/*
 * Copyright (C) 2020 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 "GeneratedTestUtils.h"

#include <android-base/file.h>
#include <android-base/logging.h>
#include <android-base/mapped_file.h>
#include <android-base/unique_fd.h>
#include <android/sharedmem.h>
#include <gtest/gtest.h>

#include <algorithm>
#include <memory>
#include <string>
#include <utility>
#include <vector>

#include "TestHarness.h"

#ifdef NNTEST_SLTS
#include "SupportLibraryWrapper.h"
#else
#include "TestNeuralNetworksWrapper.h"
#endif

namespace android::nn::generated_tests {
using namespace test_wrapper;
using namespace test_helper;

static OperandType getOperandType(const TestOperand& op, bool testDynamicOutputShape) {
    auto dims = op.dimensions;
    if (testDynamicOutputShape && op.lifetime == TestOperandLifeTime::SUBGRAPH_OUTPUT) {
        dims.assign(dims.size(), 0);
    }
    if (op.type == TestOperandType::TENSOR_QUANT8_SYMM_PER_CHANNEL) {
        return OperandType(
                static_cast<Type>(op.type), dims,
                SymmPerChannelQuantParams(op.channelQuant.scales, op.channelQuant.channelDim));
    } else {
        return OperandType(static_cast<Type>(op.type), dims, op.scale, op.zeroPoint);
    }
}

// A Memory object with a memory mapping
class MemoryWithPointer : public Memory {
   public:
#ifdef NNTEST_SLTS
    static std::unique_ptr<MemoryWithPointer> create(const NnApiSupportLibrary* nnapi,
                                                     uint32_t size) {
#else   // NNTEST_SLTS
    static std::unique_ptr<MemoryWithPointer> create(uint32_t size) {
#endif  // NNTEST_SLTS

        CHECK_GT(size, 0u);
#ifdef __ANDROID__
        auto fd = base::unique_fd(ASharedMemory_create(nullptr, size));
#else   // __ANDROID__
        TemporaryFile tmpFile;
        base::unique_fd fd(tmpFile.release());
        CHECK_EQ(ftruncate(fd.get(), size), 0);
#endif  // __ANDROID__
        EXPECT_TRUE(fd.ok());
        const int protect = PROT_READ | PROT_WRITE;
        const size_t offset = 0;
        auto mapping = base::MappedFile::FromFd(fd.get(), offset, size, protect);
        EXPECT_NE(mapping, nullptr);

#ifdef NNTEST_SLTS
        return std::unique_ptr<MemoryWithPointer>(
                new MemoryWithPointer(nnapi, size, protect, fd.get(), offset, std::move(mapping)));
#else   // NNTEST_SLTS
        return std::unique_ptr<MemoryWithPointer>(
                new MemoryWithPointer(size, protect, fd.get(), offset, std::move(mapping)));
#endif  // NNTEST_SLTS
    }

    uint8_t* getPointer() const { return reinterpret_cast<uint8_t*>(mMapping->data()); }

   private:
#ifdef NNTEST_SLTS
    MemoryWithPointer(const NnApiSupportLibrary* nnapi, size_t size, int protect, int fd,
                      size_t offset, std::unique_ptr<base::MappedFile> mapping)
        : Memory(nnapi, size, protect, fd, offset), mMapping(std::move(mapping)) {}
#else
    MemoryWithPointer(size_t size, int protect, int fd, size_t offset,
                      std::unique_ptr<base::MappedFile> mapping)
        : Memory(size, protect, fd, offset), mMapping(std::move(mapping)) {}
#endif

    std::unique_ptr<base::MappedFile> mMapping;
};

#ifdef NNTEST_SLTS
static std::unique_ptr<MemoryWithPointer> createConstantReferenceMemory(
        const NnApiSupportLibrary* nnapi, const TestModel& testModel) {
#else
static std::unique_ptr<MemoryWithPointer> createConstantReferenceMemory(
        const TestModel& testModel) {
#endif
    uint32_t size = 0;

    auto processSubgraph = [&size](const TestSubgraph& subgraph) {
        for (const TestOperand& operand : subgraph.operands) {
            if (operand.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) {
                size += operand.data.alignedSize();
            }
        }
    };

    processSubgraph(testModel.main);
    for (const TestSubgraph& subgraph : testModel.referenced) {
        processSubgraph(subgraph);
    }
#ifdef NNTEST_SLTS
    return size == 0 ? nullptr : MemoryWithPointer::create(nnapi, size);
#else
    return size == 0 ? nullptr : MemoryWithPointer::create(size);
#endif
}

static void createModelFromSubgraph(const TestSubgraph& subgraph, bool testDynamicOutputShape,
                                    const std::vector<TestSubgraph>& refSubgraphs,
                                    const std::unique_ptr<MemoryWithPointer>& memory,
                                    uint32_t* memoryOffset, Model* model, Model* refModels) {
    // Operands.
    for (const auto& operand : subgraph.operands) {
        auto type = getOperandType(operand, testDynamicOutputShape);
        auto index = model->addOperand(&type);

