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