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cavis/libnd4j/tests_cpu/layers_tests/BroadcastableOpsTests.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 23.11.17.
//
#include "testlayers.h"
#include <Graph.h>
#include <Node.h>
#include <ops/declarable/CustomOperations.h>
using namespace nd4j;
using namespace nd4j::graph;
class BroadcastableOpsTests : public testing::Test {
public:
};
TEST_F(BroadcastableOpsTests, Test_Add_1) {
NDArray x('c', {5, 5}, nd4j::DataType::FLOAT32);
NDArray y('c', {1, 5}, nd4j::DataType::FLOAT32);
NDArray exp('c', {5, 5}, nd4j::DataType::FLOAT32);
x.linspace(1);
y.linspace(1);
exp.linspace(1);
//exp.printIndexedBuffer("E B");
exp.applyBroadcast(broadcast::Add, {1}, y, exp);
nd4j::ops::add op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
//exp.printIndexedBuffer("E A");
//z->printIndexedBuffer("Z");
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Multiply_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
auto y = NDArrayFactory::create<float>('c', {1, 5});
auto exp = NDArrayFactory::create<float>('c', {5, 5});
x.linspace(1);
y.linspace(1);
exp.linspace(1);
exp.applyBroadcast(broadcast::Multiply, {1}, y, exp);
nd4j::ops::multiply op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_SquaredSubtract_1) {
auto x = NDArrayFactory::create<float>('c', {5, 5});
auto y = NDArrayFactory::create<float>('c', {1, 5});
auto exp = NDArrayFactory::create<float>('c', {5, 5});
x.linspace(1);
y.linspace(1);
exp.linspace(1);
exp.applyBroadcast(broadcast::SquaredSubtract, {1}, y, exp);
nd4j::ops::squaredsubtract op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_ScalarBroadcast_1) {
auto x = NDArrayFactory::create<float>('c', {1, 1}, {1});
auto y = NDArrayFactory::create<float>('c', {1, 3}, {0, 1, 2});
auto exp = NDArrayFactory::create<float>('c', {1,3}, {1, 0, -1});
nd4j::ops::subtract op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_ScalarBroadcast_2) {
auto x = NDArrayFactory::create<float>('c', {1, 1}, {1});
auto y = NDArrayFactory::create<float>('c', {1, 3}, {0, 1, 2});
auto exp = NDArrayFactory::create<float>('c', {1,3}, {1, 2, 3});
nd4j::ops::add op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Maximum_1) {
auto x = NDArrayFactory::create<float>('c', {2, 3}, {1, 2, 1, 2, 3, 2});
auto row = NDArrayFactory::create<float>('c', {1, 3}, {2, 2, 2});
auto exp = NDArrayFactory::create<float>('c', {2, 3}, {2, 2, 2, 2, 3, 2});
nd4j::ops::maximum op;
auto result = op.evaluate({&x, &row});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Minimum_1) {
auto x = NDArrayFactory::create<float>('c', {2, 3}, {1, 2, 1, 2, 3, 2});
auto col = NDArrayFactory::create<float>('c', {2, 1}, {2, 1});
auto exp = NDArrayFactory::create<float>('c', {2, 3}, {1, 2, 1, 1, 1, 1});
nd4j::ops::minimum op;
auto result = op.evaluate({&x, &col});
ASSERT_EQ(ND4J_STATUS_OK, result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Shape_1) {
nd4j::ops::minimum op;
Nd4jLong shapeX[] = {2, 2, 5, 5, 1, 8192, 1, 99};
Nd4jLong shapeY[] = {2, 2, 5, 5, 1, 8192, 1, 99};
ShapeList inputShape({shapeX, shapeY});
VariableSpace vs;
Context ctx(1, &vs, false);
auto shapes = op.calculateOutputShape(&inputShape, ctx);
auto shapeZ = shapes->at(0);
ASSERT_TRUE(shape::shapeEquals(shapeX, shapeZ));
delete shapes;
}
TEST_F(BroadcastableOpsTests, Test_Shape_2) {
nd4j::ops::minimum op;
Nd4jLong shapeX[] = {2, 1, 1, 1, 1, 8192, 1, 99};
Nd4jLong shapeY[] = {2, 2, 5, 5, 1, 8192, 1, 99};
ShapeList inputShape({shapeX, shapeY});
VariableSpace vs;
Context ctx(1, &vs, false);
auto shapes = op.calculateOutputShape(&inputShape, ctx);
