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cavis/libnd4j/tests_cpu/layers_tests/LegacyOpsTests.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 16.10.2017.
//
#include "testlayers.h"
#include <NDArray.h>
#include <ShapeUtils.h>
#include <reduce3.h>
#include <ops/declarable/LegacyTransformOp.h>
#include <ops/declarable/LegacyPairwiseTransformOp.h>
#include <ops/declarable/LegacyScalarOp.h>
#include <ops/declarable/LegacyReduceSameOp.h>
#include <ops/declarable/LegacyReduceFloatOp.h>
#include <ops/declarable/LegacyIndexReduceOp.h>
#include <ops/declarable/LegacyBroadcastOp.h>
#include <helpers/TAD.h>
#include <helpers/ConstantTadHelper.h>
using namespace nd4j;
using namespace nd4j::ops;
class LegacyOpsTests : public testing::Test {
};
TEST_F(LegacyOpsTests, TransformTests_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(1.0);
auto z = NDArrayFactory::create<float>('c', {5,5});
auto exp = NDArrayFactory::create<float>('c', {5, 5});
exp.assign(-1.0);
nd4j::ops::LegacyTransformSameOp op(transform::Neg); // Neg
auto status = op.execute({&x}, {&z}, {}, {}, {});
ASSERT_EQ(status, ND4J_STATUS_OK);
//z.printIndexedBuffer("Output NEG");
ASSERT_TRUE(z.equalsTo(&exp));
}
TEST_F(LegacyOpsTests, TransformTests_2) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(1.0);
auto exp = NDArrayFactory::create<float>('c', {5, 5});
exp.assign(-1.0);
nd4j::ops::LegacyTransformSameOp op(transform::Neg); // Neg
auto result = op.execute({&x}, {}, {});
ASSERT_EQ(1, result->size());
auto z = result->at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, Reciprocal_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(2.0f);
auto ethalon = NDArrayFactory::create<float>('c', {5, 5});
ethalon.assign(0.5f);
nd4j::ops::LegacyTransformSameOp op(transform::Reciprocal); // Reciprocal
Nd4jStatus status = op.execute({&x}, {&x}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(ethalon.equalsTo(&x));
}
TEST_F(LegacyOpsTests, PWT_Tests_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(2.0);
auto y = NDArrayFactory::create<float>('c', {5, 5});
y.assign(3.0);
auto exp = NDArrayFactory::create<float>('c', {5, 5});
exp.assign(6.0);
nd4j::ops::LegacyPairwiseTransformOp op(pairwise::Multiply); // Multiply
Nd4jStatus status = op.execute({&x, &y}, {&x}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(exp.equalsTo(&x));
}
TEST_F(LegacyOpsTests, PWT_Tests_2) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(2.0);
auto y = NDArrayFactory::create<float>('c', {5, 5});
y.assign(3.0);
auto exp = NDArrayFactory::create<float>('c', {5, 5});
exp.assign(6.0);
nd4j::ops::LegacyPairwiseTransformOp op(pairwise::Multiply); // Multiply
auto result = op.execute({&x, &y}, {}, {});
auto z = result->at(0);
//z->printBuffer("Z");
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, Scalar_Test_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(2.0);
auto exp = NDArrayFactory::create<float>('c', {5, 5});
exp.assign(7.0);
nd4j::ops::LegacyScalarOp op(scalar::Add);
op.execute({&x}, {&x}, {5.0}, {}, {}); //
ASSERT_TRUE(exp.equalsTo(&x));
}
TEST_F(LegacyOpsTests, Scalar_Test_2) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(2.0);
auto exp = NDArrayFactory::create<float>('c', {5, 5});
exp.assign(7.0);
auto y = NDArrayFactory::create<float>(5.0f);
nd4j::ops::LegacyScalarOp op(scalar::Add, y);
auto result = op.execute({&x}, {}, {});
auto z = result->at(0);
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, ReduceTests_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(1.0);
int opNum = reduce::Sum;
nd4j::ops::LegacyReduceSameOp op(opNum);
auto result = op.execute({&x}, {}, {});
ASSERT_EQ(1, result->size());
auto z = result->at(0);
// z->printBuffer("ReduceTest1");
ASSERT_TRUE(z->isScalar());
ASSERT_NEAR(x.sumNumber().e<float>(0), z->e<float>(0), 1e-5f);
