diff --git a/neuralnetworks/1.0/vts/functional/Android.bp b/neuralnetworks/1.0/vts/functional/Android.bp
index a8406de..abff213 100644
--- a/neuralnetworks/1.0/vts/functional/Android.bp
+++ b/neuralnetworks/1.0/vts/functional/Android.bp
@@ -32,12 +32,11 @@
         "android.hidl.memory@1.0",
         "libgmock",
         "libhidlmemory",
+        "libneuralnetworks_generated_test_harness",
         "libneuralnetworks_utils",
     ],
     header_libs: [
         "libneuralnetworks_headers",
-        "libneuralnetworks_generated_test_harness_headers",
-        "libneuralnetworks_generated_tests",
     ],
 }
 
@@ -60,13 +59,12 @@
         "android.hidl.memory@1.0",
         "libgmock",
         "libhidlmemory",
+        "libneuralnetworks_generated_test_harness",
         "libneuralnetworks_utils",
         "VtsHalNeuralNetworksV1_0_utils",
     ],
     header_libs: [
         "libneuralnetworks_headers",
-        "libneuralnetworks_generated_test_harness_headers",
-        "libneuralnetworks_generated_tests",
     ],
     test_suites: ["general-tests"],
 }
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
index 40d2f4c..0fd9947 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
@@ -15,6 +15,7 @@
  */
 
 #include "GeneratedTestHarness.h"
+
 #include "1.0/Callbacks.h"
 #include "1.0/Utils.h"
 #include "MemoryUtils.h"
@@ -28,6 +29,7 @@
 #include <android/hidl/memory/1.0/IMemory.h>
 #include <hidlmemory/mapping.h>
 
+#include <gtest/gtest.h>
 #include <iostream>
 
 namespace android {
@@ -36,6 +38,7 @@
 namespace V1_0 {
 namespace generated_tests {
 
