cavis/libnd4j/include/ops/declarable/impl/BooleanOp.cpp

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/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://www.apache.org/licenses/LICENSE-2.0.
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations
* under the License.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// Created by raver119 on 13.10.2017.
//
#include "ops/declarable/BooleanOp.h"
#include <vector>
#include <initializer_list>
#include <NDArrayFactory.h>
namespace nd4j {
namespace ops {
BooleanOp::BooleanOp(const char *name, int numInputs, bool scalar) : DeclarableOp::DeclarableOp(name, numInputs, scalar) {
//
}
BooleanOp::~BooleanOp() {
//
}
/**
* Output shape of any BooleanOp is ALWAYS scalar
*/
ShapeList *BooleanOp::calculateOutputShape(ShapeList *inputShape, nd4j::graph::Context &block) {
return SHAPELIST(ConstantShapeHelper::getInstance()->scalarShapeInfo(DataType::BOOL));
}
bool BooleanOp::evaluate(nd4j::graph::Context &block) {
// check if scalar or not
// validation?
Nd4jStatus status = this->validateNonEmptyInput(block);
if (status != ND4J_STATUS_OK) {
nd4j_printf("Inputs should be not empty for BooleanOps","");
throw std::runtime_error("Bad inputs");
}
status = this->validateAndExecute(block);
if (status == ND4J_STATUS_TRUE)
return true;
else if (status == ND4J_STATUS_FALSE)
return false;
else {
nd4j_printf("Got error %i during [%s] evaluation: ", (int) status, this->getOpDescriptor()->getOpName()->c_str());
throw std::runtime_error("Internal error");
}
}
bool BooleanOp::evaluate(std::initializer_list<nd4j::NDArray *> args) {
std::vector<nd4j::NDArray *> vec(args);
return this->evaluate(vec);
}
bool BooleanOp::prepareOutputs(Context& ctx) {
auto variableSpace = ctx.getVariableSpace();
if (ctx.isFastPath())
return true;
for (int e = 0; e < this->getOpDescriptor()->getNumberOfOutputs(); e++) {
std::pair<int, int> pair(ctx.nodeId(), e);
if (!variableSpace->hasVariable(pair))
variableSpace->putVariable(pair, new Variable());
auto var = ctx.variable(pair);
if (!var->hasNDArray()) {
var->setNDArray(NDArrayFactory::create_<bool>(false, ctx.launchContext()));
var->markRemovable(true);
}
}
return true;
}
Nd4jStatus nd4j::ops::BooleanOp::execute(Context* block) {
// basic validation: ensure inputs are set
REQUIRE_OK(this->validateNonEmptyInput(*block));
// ensure number of IArgs, TArgs match our expectations
REQUIRE_OK(this->validateArguments(*block));
// this method will allocate output NDArrays for this op
this->prepareOutputs(*block);
auto timeStart = std::chrono::system_clock::now();
Nd4jStatus status = this->validateAndExecute(*block);
auto timeEnd = std::chrono::system_clock::now();
auto outerTime = std::chrono::duration_cast<std::chrono::nanoseconds> (timeEnd - timeStart).count();
block->setInnerTime(outerTime);
// basically we're should be putting 0.0 as FALSE, and any non-0.0 value will be treated as TRUE
std::pair<int,int> p(block->nodeId(), 0);
auto var = block->isFastPath() ? block->fastpath_out()[0] : block->variable(p)->getNDArray();
var->p(Nd4jLong(0), status == ND4J_STATUS_TRUE ? 1.0f : 0.0f);
[WIP] More of CUDA (#95) * initial commit Signed-off-by: raver119 <raver119@gmail.com> * Implementation of hashcode cuda helper. Working edition. * Fixed parallel test input arangements. * Fixed tests for hashcode op. * Fixed shape calculation for image:crop_and_resize op and test. * NativeOps tests. Initial test suite. * Added tests for indexReduce methods. * Added test on execBroadcast with NDArray as dimensions. * Added test on execBroadcastBool with NDArray as dimensions. * Added tests on execPairwiseTransform and execPairwiseTransofrmBool. * Added tests for execReduce with scalar