delete result;
}
TEST_F(LegacyOpsTests, ReduceTests_2) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(1.0);
nd4j::ops::LegacyReduceSameOp op(reduce::Sum);
auto axis = NDArrayFactory::create<Nd4jLong>('c', {1}, {1});
auto result = op.execute({&x, &axis}, {}, {});
ASSERT_EQ(1, result->size());
auto z = result->at(0);
auto exp = x.reduceAlongDimension(reduce::Sum, {1});
ASSERT_TRUE(exp->isSameShape(z));
ASSERT_TRUE(exp->equalsTo(z));
delete result;
delete exp;
}
TEST_F(LegacyOpsTests, ReduceTests_3) {
auto x = NDArrayFactory::create<float>('c', {3, 5});
x.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {1,1}, {1});
nd4j::ops::LegacyReduceSameOp op(reduce::Sum);
auto result = op.execute({&x, &indices}, {}, {});
auto z = result->at(0);
auto exp = x.reduceAlongDims(reduce::Sum,{1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, ReduceTests_4) {
auto x = NDArrayFactory::create<float>('c', {2, 3, 5});
x.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {1, 1}, {1});
nd4j::ops::LegacyReduceSameOp op(reduce::Sum);
auto result = op.execute({&x, &indices}, {}, {}, {true});
auto z = result->at(0);
auto exp = x.reduceAlongDims(reduce::Sum, {1}, true);
// indices.printShapeInfo("Indices shape");
ASSERT_EQ(ND4J_STATUS_OK, result->status());
// z->printIndexedBuffer("Output reduce 4");
// exp.printIndexedBuffer("Expected reduce 4");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, ReduceTests_5) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(1.0);
int opNum = reduce::Mean;
nd4j::ops::LegacyReduceFloatOp op(opNum);
ResultSet* result = op.execute({&x}, {}, {}, {}, false, nd4j::DataType::FLOAT32);
ASSERT_EQ(1, result->size());
auto z = result->at(0);
// z->printBuffer("ReduceTest1");
ASSERT_TRUE(z->isScalar());
ASSERT_NEAR(x.meanNumber().e<float>(0), z->e<float>(0), 1e-5f);
delete result;
}
TEST_F(LegacyOpsTests, ReduceTests_6) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.assign(1.0);
auto axis = NDArrayFactory::create<int>('c', {1}, {1});
nd4j::ops::LegacyReduceFloatOp op(reduce::Mean);
auto result = op.execute({&x, &axis}, {}, {});
ASSERT_EQ(1, result->size());
auto z = result->at(0);
auto exp = x.reduceAlongDimension(reduce::Mean, {1});
ASSERT_TRUE(exp->isSameShape(z));
ASSERT_TRUE(exp->equalsTo(z));
delete result;
delete exp;
}
TEST_F(LegacyOpsTests, ReduceTests_7) {
auto x = NDArrayFactory::create<float>('c', {3, 5});
x.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {1,1}, {1});
nd4j::ops::LegacyReduceFloatOp op(reduce::Mean);
auto result = op.execute({&x, &indices}, {}, {});
auto z = result->at(0);
auto exp = x.reduceAlongDims(reduce::Mean,{1});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, ReduceTests_8) {
auto x = NDArrayFactory::create<float>('c', {2, 3, 5});
x.linspace(1);
auto indices = NDArrayFactory::create<int>('c', {1}, {1});
nd4j::ops::LegacyReduceFloatOp op(reduce::Mean);
auto result = op.execute({&x, &indices}, {}, {}, {true});
auto z = result->at(0);
auto exp = x.reduceAlongDims(reduce::Mean, {1}, true);
ASSERT_EQ(ND4J_STATUS_OK, result->status());
// z->printIndexedBuffer("Reduce8 output");
// z->printShapeInfo("Reduce8 shape");
// exp.printShapeInfo("Reduce8 expected shape");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(LegacyOpsTests, IndexReduceTests_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
x.linspace(1);
nd4j::ops::LegacyIndexReduceOp op(indexreduce::IndexMax);
auto result = op.execute({&x}, {}, {});
ASSERT_EQ(1, result->size());
auto z = result->at(0);
ASSERT_TRUE(z->isScalar());
ASSERT_EQ(24, z->e<int>(0));
delete result;
}
TEST_F(LegacyOpsTests, IndexReduceTests_2) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
auto indices = NDArrayFactory::create<int>('c', {1}, {1});
x.linspace(1);
auto exp = NDArrayFactory::create<Nd4jLong>({4,4,4,4,4});
