2019-06-06 14:21:15 +02:00
|
|
|
/*******************************************************************************
|
|
|
|
* 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, Test_IsMax_1) {
|
|
|
|
if (!Environment::getInstance()->isCPU())
|
|
|
|
return;
|
|
|
|
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {2, 2, 2, 2, 2, 2});
|
|
|
|
auto z = NDArrayFactory::create<double>('c', {2, 2, 2, 2, 2, 2});
|
|
|
|
x.linspace(1.0);
|
|
|
|
z.assign(-589);
|
|
|
|
|
|
|
|
double extra[] = {1.0, 0.0};
|
|
|
|
|
|
|
|
NativeOpExecutioner::execTransformAny(nullptr, transform::IsMax, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
|
|
|
|
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(), extra, nullptr, nullptr);
|
|
|
|
|
|
|
|
// z.printIndexedBuffer("z");
|
|
|
|
for (int e = 0; e < z.lengthOf(); e++) {
|
|
|
|
ASSERT_TRUE(z.e<double>(e) >= 0);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST_F(LegacyOpsTests, Test_IsMax_2) {
|
|
|
|
if (!Environment::getInstance()->isCPU())
|
|
|
|
return;
|
|
|
|
|
|
|
|
auto x = NDArrayFactory::create<double>('c', {2, 2, 2, 2, 2, 2});
|
|
|
|
auto z = NDArrayFactory::create<bool>('c', {2, 2, 2, 2, 2, 2});
|
|
|
|
x.linspace(1.0);
|
|
|
|
z.assign(false);
|
|
|
|
|
|
|
|
double extra[] = {1.0, 0.0};
|
|
|
|
|
|
|
|
NativeOpExecutioner::execTransformAny(nullptr, transform::IsMax, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
|
|
|
|
z.buffer(), z.shapeInfo(), z.specialBuffer(), z.specialShapeInfo(), extra, nullptr, nullptr);
|
|
|
|
|
|
|
|
// z.printIndexedBuffer("z");
|
|
|
|
for (int e = 0; e < z.lengthOf(); e++) {
|
|
|
|
if (e >= z.lengthOf() / 2)
|
|
|
|
ASSERT_TRUE(z.e<bool>(e));
|
|
|
|
else
|
|
|
|
ASSERT_FALSE(z.e<bool>(e));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
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::TAD tad;
|
|
|
|
tad.init(y.shapeInfo(), &axis, 1);
|
|
|
|
tad.createTadOnlyShapeInfo();
|
|
|
|
tad.createOffsets();
|
|
|
|
|
|
|
|
shape::printShapeInfoLinear("tad shape", tad.tadOnlyShapeInfo);
|
|
|
|
|
|
|
|
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, tad.tadOnlyShapeInfo, tad.tadOffsets, tad.tadOnlyShapeInfo, tad.tadOffsets);
|
|
|
|
|
|
|
|
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));
|
|
|
|
}
|
|
|
|
|
|
|
|
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);
|
|
|
|
|
|
|
|
float distancesAssertion[4] = {0.0,8.0,16.0,24.0};
|
|
|
|
for(int i = 0; i < 4; i++)
|
|
|
|
ASSERT_EQ(distancesAssertion[i],result[i]);
|
|
|
|
|
|
|
|
delete[] shapeBuffer;
|
|
|
|
delete[] xShapeBuffer;
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
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});
|
|
|
|
|
2019-07-22 13:34:08 +02:00
|
|
|
execReduce3Tad(nullptr, 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(),
|
2019-06-06 14:21:15 +02:00
|
|
|
nullptr, nullptr, nullptr, nullptr);
|
|
|
|
}
|
|
|
|
|
|
|
|
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});
|
|
|
|
|
|
|
|
|
2019-07-22 13:34:08 +02:00
|
|
|
execReduce3Tad(nullptr, reduce3::CosineDistance,
|
2019-06-06 14:21:15 +02:00
|
|
|
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(),
|
|
|
|
nullptr, nullptr, nullptr, nullptr);
|
|
|
|
|
|
|
|
// z.printIndexedBuffer("z");
|
|
|
|
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
}
|
|
|
|
|
|
|
|
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});
|
|
|
|
|
|
|
|
|
2019-07-22 13:34:08 +02:00
|
|
|
execReduce3Tad(nullptr, reduce3::CosineDistance,
|
2019-06-06 14:21:15 +02:00
|
|
|
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(),
|
|
|
|
nullptr, nullptr, nullptr, nullptr);
|
|
|
|
|
|
|
|
// z.printIndexedBuffer("z");
|
|
|
|
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
}
|
|
|
|
|
|
|
|
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});
|
|
|
|
|
|
|
|
|
2019-07-22 13:34:08 +02:00
|
|
|
execReduce3Tad(nullptr, reduce3::CosineDistance,
|
2019-06-06 14:21:15 +02:00
|
|
|
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(),
|
|
|
|
nullptr, nullptr, nullptr, nullptr);
|
|
|
|
|
|
|
|
z.printIndexedBuffer("z");
|
|
|
|
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
}
|
|
|
|
|
|
|
|
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);
|
|
|
|
|
2019-07-22 13:34:08 +02:00
|
|
|
execReduce3All(nullptr, reduce3::EuclideanDistance, x.buffer(), x.shapeInfo(), x.specialBuffer(), x.specialShapeInfo(),
|
2019-06-06 14:21:15 +02:00
|
|
|
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());
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
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);
|
|
|
|
|
|
|
|
y.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, 0,
|
|
|
|
tadPackY.platformShapeInfo(), tadPackY.platformOffsets(),
|
|
|
|
tadPackY.platformShapeInfo(), tadPackY.platformOffsets());
|
|
|
|
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
|
|
|
|
delete row;
|
|
|
|
delete erow;
|
2019-06-15 13:34:34 +02:00
|
|
|
}
|
|
|
|
|
|
|
|
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.shapeInfo(), 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.shapeInfo(), 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.shapeInfo(), nullptr);
|
|
|
|
|
|
|
|
ASSERT_EQ(e, z);
|
|
|
|
}
|
|
|
|
|
|
|
|
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);
|
2019-07-22 13:34:08 +02:00
|
|
|
}
|