+using namespace test_helper;
 using ::android::hardware::neuralnetworks::V1_0::ErrorStatus;
 using ::android::hardware::neuralnetworks::V1_0::IDevice;
 using ::android::hardware::neuralnetworks::V1_0::IPreparedModel;
@@ -45,137 +48,111 @@
 using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
 using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
 using ::android::hidl::memory::V1_0::IMemory;
-using ::test_helper::compare;
-using ::test_helper::filter;
-using ::test_helper::for_all;
-using ::test_helper::MixedTyped;
-using ::test_helper::MixedTypedExample;
-using ::test_helper::resize_accordingly;
+
+Model createModel(const TestModel& testModel) {
+    // Model operands.
+    hidl_vec<Operand> operands(testModel.operands.size());
+    size_t constCopySize = 0, constRefSize = 0;
+    for (uint32_t i = 0; i < testModel.operands.size(); i++) {
+        const auto& op = testModel.operands[i];
+
+        DataLocation loc = {};
+        if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) {
+            loc = {.poolIndex = 0,
+                   .offset = static_cast<uint32_t>(constCopySize),
+                   .length = static_cast<uint32_t>(op.data.size())};
+            constCopySize += op.data.alignedSize();
+        } else if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) {
+            loc = {.poolIndex = 0,
+                   .offset = static_cast<uint32_t>(constRefSize),
+                   .length = static_cast<uint32_t>(op.data.size())};
+            constRefSize += op.data.alignedSize();
+        }
+
+        operands[i] = {.type = static_cast<OperandType>(op.type),
+                       .dimensions = op.dimensions,
+                       .numberOfConsumers = op.numberOfConsumers,
+                       .scale = op.scale,
+                       .zeroPoint = op.zeroPoint,
+                       .lifetime = static_cast<OperandLifeTime>(op.lifetime),
+                       .location = loc};
+    }
+
+    // Model operations.
+    hidl_vec<Operation> operations(testModel.operations.size());
+    std::transform(testModel.operations.begin(), testModel.operations.end(), operations.begin(),
+                   [](const TestOperation& op) -> Operation {
+                       return {.type = static_cast<OperationType>(op.type),
+                               .inputs = op.inputs,
+                               .outputs = op.outputs};
+                   });
+
+    // Constant copies.
+    hidl_vec<uint8_t> operandValues(constCopySize);
+    for (uint32_t i = 0; i < testModel.operands.size(); i++) {
+        const auto& op = testModel.operands[i];
+        if (op.lifetime == TestOperandLifeTime::CONSTANT_COPY) {
+            const uint8_t* begin = op.data.get<uint8_t>();
+            const uint8_t* end = begin + op.data.size();
+            std::copy(begin, end, operandValues.data() + operands[i].location.offset);
+        }
+    }
+
+    // Shared memory.
+    hidl_vec<hidl_memory> pools;
+    if (constRefSize > 0) {
+        hidl_vec_push_back(&pools, nn::allocateSharedMemory(constRefSize));
+        CHECK_NE(pools[0].size(), 0u);
+
+        // load data
+        sp<IMemory> mappedMemory = mapMemory(pools[0]);
+        CHECK(mappedMemory.get() != nullptr);
+        uint8_t* mappedPtr =
+                reinterpret_cast<uint8_t*>(static_cast<void*>(mappedMemory->getPointer()));
+        CHECK(mappedPtr != nullptr);
+
+        for (uint32_t i = 0; i < testModel.operands.size(); i++) {
+            const auto& op = testModel.operands[i];
+            if (op.lifetime == TestOperandLifeTime::CONSTANT_REFERENCE) {
+                const uint8_t* begin = op.data.get<uint8_t>();
+                const uint8_t* end = begin + op.data.size();
+                std::copy(begin, end, mappedPtr + operands[i].location.offset);
+            }
+        }
+    }
+
+    return {.operands = std::move(operands),
+            .operations = std::move(operations),
+            .inputIndexes = testModel.inputIndexes,
+            .outputIndexes = testModel.outputIndexes,
+            .operandValues = std::move(operandValues),
+            .pools = std::move(pools)};
+}
 
 // Top level driver for models and examples generated by test_generator.py
 // Test driver for those generated from ml/nn/runtime/test/spec
-void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
-                           const std::vector<MixedTypedExample>& examples, float fpAtol,
-                           float fpRtol) {
-    const uint32_t INPUT = 0;
-    const uint32_t OUTPUT = 1;
+void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel) {
+    const Request request = createRequest(testModel);
 
-    int example_no = 1;
-    for (auto& example : examples) {
-        SCOPED_TRACE(example_no++);
-        const MixedTyped& inputs = example.operands.first;
-        const MixedTyped& golden = example.operands.second;
+    // Launch execution.
+    sp<ExecutionCallback> executionCallback = new ExecutionCallback();
+    Return<ErrorStatus> executionLaunchStatus = preparedModel->execute(request, executionCallback);
+    ASSERT_TRUE(executionLaunchStatus.isOk());
+    EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
 
-        CHECK(inputs.float16Operands.empty()) << "float16 is not supported in 1.0";
+    // Retrieve execution status.
+    executionCallback->wait();
+    ASSERT_EQ(ErrorStatus::NONE, executionCallback->getStatus());
 
-        std::vector<RequestArgument> inputs_info, outputs_info;
-        uint32_t inputSize = 0, outputSize = 0;
-        // This function only partially specifies the metadata (vector of RequestArguments).
-        // The contents are copied over below.
-        for_all(inputs, [&inputs_info, &inputSize](int index, auto, auto s) {
-            if (inputs_info.size() <= static_cast<size_t>(index)) inputs_info.resize(index + 1);
-            RequestArgument arg = {
-                    .location = {.poolIndex = INPUT,
-                                 .offset = 0,
-                                 .length = static_cast<uint32_t>(s)},
-                    .dimensions = {},
-            };
-            RequestArgument arg_empty = {
-                    .hasNoValue = true,
-            };
-            inputs_info[index] = s ? arg : arg_empty;
-            inputSize += s;
-        });
-        // Compute offset for inputs 1 and so on
-        {
-            size_t offset = 0;
-            for (auto& i : inputs_info) {
-                if (!i.hasNoValue) i.location.offset = offset;
-                offset += i.location.length;
-            }
-        }
+    // Retrieve execution results.
+    const std::vector<TestBuffer> outputs = getOutputBuffers(request);
 