nd4j::ops::LegacyIndexReduceOp op(indexreduce::IndexMax);
auto result = op.execute({&x, &indices}, {}, {});
ASSERT_EQ(1, result->size());
auto z = result->at(0);
// z->printIndexedBuffer("Hello indexreduce2");
ASSERT_TRUE(exp.equalsTo(z));
//ASSERT_EQ(4, z->e<int>(0));
//ASSERT_EQ(4, z->e<int>(1));
//ASSERT_EQ(4, z->e<int>(2));
//ASSERT_EQ(4, z->e<int>(3));
//ASSERT_EQ(4, z->e<int>(4));
delete result;
}
TEST_F(LegacyOpsTests, BroadcastingTests_1) {
auto x = NDArrayFactory::create<double>('c', {5, 5});
x.assign(0.0f);
auto row = NDArrayFactory::create<double>('c', {1, 5});
row.linspace(1);
auto axis = NDArrayFactory::create<int>('c', {1}, {1});
nd4j::ops::LegacyBroadcastOp op(broadcast::Add);
Nd4jStatus status = op.execute({&x, &row, &axis}, {&x}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
auto list = x.allTensorsAlongDimension({1});
// x.printIndexedBuffer("Output broadcast");
// list->at(0)->printIndexedBuffer("Column 0:");
for (int e = 0; e < list->size(); e++)
ASSERT_TRUE(row.equalsTo(list->at(e)));
delete list;
}
TEST_F(LegacyOpsTests, BroadcastingTests_2) {
auto x = NDArrayFactory::create<double>('c', {5}, {1, 1, 1, 1, 1});
auto y = NDArrayFactory::create<double>('c', {10, 5});
auto e = NDArrayFactory::create<double>('c', {10, 5});
y.assign(3.0);
e.assign(4.0);
int axis = 1;
// shape::printShapeInfoLinear("tad shape", tad.tadOnlyShapeInfo);
auto packY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.shapeInfo(), {axis});
NDArray::prepareSpecialUse({&y}, {&x});
NativeOpExecutioner::execInverseBroadcast(LaunchContext::defaultContext(), broadcast::Add, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(), y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(), y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(), &axis, 1, packY.platformShapeInfo(), packY.platformOffsets(), packY.platformShapeInfo(), packY.platformOffsets());
NDArray::registerSpecialUse({&y}, {&x});
ASSERT_EQ(e, y);
}
TEST_F(LegacyOpsTests, PowDerivative_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
auto exp = NDArrayFactory::create<float>('c', {5, 5});
x.assign(3.f);
exp.assign(6.f);
float p = 2.0f;
x.applyScalar(scalar::PowDerivative, p);
ASSERT_TRUE(exp.equalsTo(&x));
}
#ifndef __CUDABLAS__
TEST_F(LegacyOpsTests, reduce3_1) {
Nd4jLong yShape[2] = {4,4};
Nd4jLong xShape[1] = {4};
float y[16] ={1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16};
float x[4] = {1,2,3,4};
int dimension[1] = {1};
int dimensionLength = 1;
int opNum = 1;
float extraVals[1] = {0};
float result[4] = {0.0,0.0,0.0,0.0};
std::vector<int> dim = {1};
auto shapeBuffer = nd4j::ShapeBuilders::createShapeInfo(nd4j::DataType::FLOAT32, 'c', 2, yShape);
auto xShapeBuffer = nd4j::ShapeBuilders::createShapeInfo(nd4j::DataType::FLOAT32, 'c', 1, xShape);
//int *tadShapeBuffer = shape::computeResultShape(shapeBuffer,dimension,dimensionLength);
auto tadShapeBuffer = nd4j::ShapeUtils::evalReduceShapeInfo('c', dim, shapeBuffer, false, true, nullptr);
functions::reduce3::Reduce3<float, float>::exec(opNum, x, xShapeBuffer, extraVals, y, shapeBuffer, result, tadShapeBuffer, dimension, dimensionLength, 0, 4);
float distancesAssertion[4] = {0.0,8.0,16.0,24.0};
for(int i = 0; i < 4; i++)
ASSERT_NEAR(distancesAssertion[i],result[i], 1e-5);
delete[] shapeBuffer;
delete[] xShapeBuffer;
}
#endif
TEST_F(LegacyOpsTests, Reduce3_2) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
auto y = NDArrayFactory::create<float>('c', {5});
auto z = NDArrayFactory::create<float>('c', {5});
auto dim = NDArrayFactory::create<int>('c', {1}, {1});
dim.syncToHost();
nd4j::LaunchContext* context = nd4j::LaunchContext::defaultContext();
Nd4jPointer* extraPointers = nullptr;
#ifdef __CUDABLAS__