results. * Added reduce tests for non-empty dims array. * Added tests for reduce3. * Added tests for execScalar. * Added tests for execSummaryStats. * - provide cpu/cuda code for batch_to_space - testing it Signed-off-by: Yurii <yurii@skymind.io> * - remove old test for batch_to_space (had wrong format and numbers were not checked) Signed-off-by: Yurii <yurii@skymind.io> * Fixed complilation errors with test. * Added test for execTransformFloat. * Added test for execTransformSame. * Added test for execTransformBool. * Added test for execTransformStrict. * Added tests for execScalar/execScalarBool with TADs. * Added test for flatten. * - provide cpu/cuda code for space_to_Batch operaion Signed-off-by: Yurii <yurii@skymind.io> * Added test for concat. * comment unnecessary stuff in s_t_b Signed-off-by: Yurii <yurii@skymind.io> * Added test for specialConcat. * Added tests for memcpy/set routines. * Fixed pullRow cuda test. * Added pullRow test. * Added average test. * - correct typo in NDArray::applyPairwiseTransform(nd4j::pairwise::BoolOps op...) Signed-off-by: Yurii <yurii@skymind.io> * - debugging and fixing cuda tests in JavaInteropTests file Signed-off-by: Yurii <yurii@skymind.io> * - correct some tests Signed-off-by: Yurii <yurii@skymind.io> * Added test for shuffle. * Fixed ops declarations. * Restored omp and added shuffle test. * Added convertTypes test. * Added tests for execRandom. Eliminated usage of RandomBuffer with NativeOps. * Added sort tests. * Added tests for execCustomOp. * - further debuging and fixing tests terminated with crash Signed-off-by: Yurii <yurii@skymind.io> * Added tests for calculateOutputShapes. * Addded Benchmarks test. * Commented benchmark tests. * change assertion Signed-off-by: raver119 <raver119@gmail.com> * Added tests for apply_sgd op. Added cpu helper for that op. * Implement cuda helper for aplly_sgd op. Fixed tests for NativeOps. * Added test for assign broadcastable. * Added tests for assign_bp op. * Added tests for axpy op. * - assign/execScalar/execTransformAny signature change - minor test fix Signed-off-by: raver119 <raver119@gmail.com> * Fixed axpy op. * meh Signed-off-by: raver119 <raver119@gmail.com> * - fix tests for nativeOps::concat Signed-off-by: Yurii <yurii@skymind.io> * sequential transform/scalar Signed-off-by: raver119 <raver119@gmail.com> * allow nested parallelism Signed-off-by: raver119 <raver119@gmail.com> * assign_bp leak fix Signed-off-by: raver119 <raver119@gmail.com> * block setRNG fix Signed-off-by: raver119 <raver119@gmail.com> * enable parallelism by default Signed-off-by: raver119 <raver119@gmail.com> * enable nested parallelism by default Signed-off-by: raver119 <raver119@gmail.com> * Added cuda implementation for row_count helper. * Added implementation for tnse gains op helper. * - take into account possible situations when input arrays are empty in reduce_ cuda stuff Signed-off-by: Yurii <yurii@skymind.io> * Implemented tsne/edge_forces op cuda-based helper. Parallelized cpu-based helper for edge_forces. * Added kernel for tsne/symmetrized op heleper. * Implementation of tsne/symmetrized op cuda helper. Working edition. * Eliminated waste printfs. * Added test for broadcastgradientargs op. * host-only fallback for empty reduce float Signed-off-by: raver119 <raver119@gmail.com> * - some tests fixes Signed-off-by: Yurii <yurii@skymind.io> * - correct the rest of reduce_ stuff Signed-off-by: Yurii <yurii@skymind.io> * - further correction of reduce_ stuff Signed-off-by: Yurii <yurii@skymind.io> * Added test for Cbow op. Also added cuda implementation for cbow helpers. * - improve code of stack operation for scalar case Signed-off-by: Yurii <yurii@skymind.io> * - provide