-        MixedTyped test;  // holding test results
-
-        // Go through all outputs, initialize RequestArgument descriptors
-        resize_accordingly(golden, test);
-        for_all(golden, [&outputs_info, &outputSize](int index, auto, auto s) {
-            if (outputs_info.size() <= static_cast<size_t>(index)) outputs_info.resize(index + 1);
-            RequestArgument arg = {
-                    .location = {.poolIndex = OUTPUT,
-                                 .offset = 0,
-                                 .length = static_cast<uint32_t>(s)},
-                    .dimensions = {},
-            };
-            outputs_info[index] = arg;
-            outputSize += s;
-        });
-        // Compute offset for outputs 1 and so on
-        {
-            size_t offset = 0;
-            for (auto& i : outputs_info) {
-                i.location.offset = offset;
-                offset += i.location.length;
-            }
-        }
-        std::vector<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
-                                          nn::allocateSharedMemory(outputSize)};
-        ASSERT_NE(0ull, pools[INPUT].size());
-        ASSERT_NE(0ull, pools[OUTPUT].size());
-
-        // load data
-        sp<IMemory> inputMemory = mapMemory(pools[INPUT]);
-        sp<IMemory> outputMemory = mapMemory(pools[OUTPUT]);
-        ASSERT_NE(nullptr, inputMemory.get());
-        ASSERT_NE(nullptr, outputMemory.get());
-        char* inputPtr = reinterpret_cast<char*>(static_cast<void*>(inputMemory->getPointer()));
-        char* outputPtr = reinterpret_cast<char*>(static_cast<void*>(outputMemory->getPointer()));
-        ASSERT_NE(nullptr, inputPtr);
-        ASSERT_NE(nullptr, outputPtr);
-        inputMemory->update();
-        outputMemory->update();
-
-        // Go through all inputs, copy the values
-        for_all(inputs, [&inputs_info, inputPtr](int index, auto p, auto s) {
-            char* begin = (char*)p;
-            char* end = begin + s;
-            // TODO: handle more than one input
-            std::copy(begin, end, inputPtr + inputs_info[index].location.offset);
-        });
-
-        inputMemory->commit();
-        outputMemory->commit();
-
-        const Request request = {.inputs = inputs_info, .outputs = outputs_info, .pools = pools};
-
-        // launch execution
-        sp<ExecutionCallback> executionCallback = new ExecutionCallback();
-        ASSERT_NE(nullptr, executionCallback.get());
-        Return<ErrorStatus> executionLaunchStatus =
-                preparedModel->execute(request, executionCallback);
-        ASSERT_TRUE(executionLaunchStatus.isOk());
-        EXPECT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(executionLaunchStatus));
-
-        // retrieve execution status
-        executionCallback->wait();
-        ASSERT_EQ(ErrorStatus::NONE, executionCallback->getStatus());
-
-        // validate results
-        outputMemory->read();
-        copy_back(&test, outputs_info, outputPtr);
-        outputMemory->commit();
-        // Filter out don't cares
-        MixedTyped filtered_golden = filter(golden, is_ignored);
-        MixedTyped filtered_test = filter(test, is_ignored);
-
-        // We want "close-enough" results for float
-        compare(filtered_golden, filtered_test, fpAtol, fpRtol);
-    }
+    // We want "close-enough" results.
+    checkResults(testModel, outputs);
 }
 