extraPointers = new Nd4jPointer[7] {nullptr, context->getCudaStream(), context->getScalarPointer(), nullptr, context->getCudaSpecialStream(), context->getReductionPointer(), context->getAllocationPointer()};
#endif
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(x.getShapeInfo(), {1});
auto packY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.getShapeInfo(), {1});
NDArray::prepareSpecialUse({&z}, {&x, &y, &dim});
execReduce3Tad(extraPointers, reduce3::CosineSimilarity,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
nullptr, y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
dim.buffer(), dim.shapeInfo(), dim.specialBuffer(), dim.specialShapeInfo(),
packX.platformShapeInfo(), packX.platformOffsets(), packY.platformShapeInfo(), packY.platformOffsets());
NDArray::registerSpecialUse({&z}, {&x, &y, &dim});
delete []extraPointers;
}
TEST_F(LegacyOpsTests, Reduce3_3) {
auto x = NDArrayFactory::create<double>('c', {3, 5}, {-0.84443557262, -0.06822254508, 0.74266910552, 0.61765557527, -0.77555125951,
-0.99536740779, -0.0257304441183, -0.6512106060, -0.345789492130, -1.25485503673,
0.62955373525, -0.31357592344, 1.03362500667, -0.59279078245, 1.1914824247});
auto y = NDArrayFactory::create<double>('c', {5}, {-0.99536740779, -0.0257304441183, -0.6512106060, -0.345789492130, -1.25485503673});
auto e = NDArrayFactory::create<double>('c', {3}, {0.577452, 0.0, 1.80182});
auto z = NDArrayFactory::create<double>('c', {3});
auto dim = NDArrayFactory::create<int>('c', {1}, {1});
dim.syncToHost();
nd4j::LaunchContext* context = nd4j::LaunchContext::defaultContext();
Nd4jPointer* extraPointers = nullptr;
#ifdef __CUDABLAS__
extraPointers = new Nd4jPointer[7] {nullptr, context->getCudaStream(), context->getScalarPointer(), nullptr, context->getCudaSpecialStream(), context->getReductionPointer(), context->getAllocationPointer()};
#endif
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(x.getShapeInfo(), {1});
auto packY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.getShapeInfo(), {1});
NDArray::prepareSpecialUse({&z}, {&x, &y, &dim});
execReduce3Tad(extraPointers, reduce3::CosineDistance,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
nullptr,
y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
dim.buffer(), dim.shapeInfo(), dim.specialBuffer(), dim.specialShapeInfo(),
packX.platformShapeInfo(), packX.platformOffsets(), packY.platformShapeInfo(), packY.platformOffsets());
ASSERT_EQ(e, z);
NDArray::registerSpecialUse({&z}, {&x, &y, &dim});
delete []extraPointers;
}
TEST_F(LegacyOpsTests, Reduce3_4) {
auto x = NDArrayFactory::create<double>('c', {3, 5}, {-0.84443557262, -0.06822254508, 0.74266910552, 0.61765557527, -0.77555125951,
-0.99536740779, -0.0257304441183, -0.6512106060, -0.345789492130, -1.25485503673,
0.62955373525, -0.31357592344, 1.03362500667, -0.59279078245, 1.1914824247});
auto y = NDArrayFactory::create<double>('c', {1, 5}, {-0.99536740779, -0.0257304441183, -0.6512106060, -0.345789492130, -1.25485503673});
auto e = NDArrayFactory::create<double>('c', {1, 3}, {0.577452, 0.0, 1.80182});
auto z = NDArrayFactory::create<double>('c', {1, 3});
auto dim = NDArrayFactory::create<int>('c', {1}, {1});
dim.syncToHost();
nd4j::LaunchContext* context = nd4j::LaunchContext::defaultContext();
Nd4jPointer* extraPointers = nullptr;
#ifdef __CUDABLAS__
extraPointers = new Nd4jPointer[7] {nullptr, context->getCudaStream(), context->getScalarPointer(), nullptr, context->getCudaSpecialStream(), context->getReductionPointer(), context->getAllocationPointer()};
#endif
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(x.getShapeInfo(), {1});
auto packY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.getShapeInfo(), {1});
NDArray::prepareSpecialUse({&z}, {&x, &y, &dim});
execReduce3Tad(extraPointers, reduce3::CosineDistance,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