        switch (operand.lifetime) {
            case TestOperandLifeTime::CONSTANT_COPY: {
                model->setOperandValue(index, operand.data.get<void>(), operand.data.size());
            } break;
            case TestOperandLifeTime::CONSTANT_REFERENCE: {
                const uint32_t length = operand.data.size();
                std::memcpy(memory->getPointer() + *memoryOffset, operand.data.get<void>(), length);
                model->setOperandValueFromMemory(index, memory.get(), *memoryOffset, length);
                *memoryOffset += operand.data.alignedSize();
            } break;
            case TestOperandLifeTime::NO_VALUE: {
                model->setOperandValue(index, nullptr, 0);
            } break;
            case TestOperandLifeTime::SUBGRAPH: {
                uint32_t refIndex = *operand.data.get<uint32_t>();
                CHECK_LT(refIndex, refSubgraphs.size());
                const TestSubgraph& refSubgraph = refSubgraphs[refIndex];
                Model* refModel = &refModels[refIndex];

                if (!refModel->isFinished()) {
                    createModelFromSubgraph(refSubgraph, testDynamicOutputShape, refSubgraphs,
                                            memory, memoryOffset, refModel, refModels);
                    ASSERT_EQ(refModel->finish(), Result::NO_ERROR);
                    ASSERT_TRUE(refModel->isValid());
                }
                model->setOperandValueFromModel(index, refModel);
            } break;
            case TestOperandLifeTime::SUBGRAPH_INPUT:
            case TestOperandLifeTime::SUBGRAPH_OUTPUT:
            case TestOperandLifeTime::TEMPORARY_VARIABLE: {
                // Nothing to do here.
            } break;
        }
    }

    // Operations.
    for (const auto& operation : subgraph.operations) {
        model->addOperation(static_cast<int>(operation.type), operation.inputs, operation.outputs);
    }

    // Inputs and outputs.
    model->identifyInputsAndOutputs(subgraph.inputIndexes, subgraph.outputIndexes);
}

#ifdef NNTEST_SLTS
void createModel(const NnApiSupportLibrary* nnapi, const TestModel& testModel,
                 bool testDynamicOutputShape, GeneratedModel* model) {
#else
void createModel(const TestModel& testModel, bool testDynamicOutputShape, GeneratedModel* model) {
#endif
    ASSERT_NE(nullptr, model);

#ifdef NNTEST_SLTS
    std::unique_ptr<MemoryWithPointer> memory = createConstantReferenceMemory(nnapi, testModel);
#else
    std::unique_ptr<MemoryWithPointer> memory = createConstantReferenceMemory(testModel);
#endif
    uint32_t memoryOffset = 0;
#ifdef NNTEST_SLTS
    std::vector<Model> refModels;
    refModels.reserve(testModel.referenced.size());
    for (int i = 0; i < testModel.referenced.size(); ++i) {
        refModels.push_back(Model(nnapi));
    }
#else
    std::vector<Model> refModels(testModel.referenced.size());
#endif
    createModelFromSubgraph(testModel.main, testDynamicOutputShape, testModel.referenced, memory,
                            &memoryOffset, model, refModels.data());
    model->setRefModels(std::move(refModels));
    model->setConstantReferenceMemory(std::move(memory));

    // Relaxed computation.
    model->relaxComputationFloat32toFloat16(testModel.isRelaxed);

    if (!testModel.expectFailure) {
        ASSERT_TRUE(model->isValid());
    }
}

void createRequest(const TestModel& testModel, Execution* execution,
                   std::vector<TestBuffer>* outputs) {
    ASSERT_NE(nullptr, execution);
    ASSERT_NE(nullptr, outputs);

    // Model inputs.
    for (uint32_t i = 0; i < testModel.main.inputIndexes.size(); i++) {
        const auto& operand = testModel.main.operands[testModel.main.inputIndexes[i]];
        ASSERT_EQ(Result::NO_ERROR,
                  execution->setInput(i, operand.data.get<void>(), operand.data.size()));
    }

    // Model outputs.
    for (uint32_t i = 0; i < testModel.main.outputIndexes.size(); i++) {
        const auto& operand = testModel.main.operands[testModel.main.outputIndexes[i]];

        // In the case of zero-sized output, we should at least provide a one-byte buffer.
        // This is because zero-sized tensors are only supported internally to the runtime, or
        // reported in output shapes. It is illegal for the client to pre-specify a zero-sized
        // tensor as model output. Otherwise, we will have two semantic conflicts:
        // - "Zero dimension" conflicts with "unspecified dimension".
        // - "Omitted operand buffer" conflicts with "zero-sized operand buffer".
        const size_t bufferSize = std::max<size_t>(operand.data.size(), 1);

        outputs->emplace_back(bufferSize);
        ASSERT_EQ(Result::NO_ERROR,
                  execution->setOutput(i, outputs->back().getMutable<void>(), bufferSize));
    }
}

}  // namespace android::nn::generated_tests