-void Execute(const sp<IDevice>& device, std::function<Model(void)> create_model,
-             std::function<bool(int)> is_ignored, const std::vector<MixedTypedExample>& examples) {
-    Model model = create_model();
+void Execute(const sp<IDevice>& device, const TestModel& testModel) {
+    Model model = createModel(testModel);
 
     // see if service can handle model
     bool fullySupportsModel = false;
@@ -190,7 +167,6 @@
 
     // launch prepare model
     sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
-    ASSERT_NE(nullptr, preparedModelCallback.get());
     Return<ErrorStatus> prepareLaunchStatus = device->prepareModel(model, preparedModelCallback);
     ASSERT_TRUE(prepareLaunchStatus.isOk());
     ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
@@ -213,8 +189,7 @@
     EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
     ASSERT_NE(nullptr, preparedModel.get());
 
-    float fpAtol = 1e-5f, fpRtol = 5.0f * 1.1920928955078125e-7f;
-    EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
+    EvaluatePreparedModel(preparedModel, testModel);
 }
 
 }  // namespace generated_tests
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h
index 337eb0f..5d22158 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTestHarness.h
@@ -26,10 +26,9 @@
 namespace V1_0 {
 namespace generated_tests {
 
-using ::test_helper::MixedTypedExample;
+Model createModel(const ::test_helper::TestModel& testModel);
 
-void Execute(const sp<V1_0::IDevice>& device, std::function<V1_0::Model(void)> create_model,
-             std::function<bool(int)> is_ignored, const std::vector<MixedTypedExample>& examples);
+void Execute(const sp<V1_0::IDevice>& device, const ::test_helper::TestModel& testModel);
 
 }  // namespace generated_tests
 }  // namespace V1_0
diff --git a/neuralnetworks/1.0/vts/functional/GeneratedTests.h b/neuralnetworks/1.0/vts/functional/GeneratedTests.h
index 5cabf68..9528905 100644
--- a/neuralnetworks/1.0/vts/functional/GeneratedTests.h
+++ b/neuralnetworks/1.0/vts/functional/GeneratedTests.h
@@ -14,20 +14,11 @@
  * limitations under the License.
  */
 
-#include <android/hidl/memory/1.0/IMemory.h>
-#include <hidlmemory/mapping.h>
-
+#include "1.0/Utils.h"
 #include "GeneratedTestHarness.h"
-#include "MemoryUtils.h"
 #include "TestHarness.h"
 #include "VtsHalNeuralnetworks.h"
 
-namespace android::hardware::neuralnetworks::V1_0::vts::functional {
-
-std::vector<Request> createRequests(const std::vector<::test_helper::MixedTypedExample>& examples);
-
-}  // namespace android::hardware::neuralnetworks::V1_0::vts::functional
-
 namespace android::hardware::neuralnetworks::V1_0::generated_tests {
 
 using namespace android::hardware::neuralnetworks::V1_0::vts::functional;
diff --git a/neuralnetworks/1.0/vts/functional/Utils.cpp b/neuralnetworks/1.0/vts/functional/Utils.cpp
index 521e524..94ba183 100644
--- a/neuralnetworks/1.0/vts/functional/Utils.cpp
+++ b/neuralnetworks/1.0/vts/functional/Utils.cpp
@@ -14,45 +14,99 @@
  * limitations under the License.
  */
 
-#include "GeneratedTestHarness.h"
+#include "1.0/Utils.h"
+
+#include "MemoryUtils.h"
 #include "TestHarness.h"
 
+#include <android-base/logging.h>
 #include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hidl/allocator/1.0/IAllocator.h>
+#include <android/hidl/memory/1.0/IMemory.h>
+#include <hidlmemory/mapping.h>
 