nullptr,
y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
dim.buffer(), dim.shapeInfo(), dim.specialBuffer(), dim.specialShapeInfo(),
packX.platformShapeInfo(), packX.platformOffsets(), packY.platformShapeInfo(), packY.platformOffsets());
// z.printIndexedBuffer("z");
NDArray::registerSpecialUse({&z}, {&x, &y, &dim});
ASSERT_EQ(e, z);
delete []extraPointers;
}
TEST_F(LegacyOpsTests, Reduce3_5) {
auto x = NDArrayFactory::create<double>('c', {3, 5}, {-0.84443557262, -0.06822254508, 0.74266910552, 0.61765557527, -0.77555125951,
-0.99536740779, -0.0257304441183, -0.6512106060, -0.345789492130, -1.25485503673,
0.62955373525, -0.31357592344, 1.03362500667, -0.59279078245, 1.1914824247});
auto y = NDArrayFactory::create<double>('c', {1, 5}, {-0.99536740779, -0.0257304441183, -0.6512106060, -0.345789492130, -1.25485503673});
auto e = NDArrayFactory::create<double>('c', {1, 3}, {0.577452, 0.0, 1.80182});
auto z = NDArrayFactory::create<double>('c', {1, 3});
auto dim = NDArrayFactory::create<int>('c', {1}, {1});
dim.syncToHost();
nd4j::LaunchContext* context = nd4j::LaunchContext::defaultContext();
Nd4jPointer* extraPointers = nullptr;
#ifdef __CUDABLAS__
extraPointers = new Nd4jPointer[7] {nullptr, context->getCudaStream(), context->getScalarPointer(), nullptr, context->getCudaSpecialStream(), context->getReductionPointer(), context->getAllocationPointer()};
#endif
auto packX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(x.getShapeInfo(), {1});
auto packY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.getShapeInfo(), {1});
NDArray::prepareSpecialUse({&z}, {&x, &y, &dim});
execReduce3Tad(extraPointers, reduce3::CosineDistance,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
nullptr,
y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
dim.buffer(), dim.shapeInfo(), dim.specialBuffer(), dim.specialShapeInfo(),
packX.platformShapeInfo(), packX.platformOffsets(), packY.platformShapeInfo(), packY.platformOffsets());
NDArray::registerSpecialUse({&z}, {&x, &y, &dim});
ASSERT_EQ(e, z);
delete []extraPointers;
}
TEST_F(LegacyOpsTests, test_Reduce3_All_1) {
auto x = NDArrayFactory::create<float>('c', {1000, 100});
auto y = NDArrayFactory::create<float>('c', {1, 100});
auto z = NDArrayFactory::create<float>('c', {1000, 1});
auto dim = NDArrayFactory::create<int>('c', {1}, {-1});
auto tadPackX = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(x.shapeInfo(), -1);
auto tadPackY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.shapeInfo(), -1);
nd4j::LaunchContext* context = nd4j::LaunchContext::defaultContext();
Nd4jPointer* extraPointers = nullptr;
#ifdef __CUDABLAS__
extraPointers = new Nd4jPointer[7] {nullptr, context->getCudaStream(), context->getScalarPointer(), nullptr, context->getCudaSpecialStream(), context->getReductionPointer(), context->getAllocationPointer()};
#endif
NDArray::prepareSpecialUse({&z}, {&x, &y});
execReduce3All(extraPointers, reduce3::EuclideanDistance, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
nullptr, y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
dim.buffer(), dim.shapeInfo(), dim.specialBuffer(), dim.specialShapeInfo(),
tadPackX.platformShapeInfo(), tadPackX.platformOffsets(),
tadPackY.platformShapeInfo(), tadPackY.platformOffsets());
NDArray::registerSpecialUse({&z}, {&x, &y});
delete []extraPointers;
}
TEST_F(LegacyOpsTests, test_inverse_broadcast_1) {
auto x = NDArrayFactory::create<float>('c', {4}, {2.0f, 2.0f, 2.0f, 2.0f});
auto y = NDArrayFactory::create<float>('c', {3, 4});
auto e = NDArrayFactory::create<float>('c', {3, 4});
e.assign(2.0f);
auto tadPackY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.shapeInfo(), 1);
y.tickWriteDevice();
NativeOpExecutioner::execInverseBroadcast(LaunchContext::defaultContext(), broadcast::Add,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