auto shapeZ = shapes->at(0);
ASSERT_TRUE(shape::shapeEquals(shapeY, shapeZ));
delete shapes;
}
TEST_F(BroadcastableOpsTests, Test_Shape_3) {
nd4j::ops::minimum op;
Nd4jLong shapeX[] = {2, 5, 3, 1, 1, 8192, 1, 99};
Nd4jLong shapeY[] = {2, 1, 3, 3, 1, 8192, 1, 99};
ShapeList inputShape({shapeX, shapeY});
VariableSpace vs;
Context ctx(1, &vs, false);
auto shapes = op.calculateOutputShape(&inputShape, ctx);
auto shapeZ = shapes->at(0);
ASSERT_TRUE(shape::shapeEquals(shapeX, shapeZ));
delete shapes;
}
TEST_F(BroadcastableOpsTests, Test_Shape_4) {
nd4j::ops::minimum op;
Nd4jLong shapeX[] = {2, 5, 3, 1, 1, 8192, 1, 99};
Nd4jLong shapeY[] = {2, 5, 1, 1, 1, 8192, 1, 99};
ShapeList inputShape({shapeX, shapeY});
VariableSpace vs;
Context ctx(1, &vs, false);
auto shapes = op.calculateOutputShape(&inputShape, ctx);
auto shapeZ = shapes->at(0);
ASSERT_TRUE(shape::shapeEquals(shapeX, shapeZ));
delete shapes;
}
// (2,1,3) + (4,3) = (2,4,3)
TEST_F(BroadcastableOpsTests, Test_Shape_5) {
nd4j::ops::minimum op;
Nd4jLong shapeX[] = {3, 2, 1, 3, 3, 3, 1, 8192, 1, 99};
Nd4jLong shapeY[] = {2, 4, 3, 3, 1, 8192, 1, 99};
Nd4jLong shapeE[] = {3, 2, 4, 3, 12, 3, 1, 8192, 1, 99};
ShapeList inputShape({shapeX, shapeY});
VariableSpace vs;
Context ctx(1, &vs, false);
auto shapes = op.calculateOutputShape(&inputShape, ctx);
auto shapeZ = shapes->at(0);
ASSERT_TRUE(shape::shapeEquals(shapeE, shapeZ));
delete shapes;
}
TEST_F(BroadcastableOpsTests, Test_Scalar_Add_1) {
auto x = NDArrayFactory::create<float>('c', {2, 2}, {1, 2, 3, 4});
auto y = NDArrayFactory::create<float>(2.0f);
auto exp = NDArrayFactory::create<float>('c', {2, 2}, {3, 4, 5, 6});
nd4j::ops::add op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(exp.isSameShape(z));
ASSERT_TRUE(exp.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Inplace_Output_1) {
auto x = NDArrayFactory::create<float>('c', {2, 1, 3});
auto y = NDArrayFactory::create<float>('c', {4, 3});
auto o = NDArrayFactory::create<float>('c', {2, 4, 3});
auto e = NDArrayFactory::create<float>('c', {2, 4, 3});
auto buffO1 = reinterpret_cast<float *>(o.buffer());
y.assign(1.0f);
e.assign(1.0f);
nd4j::ops::add op;
auto result = op.execute({&x, &y}, {&o}, {}, {}, {});
ASSERT_EQ(Status::OK(), result);
auto buffO2 = reinterpret_cast<float *>(o.buffer());
ASSERT_TRUE(e.isSameShape(o));
ASSERT_TRUE(e.equalsTo(o));
ASSERT_TRUE(buffO1 == buffO2);
}
TEST_F(BroadcastableOpsTests, Test_Subtract_1) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {0.0f, 1.0f});
auto e = NDArrayFactory::create<float>('c', {2}, {1.0f, 0.0f});
auto z = x - y;
ASSERT_TRUE(e.equalsTo(z));
}
TEST_F(BroadcastableOpsTests, Test_Subtract_2) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {0.0f, 1.0f});
auto e = NDArrayFactory::create<float>('c', {2}, {1.0f, 0.0f});
nd4j::ops::subtract op;
auto result = op.evaluate({&x, &y});
auto z = result->at(0);
ASSERT_TRUE(e.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Subtract_3) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {0.0f, 1.0f});
auto z = NDArrayFactory::create<float>('c', {2}, {0.0f, 0.0f});
auto e = NDArrayFactory::create<float>('c', {2}, {1.0f, 0.0f});
nd4j::ops::subtract op;
auto result = op.execute({&x, &y}, {&z}, {}, {}, {});
ASSERT_EQ(Status::OK(), result);
ASSERT_TRUE(e.equalsTo(z));
}
TEST_F(BroadcastableOpsTests, Test_Subtract_4) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {0.0f, 1.0f});
auto e = NDArrayFactory::create<float>('c', {2}, {1.0f, 0.0f});
