/* * Copyright (C) 2018 The Android Open Source Project * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://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. */ #include #include #include #include #include #include "HalInterfaces.h" #include "MemoryUtils.h" #include "OperationsUtils.cpp" #include "QuantUtils.h" #include "Utils.h" #include "ValidateHal.h" #include "nnapi/TypeUtils.h" #include "nnapi/Types.h" namespace android { namespace nn { namespace wrapper { namespace { using ::testing::ElementsAreArray; } // namespace TEST(CalculateBroadcastedShapeTest, Basic) { Shape shape1; Shape shape2; shape1.dimensions = {4, 3, 2, 1}; shape2.dimensions = {3, 1, 5}; Shape expectedOutputShape; expectedOutputShape.dimensions = {4, 3, 2, 5}; Shape actualOutputShape; EXPECT_TRUE(calculateBroadcastedShape(shape1, shape2, &actualOutputShape)); EXPECT_THAT(actualOutputShape.dimensions, ElementsAreArray(expectedOutputShape.dimensions)); EXPECT_TRUE(calculateBroadcastedShape(shape2, shape1, &actualOutputShape)); EXPECT_THAT(actualOutputShape.dimensions, ElementsAreArray(expectedOutputShape.dimensions)); } TEST(CalculateBroadcastedShapeTest, FailsOnIncompatible) { Shape shape1; Shape shape2; shape1.dimensions = {5}; shape2.dimensions = {3}; Shape actualOutputShape; EXPECT_FALSE(calculateBroadcastedShape(shape1, shape2, &actualOutputShape)); EXPECT_FALSE(calculateBroadcastedShape(shape2, shape1, &actualOutputShape)); } static int32_t getExtensionType(uint16_t extensionPrefix, uint16_t typeWithinExtension) { int32_t type = (extensionPrefix << kExtensionTypeBits) | typeWithinExtension; EXPECT_TRUE(isExtensionOperandType(static_cast(type))); return type; } TEST(TensorHasUnspecifiedDimensionsTest, ExtensionTensorWithUnspecifiedRank) { // Regression test for b/124285861. EXPECT_TRUE(tensorHasUnspecifiedDimensions(getExtensionType(1, 0), /*dim=*/nullptr, /*dimCount=*/0)); } TEST(ValidateOperandTypeTest, ExtensionTensorWithUnspecifiedRank) { // Regression test for b/124104123. constexpr uint16_t kExtensionPrefix = 1; constexpr uint16_t kTypeWithinExtension = 0; int32_t extensionType = getExtensionType(kExtensionPrefix, kTypeWithinExtension); ANeuralNetworksOperandType type = { .type = extensionType, .dimensionCount = 0, .dimensions = nullptr, }; Extension::OperandTypeInformation info = { .type = kTypeWithinExtension, .isTensor = true, .byteSize = 4, }; EXPECT_EQ(validateOperandType(type, &info, /*tag=*/"test", /*allowPartial=*/true), ANEURALNETWORKS_NO_ERROR); EXPECT_EQ(validateOperandType(type, &info, /*tag=*/"test", /*allowPartial=*/false), ANEURALNETWORKS_BAD_DATA); } TEST(ValidateOperandTypeTest, ExtensionTypeDimensionProductOverflow) { // Regression test for b/146044137. constexpr uint16_t kExtensionPrefix = 1; constexpr uint16_t kTypeWithinExtension = 0; int32_t extensionType = getExtensionType(kExtensionPrefix, kTypeWithinExtension); uint32_t dimensions[] = {5, 4, 4, 786433, 5, 3, 16777216, 4, 5}; ANeuralNetworksOperandType type = { .type = extensionType, .dimensionCount = std::size(dimensions), .dimensions = dimensions, }; Extension::OperandTypeInformation info = { .type = kTypeWithinExtension, .isTensor = true, .byteSize = 1, }; EXPECT_EQ(validateOperandType(type, &info, /*tag=*/"test", /*allowPartial=*/true), ANEURALNETWORKS_BAD_DATA); } TEST(ValidateOperandTypeTest, TensorSizeDimensionProductOverflow) { // Regression test for b/146044137. uint32_t dimensions[] = {256, 256, 256, 256}; ANeuralNetworksOperandType type = { .type = ANEURALNETWORKS_TENSOR_FLOAT32, .dimensionCount = std::size(dimensions), .dimensions = dimensions, }; EXPECT_EQ(validateOperandType(type, nullptr, /*tag=*/"test", /*allowPartial=*/true), ANEURALNETWORKS_BAD_DATA); } TEST(ValidateRequestTest, UnknownOutputRank) { V1_3::Request::MemoryPool pool; pool.hidlMemory(allocateSharedMemory(2 * sizeof(float))); ASSERT_TRUE(pool.hidlMemory().valid()); const V1_3::Model model = { .main = { .operands = {{ .type = V1_3::OperandType::TENSOR_FLOAT32, .dimensions = {1}, .numberOfConsumers = 1, .lifetime = V1_3::OperandLifeTime::SUBGRAPH_INPUT, }, { .type = V1_3::OperandType::TENSOR_FLOAT32, .dimensions = {}, // unknown output rank .numberOfConsumers = 0, .lifetime = V1_3::OperandLifeTime::SUBGRAPH_OUTPUT, }}, .operations = {{ .type = V1_3::OperationType::ABS, .inputs = {0}, .outputs = {1}, }}, .inputIndexes = {0}, .outputIndexes = {1}, }, }; const V1_3::Request request = { .inputs = {{ .location = {.poolIndex = 0, .offset = 0, .length = sizeof(float)}, .dimensions = {}, }}, .outputs = {{ .location = {.poolIndex = 0, .offset = sizeof(float), .length = sizeof(float)}, .dimensions = {}, }}, .pools = {std::move(pool)}, }; EXPECT_FALSE(validateRequest(request, model, /*allowUnspecifiedOutput=*/false)); } TEST(ValidateRequestTest, ScalarOutput) { V1_3::Request::MemoryPool pool; pool.hidlMemory(allocateSharedMemory(sizeof(float) + sizeof(int32_t))); ASSERT_TRUE(pool.hidlMemory().valid()); const V1_3::Model model = { .main = { .operands = {{ .type = V1_3::OperandType::TENSOR_FLOAT32, .dimensions = {1}, .numberOfConsumers = 1, .lifetime = V1_3::OperandLifeTime::SUBGRAPH_INPUT, }, { .type = V1_3::OperandType::INT32, .dimensions = {}, .numberOfConsumers = 0, .lifetime = V1_3::OperandLifeTime::SUBGRAPH_OUTPUT, }}, .operations = {{ .type = V1_3::OperationType::RANK, .inputs = {0}, .outputs = {1}, }}, .inputIndexes = {0}, .outputIndexes = {1}, }, }; const V1_3::Request request = { .inputs = {{ .location = {.poolIndex = 0, .offset = 0, .length = sizeof(float)}, .dimensions = {}, }}, .outputs = {{ .location = {.poolIndex = 0, .offset = sizeof(float), .length = sizeof(int32_t)}, .dimensions = {}, }}, .pools = {std::move(pool)}, }; EXPECT_TRUE(validateRequest(request, model, /*allowUnspecifiedOutput=*/false)); } class CombineDimensionsTest : public ::testing::Test { protected: void testCompatible(const std::vector& lhs, const std::vector& rhs, const std::vector& expected) { SCOPED_TRACE("lhs = " + toString(lhs) + ", rhs = " + toString(rhs)); const auto res = combineDimensions(lhs, rhs); ASSERT_TRUE(res.has_value()); EXPECT_EQ(res.value(), expected); } void testIncompatible(const std::vector& lhs, const std::vector& rhs) { SCOPED_TRACE("lhs = " + toString(lhs) + ", rhs = " + toString(rhs)); const auto res = combineDimensions(lhs, rhs); EXPECT_FALSE(res.has_value()); } }; TEST_F(CombineDimensionsTest, Rank) { testCompatible({}, {1, 2, 3, 4}, {1, 2, 3, 4}); testCompatible({1, 2, 3, 4}, {}, {1, 2, 3, 4}); testCompatible({}, {}, {}); testIncompatible({1, 2, 3}, {1, 2, 3, 4}); testIncompatible({1, 2, 3, 4}, {1, 2, 3}); } TEST_F(CombineDimensionsTest, Dimensions) { testCompatible({0, 0, 0, 0}, {1, 2, 3, 4}, {1, 2, 3, 4}); testCompatible({1, 2, 3, 4}, {0, 0, 0, 0}, {1, 2, 3, 4}); testCompatible({0, 0, 0, 0}, {0, 0, 0, 0}, {0, 0, 0, 0}); testIncompatible({1, 2, 3, 4}, {2, 2, 3, 4}); testIncompatible({1, 2, 3, 4}, {1, 2, 3, 3}); } TEST(QuantizationUtilsTest, QuantizeMultiplierSmallerThanOneExp) { auto checkInvalidQuantization = [](double value) { int32_t q; int s; EXPECT_FALSE(QuantizeMultiplierSmallerThanOneExp(value, &q, &s)); }; checkInvalidQuantization(-0.1); checkInvalidQuantization(0.0); // If we get close enough to 1.0 it crashes and dies in one of two ways: // Either the shift becomes