212 lines
8.8 KiB
C
212 lines
8.8 KiB
C
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/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// @author raver119@gmail.com
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//
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#ifndef LIBND4J_DECLARABLE_OPS_H
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#define LIBND4J_DECLARABLE_OPS_H
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#include <sstream>
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#include <types/float16.h>
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#include <pointercast.h>
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#include <NDArray.h>
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#include <graph/Context.h>
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#include "OpDescriptor.h"
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#include <helpers/helper_hash.h>
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#include <array/ShapeList.h>
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#include <array/ResultSet.h>
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#include <helpers/OpArgsHolder.h>
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#include <dll.h>
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//#include <ops/declarable/declarable_ops.h>
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#include <chrono>
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#include <ctime>
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#include <mutex>
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using namespace nd4j::graph;
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namespace nd4j {
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namespace ops {
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Nd4jStatus ND4J_EXPORT conditionHelper(const char *file, int line, int condition, int argNumber, const char *format, ...);
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template<typename T>
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Nd4jStatus resultHelper(T status, const char *func, const char *file, int line) {
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if (status) {
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// TODO: fill out error codes here
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fprintf(stderr, "Validation error at %s:%d code=%d(%s) \"%s\" \n", file, line,
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static_cast<unsigned int>(status), "", func);
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return ND4J_STATUS_BAD_INPUT;
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}
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return ND4J_STATUS_OK;
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}
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/**
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* This class is the basic building block of Graph Operations. Any CustomOp out there is built on top of this "abstract" class.
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*
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*/
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class ND4J_EXPORT DeclarableOp {
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private:
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std::mutex _registrator;
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bool _registered = false;
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protected:
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OpDescriptor *_descriptor;
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NDArray *_scalar = nullptr;
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virtual void registerTypes();
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/**
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* This method executes this Op, and defined for most of individual ops separately
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*/
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virtual Nd4jStatus validateAndExecute(Context& block) = 0;
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/**
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* This method ensures that target variable has enough space for op execution
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*
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* TODO: we want workspaces support right here
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*/
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bool allocateResult(Context& block, std::initializer_list<Nd4jLong>& shape, char order = 'c');
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bool allocateResult(Context& block, Nd4jLong* shape);
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/**
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* This method overwrites existen NDArray or NDArrayList in VariableSpace
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*
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* PLEASE NOTE: This method is dangerous.
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*
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* @param block
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* @param numOutput
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* @param array
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*/
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void overwriteResult(Context& block, int outputIdx, NDArray* array);
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void overwriteResult(Context& block, int outputIdx, NDArrayList* list);
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/*
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* This method attaches array to specific Variable, identified by node ID and outputNumber (which is output index for multi-output operations)
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*/
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void storeResult(Context &block, int outputNumber, NDArray& array);
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void storeResult(Context &block, int outputNumber, NDArray* array);
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nd4j::NDArray* getZ(Context& block, int inputId = 0);
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/**
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* This method pre-allocates NDArrays for Op output, in case they are not available at op execution time
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*/
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int prepareOutputs(Context& block);
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//std::vector<int>* calculateOutputShape(std::vector<int>* inputShape, nd4j::graph::Block<T>& block);
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public:
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// for special cases, like BooleanOps
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DeclarableOp();
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DeclarableOp(const char *name, int numInputs, bool scalar);
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// regular constructors
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DeclarableOp(int numInputs, int numOutputs, const char *opName, bool allowsInplace);