auto z = x.applyTrueBroadcast(BroadcastOpsTuple::Subtract(), y);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Subtract_5) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {0.0f, 1.0f});
auto e = NDArrayFactory::create<float>('c', {2}, {-1., 0.});
auto z = y - x;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Subtract_6) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>(4.f);
auto e = NDArrayFactory::create<float>(3.f);
auto z = y - x;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Subtract_7) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>(4.f);
auto e = NDArrayFactory::create<float>(-3.f);
auto z = x - y;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Add_2) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {0.0f, 1.0f});
auto e = NDArrayFactory::create<float>('c', {2}, {1.f, 2.f});
auto z = x + y;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Add_3) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {0.0f, 1.0f});
auto e = NDArrayFactory::create<float>('c', {2}, {1.f, 2.f});
auto z = y + x;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Add_4) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>(4.f);
auto e = NDArrayFactory::create<float>(5.f);
auto z = x + y;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Add_5) {
auto x = NDArrayFactory::create<float>(1.0f);
auto y = NDArrayFactory::create<float>(4.f);
auto e = NDArrayFactory::create<float>(5.f);
auto z = y + x;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Multiply_2) {
auto x = NDArrayFactory::create<float>(2.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {3.f, 4.f});
auto e = NDArrayFactory::create<float>('c', {2}, {6.f, 8.f});
auto z = y * x;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Multiply_3) {
auto x = NDArrayFactory::create<float>(2.0f);
auto y = NDArrayFactory::create<float>('c', {2}, {3.f, 4.f});
auto e = NDArrayFactory::create<float>('c', {2}, {6.f, 8.f});
auto z = x * y;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Multiply_4) {
auto x = NDArrayFactory::create<float>(2.0f);
auto y = NDArrayFactory::create<float>(4.f);
auto e = NDArrayFactory::create<float>(8.f);
auto z = y * x;
ASSERT_TRUE(e.equalsTo(z));
}
////////////////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, Test_Multiply_5) {
auto x = NDArrayFactory::create<float>(2.0f);
auto y = NDArrayFactory::create<float>(4.f);
auto e = NDArrayFactory::create<float>(8.f);
auto z = x * y;
ASSERT_TRUE(e.equalsTo(z));
}
TEST_F(BroadcastableOpsTests, Test_Multiply_6) {
auto x = NDArrayFactory::create<float>(2.0f);
auto y = NDArrayFactory::create<float>('c', {1}, {4.f});
auto e = NDArrayFactory::create<float>('c', {1}, {8.f});
auto z = x * y;
ASSERT_TRUE(e.equalsTo(z));
}
TEST_F(BroadcastableOpsTests, Test_Multiply_7) {
auto x = NDArrayFactory::create<float>(2.0f);
auto y = NDArrayFactory::create<float>('c', {1}, {4.f});
auto e = NDArrayFactory::create<float>('c', {1}, {8.f});
nd4j::ops::multiply op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(e.equalsTo(z));
delete result;
}
TEST_F(BroadcastableOpsTests, Test_Multiply_8) {
auto x = NDArrayFactory::create<float>(2.0f);
auto y = NDArrayFactory::create<float>('c', {1, 1}, {4.f});
auto e = NDArrayFactory::create<float>('c', {1, 1}, {8.f});
nd4j::ops::multiply op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(e.equalsTo(z));
delete result;
}
//////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, broadcast_add_1) {
NDArray x('c', {4}, {1,1,1,1});
NDArray y('c', {1,4}, {1,2,3,4});
NDArray z('c', {1,4}, nd4j::DataType::DOUBLE);
NDArray exp('c', {1,4}, {2,3,4,5}, nd4j::DataType::DOUBLE);
nd4j::ops::add op;
