class hashcode extends DeclarableCustomOp {
static { Loader.load(); }
/** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
public hashcode(Pointer p) { super(p); }
@ -17128,6 +16776,7 @@ public static final int TAD_THRESHOLD = TAD_THRESHOLD();
public hashcode() { super((Pointer)null); allocate(); }
private native void allocate();
public native ShapeList calculateOutputShape(ShapeList inputShape, @ByRef Context block);
}
// #endif
@ -19345,6 +18994,38 @@ public static final int TAD_THRESHOLD = TAD_THRESHOLD();
}
// #endif
/**
* lu op. - make LUP decomposition of given batch of 2D square matricies
*
* input params:
* 0 - float tensor with dimension (x * y * z * ::: * M * M)
*
* return value:
* 0 - float tensor with dimension (x * y * z * ::: * M * M) with LU M x M matricies in it
* 1 - int (32 or 64) batched vector of permutations with length M - shape (x * y * z * ::: * M)
*
* int argument:
* 0 - data type of output permutaion vector (int32 or int64), optional, default INT32
*/
// #if NOT_EXCLUDED(OP_matrix_inverse)
@Namespace("nd4j::ops") public static class lu extends DeclarableCustomOp {
static { Loader.load(); }
/** Pointer cast constructor. Invokes {@link Pointer#Pointer(Pointer)}. */
public lu(Pointer p) { super(p); }
/** Native array allocator. Access with {@link Pointer#position(long)}. */
public lu(long size) { super((Pointer)null); allocateArray(size); }
private native void allocateArray(long size);
@Override public lu position(long position) {
return (lu)super.position(position);
}
public lu() { super((Pointer)null); allocate(); }
private native void allocate();
public native ShapeList calculateOutputShape(ShapeList inputShape, @ByRef Context block);
}
// #endif
/**
* sequence_mask op. - make mask for given tensor filled by (j > x[i_1, i_2,...,i_n]) -> z[i_1, i_2,...,i_n,j]
*