-#include <cstring>
-#include <map>
 #include <vector>
 
 namespace android {
 namespace hardware {
 namespace neuralnetworks {
 
+using namespace test_helper;
+using ::android::hardware::neuralnetworks::V1_0::DataLocation;
+using ::android::hardware::neuralnetworks::V1_0::Request;
 using ::android::hardware::neuralnetworks::V1_0::RequestArgument;
-using ::test_helper::for_each;
-using ::test_helper::MixedTyped;
+using ::android::hidl::memory::V1_0::IMemory;
 
-template <typename T>
-void copy_back_(std::map<int, std::vector<T>>* dst, const std::vector<RequestArgument>& ra,
-                char* src) {
-    for_each<T>(*dst, [&ra, src](int index, std::vector<T>& m) {
-        ASSERT_EQ(m.size(), ra[index].location.length / sizeof(T));
-        char* begin = src + ra[index].location.offset;
-        memcpy(m.data(), begin, ra[index].location.length);
-    });
+constexpr uint32_t kInputPoolIndex = 0;
+constexpr uint32_t kOutputPoolIndex = 1;
+
+Request createRequest(const TestModel& testModel) {
+    // Model inputs.
+    hidl_vec<RequestArgument> inputs(testModel.inputIndexes.size());
+    size_t inputSize = 0;
+    for (uint32_t i = 0; i < testModel.inputIndexes.size(); i++) {
+        const auto& op = testModel.operands[testModel.inputIndexes[i]];
+        if (op.data.size() == 0) {
+            // Omitted input.
+            inputs[i] = {.hasNoValue = true};
+        } else {
+            DataLocation loc = {.poolIndex = kInputPoolIndex,
+                                .offset = static_cast<uint32_t>(inputSize),
+                                .length = static_cast<uint32_t>(op.data.size())};
+            inputSize += op.data.alignedSize();
+            inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+        }
+    }
+
+    // Model outputs.
+    hidl_vec<RequestArgument> outputs(testModel.outputIndexes.size());
+    size_t outputSize = 0;
+    for (uint32_t i = 0; i < testModel.outputIndexes.size(); i++) {
+        const auto& op = testModel.operands[testModel.outputIndexes[i]];
+        size_t dataSize = op.data.size();
+        DataLocation loc = {.poolIndex = kOutputPoolIndex,
+                            .offset = static_cast<uint32_t>(outputSize),
+                            .length = static_cast<uint32_t>(dataSize)};
+        outputSize += op.data.alignedSize();
+        outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+    }
+
+    // Allocate memory pools.
+    hidl_vec<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
+                                   nn::allocateSharedMemory(outputSize)};
+    CHECK_NE(pools[kInputPoolIndex].size(), 0u);
+    CHECK_NE(pools[kOutputPoolIndex].size(), 0u);
+    sp<IMemory> inputMemory = mapMemory(pools[kInputPoolIndex]);
+    CHECK(inputMemory.get() != nullptr);
+    uint8_t* inputPtr = static_cast<uint8_t*>(static_cast<void*>(inputMemory->getPointer()));
+    CHECK(inputPtr != nullptr);
+
+    // Copy input data to the memory pool.
+    for (uint32_t i = 0; i < testModel.inputIndexes.size(); i++) {
+        const auto& op = testModel.operands[testModel.inputIndexes[i]];
+        if (op.data.size() > 0) {
+            const uint8_t* begin = op.data.get<uint8_t>();
+            const uint8_t* end = begin + op.data.size();
+            std::copy(begin, end, inputPtr + inputs[i].location.offset);
+        }
+    }
+
+    return {.inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)};
 }
 