nullptr, 0,
tadPackY.platformShapeInfo(), tadPackY.platformOffsets(),
tadPackY.platformShapeInfo(), tadPackY.platformOffsets());
ASSERT_EQ(e, y);
}
TEST_F(LegacyOpsTests, test_inverse_broadcast_2) {
auto x = NDArrayFactory::create<float>('c', {4}, {2.0f, 2.0f, 2.0f, 2.0f});
auto y = NDArrayFactory::create<float>('c', {3, 4});
auto z = NDArrayFactory::create<bool>('c', {3, 4});
auto e = NDArrayFactory::create<bool>('c', {3, 4});
e.assign(false);
auto row = y.tensorAlongDimension(1, {1});
row->assign(2.0f);
auto erow = e.tensorAlongDimension(1, {1});
erow->assign(true);
auto tadPackY = nd4j::ConstantTadHelper::getInstance()->tadForDimensions(y.shapeInfo(), 1);
z.tickWriteDevice();
NativeOpExecutioner::execInverseBroadcastBool(LaunchContext::defaultContext(), broadcast::BoolOps::EqualTo,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
y.buffer(), y.shapeInfo(), y.specialBuffer(), y.specialShapeInfo(),
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
nullptr,
nullptr, 0,
tadPackY.platformShapeInfo(), tadPackY.platformOffsets(),
tadPackY.platformShapeInfo(), tadPackY.platformOffsets());
ASSERT_EQ(e, z);
delete row;
delete erow;
}
TEST_F(LegacyOpsTests, test_legacy_reduce_empty_1) {
auto x = NDArrayFactory::create<float>('c', {2, 0, 3});
auto z = NDArrayFactory::create<float>('c', {2, 3});
auto e = NDArrayFactory::create<float>('c', {2, 3});
int dim = 1;
NativeOpExecutioner::execReduceSame(LaunchContext::defaultContext(), reduce::SameOps::Sum,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
nullptr,
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
&dim, 1, x.getPlatformShapeInfo(), nullptr);
ASSERT_EQ(e, z);
}
TEST_F(LegacyOpsTests, test_legacy_reduce_empty_2) {
auto x = NDArrayFactory::create<float>('c', {2, 0, 3});
auto z = NDArrayFactory::create<float>('c', {2, 3});
auto e = NDArrayFactory::create<float>('c', {2, 3});
e.assign(std::numeric_limits<float>::infinity());
int dim = 1;
NativeOpExecutioner::execReduceSame(LaunchContext::defaultContext(), reduce::SameOps::Min, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(), nullptr, z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(), &dim, 1, x.getPlatformShapeInfo(), nullptr);
ASSERT_EQ(e, z);
}
TEST_F(LegacyOpsTests, test_legacy_reduce_empty_3) {
auto x = NDArrayFactory::create<float>('c', {2, 0, 3});
auto z = NDArrayFactory::create<float>('c', {2, 3});
auto e = NDArrayFactory::create<float>('c', {2, 3});
e.assign(-std::numeric_limits<float>::infinity());
int dim = 1;
NativeOpExecutioner::execReduceSame(LaunchContext::defaultContext(), reduce::SameOps::Max, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(), nullptr, z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(), &dim, 1, x.getPlatformShapeInfo(), nullptr);
ASSERT_EQ(e, z);
}
TEST_F(LegacyOpsTests, test_legacy_reduce_empty_4) {
if (!Environment::getInstance()->isCPU())
return;
int a = 0;
auto x = NDArrayFactory::create<float>('c', {1, 0, 2});
auto d = NDArrayFactory::create<int>('c', {1}, {a});
auto z = NDArrayFactory::create<float>('c', {0, 2});
auto e = NDArrayFactory::create<float>('c', {0, 2});
::execReduceSame2(nullptr, reduce::SameOps::Sum,
x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
nullptr,
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(),
d.buffer(), d.shapeInfo(), d.specialBuffer(), d.specialShapeInfo());
}
TEST_F(LegacyOpsTests, test_legacy_transform_float_1) {
auto x = NDArrayFactory::create<float>('c', {1, 0, 4});
NativeOpExecutioner::execTransformFloat(LaunchContext::defaultContext(), transform::FloatOps::RSqrt, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(), x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(), nullptr, nullptr, nullptr);
}
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