cuda kernel for gatherND operation Signed-off-by: Yurii <yurii@skymind.io> * Implementation of cbow helpers with cuda kernels. * minor tests tweaks Signed-off-by: raver119 <raver119@gmail.com> * minor tests tweaks Signed-off-by: raver119 <raver119@gmail.com> * - further correction of cuda stuff Signed-off-by: Yurii <yurii@skymind.io> * Implementatation of cbow op helper with cuda kernels. Working edition. * Skip random testing for cudablas case. * lstmBlockCell context fix Signed-off-by: raver119 <raver119@gmail.com> * Added tests for ELU and ELU_BP ops. * Added tests for eq_scalar, gt_scalar, gte_scalar and lte_scalar ops. * Added tests for neq_scalar. * Added test for noop. * - further work on clipbynorm_bp Signed-off-by: Yurii <yurii@skymind.io> * - get rid of concat op call, use instead direct concat helper call Signed-off-by: Yurii <yurii@skymind.io> * lstmBlockCell context fix Signed-off-by: raver119 <raver119@gmail.com> * Added tests for lrelu and lrelu_bp. * Added tests for selu and selu_bp. * Fixed lrelu derivative helpers. * - some corrections in lstm Signed-off-by: Yurii <yurii@skymind.io> * operator * result shape fix Signed-off-by: raver119 <raver119@gmail.com> * - correct typo in lstmCell Signed-off-by: Yurii <yurii@skymind.io> * few tests fixed Signed-off-by: raver119 <raver119@gmail.com> * CUDA inverse broadcast bool fix Signed-off-by: raver119 <raver119@gmail.com> * disable MMAP test for CUDA Signed-off-by: raver119 <raver119@gmail.com> * BooleanOp syncToDevice Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * additional data types for im2col/col2im Signed-off-by: raver119 <raver119@gmail.com> * Added test for firas_sparse op. * one more RandomBuffer test excluded Signed-off-by: raver119 <raver119@gmail.com> * Added tests for flatten op. * Added test for Floor op. * bunch of tests fixed Signed-off-by: raver119 <raver119@gmail.com> * mmulDot tests fixed Signed-off-by: raver119 <raver119@gmail.com> * more tests fixed Signed-off-by: raver119 <raver119@gmail.com> * Implemented floordiv_bp op and tests. * Fixed scalar case with cuda implementation for bds. * - work on cuda kernel for clip_by_norm backprop op is completed Signed-off-by: Yurii <yurii@skymind.io> * Eliminate cbow crach. * more tests fixed Signed-off-by: raver119 <raver119@gmail.com> * more tests fixed Signed-off-by: raver119 <raver119@gmail.com> * Eliminated abortion with batched nlp test. * more tests fixed Signed-off-by: raver119 <raver119@gmail.com> * Fixed shared flag initializing. * disabled bunch of cpu workspaces tests Signed-off-by: raver119 <raver119@gmail.com> * scalar operators fix: missing registerSpecialUse call Signed-off-by: raver119 <raver119@gmail.com> * Fixed logdet for cuda and tests. * - correct clipBynorm_bp Signed-off-by: Yurii <yurii@skymind.io> * Fixed crop_and_resize shape datatype. * - correct some mmul tests Signed-off-by: Yurii <yurii@skymind.io>
2019-08-02 19:01:03 +02:00
// for CPU backend that's nop, but for CUDA-like archs this will update special buffer
var->syncToDevice();
2019-06-06 14:21:15 +02:00
if (status == ND4J_STATUS_FALSE || status == ND4J_STATUS_TRUE)
return ND4J_STATUS_OK;
nd4j_printf("%s: node_%i got unexpected result instead of boolean: [%i]\n", this->getOpName()->c_str(), block->nodeId(), status);
return ND4J_STATUS_KERNEL_FAILURE;
}
bool BooleanOp::evaluate(std::vector<nd4j::NDArray *> &args) {
VariableSpace variableSpace;
int cnt = -1;
std::vector<int> in;
for (auto v: args) {
auto var = new Variable(v);
var->markRemovable(false);
in.push_back(cnt);
variableSpace.putVariable(cnt--, var);
}
Context block(1, &variableSpace, false);
block.fillInputs(in);
return this->evaluate(block);
}
}
}