-void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* src) {
-    copy_back_(&dst->float32Operands, ra, src);
-    copy_back_(&dst->int32Operands, ra, src);
-    copy_back_(&dst->quant8AsymmOperands, ra, src);
-    copy_back_(&dst->quant16SymmOperands, ra, src);
-    copy_back_(&dst->float16Operands, ra, src);
-    copy_back_(&dst->bool8Operands, ra, src);
-    copy_back_(&dst->quant8ChannelOperands, ra, src);
-    copy_back_(&dst->quant16AsymmOperands, ra, src);
-    copy_back_(&dst->quant8SymmOperands, ra, src);
-    static_assert(9 == MixedTyped::kNumTypes,
-                  "Number of types in MixedTyped changed, but copy_back function wasn't updated");
+std::vector<TestBuffer> getOutputBuffers(const Request& request) {
+    sp<IMemory> outputMemory = mapMemory(request.pools[kOutputPoolIndex]);
+    CHECK(outputMemory.get() != nullptr);
+    uint8_t* outputPtr = static_cast<uint8_t*>(static_cast<void*>(outputMemory->getPointer()));
+    CHECK(outputPtr != nullptr);
+
+    // Copy out output results.
+    std::vector<TestBuffer> outputBuffers;
+    for (const auto& output : request.outputs) {
+        outputBuffers.emplace_back(output.location.length, outputPtr + output.location.offset);
+    }
+
+    return outputBuffers;
 }
 
 }  // namespace neuralnetworks
diff --git a/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp b/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp
index 058eb25..d62365c 100644
--- a/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/1.0/vts/functional/ValidateRequest.cpp
@@ -16,13 +16,7 @@
 
 #define LOG_TAG "neuralnetworks_hidl_hal_test"
 
-#include <android-base/logging.h>
-#include <android/hidl/memory/1.0/IMemory.h>
-#include <hidlmemory/mapping.h>
-
 #include "1.0/Callbacks.h"
-#include "MemoryUtils.h"
-#include "TestHarness.h"
 #include "VtsHalNeuralnetworks.h"
 
 namespace android {
@@ -33,10 +27,6 @@
 namespace functional {
 
 using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
-using ::android::hidl::memory::V1_0::IMemory;
-using test_helper::for_all;
-using test_helper::MixedTyped;
-using test_helper::MixedTypedExample;
 
 ///////////////////////// UTILITY FUNCTIONS /////////////////////////
 
@@ -102,103 +92,10 @@
 
 ///////////////////////////// ENTRY POINT //////////////////////////////////
 
-std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples) {
-    const uint32_t INPUT = 0;
-    const uint32_t OUTPUT = 1;
-
-    std::vector<Request> requests;
-
-    for (const MixedTypedExample& example : examples) {
-        const MixedTyped& inputs = example.operands.first;
-        const MixedTyped& outputs = example.operands.second;
-
-        std::vector<RequestArgument> inputs_info, outputs_info;
-        uint32_t inputSize = 0, outputSize = 0;
-
-        // This function only partially specifies the metadata (vector of RequestArguments).
-        // The contents are copied over below.
-        for_all(inputs, [&inputs_info, &inputSize](int index, auto, auto s) {
-            if (inputs_info.size() <= static_cast<size_t>(index)) inputs_info.resize(index + 1);
-            RequestArgument arg = {
-                    .location = {.poolIndex = INPUT,
-                                 .offset = 0,
-                                 .length = static_cast<uint32_t>(s)},
-                    .dimensions = {},
-            };
-            RequestArgument arg_empty = {
-                    .hasNoValue = true,
-            };
-            inputs_info[index] = s ? arg : arg_empty;
-            inputSize += s;
-        });
-        // Compute offset for inputs 1 and so on
-        {
-            size_t offset = 0;
-            for (auto& i : inputs_info) {
-                if (!i.hasNoValue) i.location.offset = offset;
-                offset += i.location.length;
-            }
-        }
-
-        // Go through all outputs, initialize RequestArgument descriptors
-        for_all(outputs, [&outputs_info, &outputSize](int index, auto, auto s) {
-            if (outputs_info.size() <= static_cast<size_t>(index)) outputs_info.resize(index + 1);
-            RequestArgument arg = {
-                    .location = {.poolIndex = OUTPUT,
-                                 .offset = 0,
-                                 .length = static_cast<uint32_t>(s)},
-                    .dimensions = {},
-            };
-            outputs_info[index] = arg;
-            outputSize += s;
-        });
-        // Compute offset for outputs 1 and so on
-        {
-            size_t offset = 0;
-            for (auto& i : outputs_info) {
-                i.location.offset = offset;
-                offset += i.location.length;
-            }
-        }
-        std::vector<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
-                                          nn::allocateSharedMemory(outputSize)};
-        if (pools[INPUT].size() == 0 || pools[OUTPUT].size() == 0) {
-            return {};
-        }
-
-        // map pool
-        sp<IMemory> inputMemory = mapMemory(pools[INPUT]);
-        if (inputMemory == nullptr) {
-            return {};
-        }
-        char* inputPtr = reinterpret_cast<char*>(static_cast<void*>(inputMemory->getPointer()));
-        if (inputPtr == nullptr) {
-            return {};
-        }
-
-        // initialize pool
-        inputMemory->update();
-        for_all(inputs, [&inputs_info, inputPtr](int index, auto p, auto s) {
-            char* begin = (char*)p;
-            char* end = begin + s;
-            // TODO: handle more than one input
-            std::copy(begin, end, inputPtr + inputs_info[index].location.offset);
-        });
-        inputMemory->commit();
-
-        requests.push_back({.inputs = inputs_info, .outputs = outputs_info, .pools = pools});
-    }
-
-    return requests;
-}
-
-void ValidationTest::validateRequests(const sp<IPreparedModel>& preparedModel,
-                                      const std::vector<Request>& requests) {
-    // validate each request
-    for (const Request& request : requests) {
-        removeInputTest(preparedModel, request);
-        removeOutputTest(preparedModel, request);
-    }
+void ValidationTest::validateRequest(const sp<IPreparedModel>& preparedModel,
+                                     const Request& request) {
+    removeInputTest(preparedModel, request);
+    removeOutputTest(preparedModel, request);
 }
 