auto status = op.execute({&x, &y}, {&z});
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(z.equalsTo(exp));
}
//////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, broadcast_equals_1) {
NDArray x('c', {1,4}, {1,2,3,4});
NDArray y('c', {3,4}, {0,0,0,0, 1,2,3,4, 1,2,3,4});
NDArray z('c', {3,4}, nd4j::DataType::BOOL);
NDArray exp('c', {3,4}, {0,0,0,0, 1,1,1,1, 1,1,1,1}, nd4j::DataType::BOOL);
nd4j::ops::equals op;
auto status = op.execute({&x, &y}, {&z});
// z.printIndexedBuffer();
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(z.equalsTo(exp));
}
//////////////////////////////////////////////////////////////////////
TEST_F(BroadcastableOpsTests, broadcast_empty_1) {
NDArray y('c', {3,4}, {0,0,0,0, 1,2,3,4, 1,2,3,4});
NDArray x(nd4j::DataType::DOUBLE, y.getContext(), false);
NDArray z(nd4j::DataType::DOUBLE, y.getContext(), false);
NDArray zExp(nd4j::DataType::DOUBLE, y.getContext(), false);
nd4j::ops::multiply op;
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(z.isSameShape(zExp));
ASSERT_TRUE(z.equalsTo(zExp));
}
TEST_F(BroadcastableOpsTests, broadcast_empty_2) {
NDArray y('c', {1,4}, {1,2,3,4});
NDArray x = NDArrayFactory::create<double>('c', {0, 4});
NDArray e = NDArrayFactory::create<double>('c', {0, 4});;
nd4j::ops::multiply op;
auto status = op.execute({&x, &y}, {&x}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(e.isSameShape(x));
ASSERT_TRUE(e.equalsTo(x));
}
TEST_F(BroadcastableOpsTests, broadcast_empty_3) {
NDArray x = NDArrayFactory::create<float>('c', {1, 0, 2});
NDArray y('c', {}, {0.1}, nd4j::DataType::FLOAT32);
NDArray e = NDArrayFactory::create<float>('c', {1, 0, 2});;
nd4j::ops::maximum op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_4) {
NDArray x = NDArrayFactory::create<float>('c', {1, 0, 1});
NDArray y = NDArrayFactory::create<float>('c', {1, 0, 2});
NDArray e = NDArrayFactory::create<float>('c', {1, 0, 2});;
nd4j::ops::maximum op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_5) {
NDArray x = NDArrayFactory::create<float>('c', {1, 0, 1});
NDArray y = NDArrayFactory::create<float>('c', {1, 0, 2});
NDArray e = NDArrayFactory::create<float>('c', {1, 0, 2});;
nd4j::ops::realdiv op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_6) {
NDArray x = NDArrayFactory::create<float>('c', {1, 0, 1});
NDArray y = NDArrayFactory::create<float>('c', {1, 2}, {2, 2});
NDArray e = NDArrayFactory::create<float>('c', {1, 0, 2});;
nd4j::ops::realdiv op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_empty_7) {
NDArray x = NDArrayFactory::create<float>('c', {1, 0, 2, 1});
NDArray y = NDArrayFactory::create<float>('c', {1, 2, 0});
NDArray e = NDArrayFactory::create<float>('c', {1, 0, 2, 0});;
nd4j::ops::realdiv op;
auto result = op.evaluate({&x, &y});
ASSERT_EQ(Status::OK(), result->status());
auto z = result->at(0);
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_bool_empty_1) {
NDArray y('c', {3,4}, {0,0,0,0, 1,2,3,4, 1,2,3,4});
NDArray x(nd4j::DataType::DOUBLE, y.getContext(), false);
NDArray z(nd4j::DataType::BOOL, y.getContext(), false);
NDArray zExp(nd4j::DataType::BOOL, y.getContext(), false);
nd4j::ops::greater op;
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
ASSERT_TRUE(z.isSameShape(zExp));
ASSERT_TRUE(z.equalsTo(zExp));
}
TEST_F(BroadcastableOpsTests, broadcast_bool_empty_2) {
NDArray y('c', {1,4}, {1,2,3,4});
NDArray x = NDArrayFactory::create<double>('c', {0, 4});
NDArray e = NDArrayFactory::create<bool>('c', {0, 4});;
nd4j::ops::greater op;
auto result = op.evaluate({&x, &y});
auto z = result->at(0);
// z->printShapeInfo("z");