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DeclarableOp(int numInputs, int numOutputs, const char *opName, bool allowsInplace, bool divergent);
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DeclarableOp(int numInputs, int numOutputs, const char *opName, bool allowsInplace, int tArgs, int iArgs);
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// for LogicalOps
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DeclarableOp(const char *name, bool isLogical);
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// default testructor
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~DeclarableOp();
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// this method returns OpDescriptor, describing this Op instance
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OpDescriptor *getOpDescriptor();
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Nd4jStatus validateDataTypes(Context& block);
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/**
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* This method should be available in each implemented Op, and should return Op output shape(s), for a given input shape(s)
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*/
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virtual ShapeList* calculateOutputShape(ShapeList* inputShape, nd4j::graph::Context& block) = 0;
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/**
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* Returns opName
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*
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* @return
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*/
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std::string *getOpName();
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/**
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* Returns opHash
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*/
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Nd4jLong getOpHash();
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/**
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* This method sets arguments for op
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*/
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// void setArguments();
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/**
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* This method returns pointer to results
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*/
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// void getResults();
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/**
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* This method executes given Op
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*
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* @param block
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* @return 0 if OK, error code otherwise
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*/
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virtual Nd4jStatus execute(Context* block);
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nd4j::ResultSet* execute(std::initializer_list<NDArray*> inputs, std::initializer_list<double> tArgs, std::initializer_list<Nd4jLong> iArgs, std::initializer_list<bool> bArgs, bool isInplace = false, nd4j::DataType type = nd4j::DataType::FLOAT32);
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Nd4jStatus execute(std::initializer_list<NDArray*> inputs, std::initializer_list<NDArray*> outputs , std::initializer_list<double> tArgs, std::initializer_list<Nd4jLong> iArgs, std::initializer_list<bool> bArgs, bool isInplace = false, nd4j::DataType type = nd4j::DataType::FLOAT32);
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Nd4jStatus execute(nd4j::graph::RandomGenerator& rng, std::initializer_list<NDArray*> inputs, std::initializer_list<NDArray*> outputs , std::initializer_list<double> tArgs, std::initializer_list<Nd4jLong> iArgs, std::initializer_list<bool> bArgs, bool isInplace = false, nd4j::DataType type = nd4j::DataType::FLOAT32);
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nd4j::ResultSet* execute(const std::vector<NDArray*>& inputs, const std::vector<double>& tArgs, const std::vector<Nd4jLong>& iArgs, const std::vector<bool>& bArgs = std::vector<bool>(), bool isInplace = false, nd4j::DataType type = nd4j::DataType::FLOAT32);
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Nd4jStatus execute(std::vector<NDArray*>& inputs, std::vector<NDArray*>& outputs , std::vector<double>& tArgs, std::vector<Nd4jLong>& iArgs, std::vector<bool>& bArgs, bool isInplace = false, nd4j::DataType type = nd4j::DataType::FLOAT32);
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Nd4jStatus execute(nd4j::graph::RandomGenerator& rng, std::vector<NDArray*>& inputs, std::vector<NDArray*>& outputs, std::vector<double>& tArgs, std::vector<Nd4jLong>& iArgs, std::vector<bool>& bArgs, bool isInplace = false, nd4j::DataType type = nd4j::DataType::FLOAT32);
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nd4j::ResultSet* execute(const nd4j::OpArgsHolder& holder, bool isInplace = false);
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// There methods provide various validation options
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Nd4jStatus validateNonEmptyInput(Context& block);
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// this method checks if all input arrays have equal lengths
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Nd4jStatus validateInputLengthMatch(Context& block);
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// this method checks if all input arrays have the same shapes (orders/strides are NOT checked)
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Nd4jStatus validateInputDimensionsMatch(Context& block);
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// this method check if all input arrays have the same orders
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Nd4jStatus validateOrdersMatch(Context& block);
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// this method checks if all input arrays are 2D
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Nd4jStatus validateInput2D(Context& block);
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// this method checks if all input arrays are 3D
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Nd4jStatus validateInput3D(Context& block);
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// this method checks if all input arrays are 4D
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Nd4jStatus validateInput4D(Context& block);
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// this method checks if all input arrays are ND
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Nd4jStatus validateInputDimensions(Context& block, int rank);
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// this method checks if number of available arguments matches op expectations
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Nd4jStatus validateArguments(Context& block);
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};
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}
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}
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#endif //LIBND4J_DECLARABLE_OPS_H
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