negative or we trigger the 'less-than-one' CHECK. checkInvalidQuantization(1 - 1e-15); checkInvalidQuantization(1 - 1e-17); checkInvalidQuantization(1.0); auto checkQuantization = [](double value, int32_t goldenQuantized, int goldenShift) { int32_t q; int s; EXPECT_TRUE(QuantizeMultiplierSmallerThanOneExp(value, &q, &s)); EXPECT_EQ(q, goldenQuantized); EXPECT_EQ(s, goldenShift); }; checkQuantization(0.25, 1073741824, -1); checkQuantization(0.50 - 5e-9, 2147483627, -1); checkQuantization(0.50 - 1e-10, 1073741824, 0); checkQuantization(0.50, 1073741824, 0); checkQuantization(0.75, 1610612736, 0); checkQuantization(1 - 1e-9, 2147483646, 0); } TEST(QuantizationUtilsTest, QuantizeMultiplierGreaterThanOne) { auto checkInvalidQuantization = [](double value) { int32_t q; int s; EXPECT_FALSE(QuantizeMultiplierGreaterThanOne(value, &q, &s)); }; checkInvalidQuantization(1 + 1e-16); auto checkQuantization = [](double value, int32_t goldenQuantized, int goldenShift) { int32_t q; int s; EXPECT_TRUE(QuantizeMultiplierGreaterThanOne(value, &q, &s)); EXPECT_EQ(q, goldenQuantized); EXPECT_EQ(s, goldenShift); }; checkQuantization(1 + 1e-11, 1073741824, 1); checkQuantization(1.25, 1342177280, 1); checkQuantization(1.50, 1610612736, 1); checkQuantization(1.50, 1610612736, 1); checkQuantization(1.75, 1879048192, 1); checkQuantization(2 - 1e-9, 2147483647, 1); checkQuantization(2 - 1e-11, 1073741824, 2); checkQuantization(2, 1073741824, 2); } TEST(QuantizationUtilTest, QuantizeMultiplier) { auto checkQuantization = [](double value, int32_t goldenQuantized, int goldenShift) { int32_t q; int s; EXPECT_TRUE(QuantizeMultiplier(value, &q, &s)); EXPECT_EQ(q, goldenQuantized); EXPECT_EQ(s, goldenShift); }; checkQuantization(-4, -1073741824, 3); checkQuantization(-2, -1073741824, 2); checkQuantization(-1, -1073741824, 1); checkQuantization(-0.5, -1073741824, 0); checkQuantization(-0.25, -1073741824, -1); checkQuantization(-0.125, -1073741824, -2); checkQuantization(0, 0, 0); checkQuantization(0.125, 1073741824, -2); checkQuantization(0.25, 1073741824, -1); checkQuantization(0.5, 1073741824, 0); checkQuantization(1, 1073741824, 1); checkQuantization(2, 1073741824, 2); checkQuantization(4, 1073741824, 3); } TEST(QuantizationUtilTest, QuantizeMultiplierUnderflow) { auto checkQuantization = [](double value, int32_t goldenQuantized, int goldenShift) { int32_t q; int s; EXPECT_TRUE(QuantizeMultiplier(value, &q, &s)); EXPECT_EQ(q, goldenQuantized); EXPECT_EQ(s, goldenShift); }; checkQuantization(std::ldexp(1.0f, -31), 1073741824, -30); checkQuantization(std::ldexp(1.0f, -32), 1073741824, -31); checkQuantization(std::ldexp(0.99f, -32), 0, 0); checkQuantization(std::ldexp(1.0f, -33), 0, 0); } TEST(QuantizationUtilTest, GetInvSqrtQuantizedMultiplierExp) { auto checkInvSqrtQuantization = [](int32_t input, int32_t goldenInvSqrt, int goldenShift) { int32_t q; int s; EXPECT_TRUE(GetInvSqrtQuantizedMultiplierExp(input, 1, &q, &s)); EXPECT_EQ(q, goldenInvSqrt); EXPECT_EQ(s, goldenShift); }; const auto kInt32Max = std::numeric_limits::max(); checkInvSqrtQuantization(0, kInt32Max, 0); checkInvSqrtQuantization(1, kInt32Max, 0); checkInvSqrtQuantization(2, 1518498372, 0); checkInvSqrtQuantization(3, 1239850284, 0); checkInvSqrtQuantization(4, 1073741828, 0); checkInvSqrtQuantization(100, 214748363, 0); checkInvSqrtQuantization(10000, 343597361, 4); checkInvSqrtQuantization(1000000, 274877901, 7); checkInvSqrtQuantization(100000000, 219902323, 10); checkInvSqrtQuantization((1 << 30), 268435457, 12); checkInvSqrtQuantization(kInt32Max, 189812531, 12); } } // namespace wrapper } // namespace nn } // namespace android