ASSERT_EQ(Status::OK(), result->status());
ASSERT_TRUE(e.isSameShape(z));
ASSERT_TRUE(e.equalsTo(*z));
delete result;
}
TEST_F(BroadcastableOpsTests, broadcast_bool_1) {
NDArray x('c', {3, 1, 2}, nd4j::DataType::FLOAT32);
NDArray y('c', {2, 2}, nd4j::DataType::FLOAT32);
NDArray z('c', {3, 2, 2}, nd4j::DataType::BOOL);
NDArray e('c', {3, 2, 2}, nd4j::DataType::BOOL);
x.assign(4.f);
y.assign(2.f);
e.assign(true);
nd4j::ops::greater op;
auto status = op.execute({&x, &y}, {&z});
ASSERT_EQ(ND4J_STATUS_OK, status);
// z.printIndexedBuffer("Z");
ASSERT_TRUE(z.isSameShape(e));
ASSERT_TRUE(z.equalsTo(e));
}
TEST_F(BroadcastableOpsTests, broadcast_bool_2) {
NDArray x('c', {3, 1, 2}, nd4j::DataType::FLOAT32);
NDArray y('c', {2, 2}, nd4j::DataType::FLOAT32);
NDArray z('c', {3, 2, 2}, nd4j::DataType::BOOL);
NDArray e('c', {3, 2, 2}, nd4j::DataType::BOOL);
x.assign(1.f);
y.assign(2.f);
e.assign(false);
nd4j::ops::equals op;
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
// z.printIndexedBuffer("Z");
ASSERT_TRUE(z.isSameShape(e));
ASSERT_TRUE(z.equalsTo(e));
}
TEST_F(BroadcastableOpsTests, broadcast_bool_3) {
auto x = NDArrayFactory::create<int>(0);
auto y = NDArrayFactory::create<int>('c', {3}, {2, 1, 2});
NDArray z('c', {3}, nd4j::DataType::BOOL);
NDArray e('c', {3}, nd4j::DataType::BOOL);
e.assign(true);
nd4j::ops::less op;
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
// z.printIndexedBuffer("Z");
ASSERT_TRUE(z.isSameShape(e));
ASSERT_TRUE(z.equalsTo(e));
}
TEST_F(BroadcastableOpsTests, broadcast_2) {
NDArray x('c', {3, 1, 2}, nd4j::DataType::FLOAT32);
NDArray y('c', {2, 2}, nd4j::DataType::FLOAT32);
NDArray z('c', {3, 2, 2}, nd4j::DataType::FLOAT32);
NDArray e('c', {3, 2, 2}, nd4j::DataType::FLOAT32);
x = 4.f;
y = 2.f;
e = -2.f;
nd4j::ops::reversesubtract op; // z = y - x;
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
// z.printIndexedBuffer("Z");
ASSERT_TRUE(z.isSameShape(e));
ASSERT_TRUE(z.equalsTo(e));
}
TEST_F(BroadcastableOpsTests, broadcast_3) {
auto x = NDArrayFactory::create<int>(0);
auto y = NDArrayFactory::create<int>('c', {3}, {2, 1, 2});
NDArray z('c', {3}, nd4j::DataType::INT32);
auto e = NDArrayFactory::create<int>('c', {3}, {2, 1, 2});
nd4j::ops::add op;
auto status = op.execute({&x, &y}, {&z}, {}, {}, {});
ASSERT_EQ(ND4J_STATUS_OK, status);
// z.printIndexedBuffer("Z");
ASSERT_TRUE(z.isSameShape(e));
ASSERT_TRUE(z.equalsTo(e));
}
TEST_F(BroadcastableOpsTests, test_bert_multiply_1) {
auto x = NDArrayFactory::create<float>('c', {4, 128, 1});
auto y = NDArrayFactory::create<float>('c', {4, 1, 128});
auto z = NDArrayFactory::create<float>('c', {4, 128, 128});
auto e = NDArrayFactory::create<float>('c', {4, 128, 128});
x.assign(0.f);
y.assign(1.f);
z.assign(119.f);
e.assign(0.f);
/*
Context ctx(1);
ctx.setInputArray(0, &x);
ctx.setInputArray(1, &y);
ctx.setOutputArray(0, &z);
nd4j::ops::multiply op;
auto status = op.execute(&ctx);
ASSERT_EQ(Status::OK(), status);
z.printIndexedBuffer();
*/
x.applyTrueBroadcast(BroadcastOpsTuple::Multiply(), y, z);
//z.printIndexedBuffer();
ASSERT_EQ(e, z);
}
TEST_F(BroadcastableOpsTests, test_bert_multiply_2) {
auto x = NDArrayFactory::create<float>('c', {4, 128, 1});
auto y = NDArrayFactory::create<float>('c', {768});
auto z = NDArrayFactory::create<float>('c', {4, 128, 768});
auto e = NDArrayFactory::create<float>('c', {4, 128, 768});
x.assign(1.f);
y.assign(2.f);
z.assign(119.f);
e.assign(2.f);
x.applyTrueBroadcast(BroadcastOpsTuple::Multiply(), y, z);
ASSERT_EQ(e, z);
}
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