 }  // namespace functional
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
index 95b7ad3..626deac 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.cpp
@@ -121,7 +121,7 @@
     ::testing::VtsHalHidlTargetTestBase::TearDown();
 }
 
-void ValidationTest::validateEverything(const Model& model, const std::vector<Request>& requests) {
+void ValidationTest::validateEverything(const Model& model, const Request& request) {
     validateModel(model);
 
     // create IPreparedModel
@@ -131,7 +131,7 @@
         return;
     }
 
-    validateRequests(preparedModel, requests);
+    validateRequest(preparedModel, request);
 }
 
 }  // namespace functional
diff --git a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
index c32a91d..3765314 100644
--- a/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
+++ b/neuralnetworks/1.0/vts/functional/VtsHalNeuralnetworks.h
@@ -63,12 +63,11 @@
 // Tag for the validation tests
 class ValidationTest : public NeuralnetworksHidlTest {
    protected:
-     void validateEverything(const Model& model, const std::vector<Request>& request);
+     void validateEverything(const Model& model, const Request& request);
 
    private:
      void validateModel(const Model& model);
-     void validateRequests(const sp<IPreparedModel>& preparedModel,
-                           const std::vector<Request>& requests);
+     void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& request);
 };
 
 // Tag for the generated tests
diff --git a/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h b/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h
index b270c20..2955b6e 100644
--- a/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h
+++ b/neuralnetworks/1.0/vts/functional/include/1.0/Utils.h
@@ -26,8 +26,11 @@
 namespace hardware {
 namespace neuralnetworks {
 
-void copy_back(::test_helper::MixedTyped* dst, const std::vector<V1_0::RequestArgument>& ra,
-               char* src);
+// Create HIDL Request from the TestModel struct.
+V1_0::Request createRequest(const ::test_helper::TestModel& testModel);
+
+// After execution, copy out output results from the output memory pool.
+std::vector<::test_helper::TestBuffer> getOutputBuffers(const V1_0::Request& request);
 
 // Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation,
 // so this is efficiently accomplished by moving the element to the end and