mirror of
https://github.com/Evolution-X/hardware_interfaces
synced 2026-02-01 16:50:18 +00:00
Create 1.2 version IPreparedModel, IPreparedModelCallback, and
IExecutionCallback.
Currently the new interfaces are created the same as 1.0 version,
but will have more methods introduced in later CLs.
Bug: 73506513
Test: VtsHalNeuralnetworksV1_xTargetTest with 1.2 sample driver
Change-Id: Icf4d04c22f88e825d87562f1489377fdf6bf585d
Merged-In: Icf4d04c22f88e825d87562f1489377fdf6bf585d
(cherry picked from commit b5cb8f7632)
263 lines
10 KiB
C++
263 lines
10 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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#define LOG_TAG "neuralnetworks_hidl_hal_test"
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#include "VtsHalNeuralnetworks.h"
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#include "Callbacks.h"
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#include "TestHarness.h"
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#include "Utils.h"
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#include <android-base/logging.h>
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#include <android/hidl/memory/1.0/IMemory.h>
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#include <hidlmemory/mapping.h>
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namespace android {
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namespace hardware {
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namespace neuralnetworks {
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namespace V1_1 {
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namespace vts {
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namespace functional {
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using ::android::hardware::neuralnetworks::V1_2::implementation::ExecutionCallback;
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using ::android::hardware::neuralnetworks::V1_2::implementation::PreparedModelCallback;
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using ::android::hidl::memory::V1_0::IMemory;
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using test_helper::for_all;
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using test_helper::MixedTyped;
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using test_helper::MixedTypedExample;
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///////////////////////// UTILITY FUNCTIONS /////////////////////////
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static void createPreparedModel(const sp<IDevice>& device, const V1_1::Model& model,
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sp<IPreparedModel>* preparedModel) {
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ASSERT_NE(nullptr, preparedModel);
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// see if service can handle model
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bool fullySupportsModel = false;
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Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_1(
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model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) {
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ASSERT_EQ(ErrorStatus::NONE, status);
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ASSERT_NE(0ul, supported.size());
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fullySupportsModel =
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std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; });
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});
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ASSERT_TRUE(supportedOpsLaunchStatus.isOk());
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// launch prepare model
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sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
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ASSERT_NE(nullptr, preparedModelCallback.get());
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Return<ErrorStatus> prepareLaunchStatus = device->prepareModel_1_1(
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model, ExecutionPreference::FAST_SINGLE_ANSWER, preparedModelCallback);
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ASSERT_TRUE(prepareLaunchStatus.isOk());
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ASSERT_EQ(ErrorStatus::NONE, static_cast<ErrorStatus>(prepareLaunchStatus));
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// retrieve prepared model
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preparedModelCallback->wait();
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ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
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*preparedModel = preparedModelCallback->getPreparedModel();
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// The getSupportedOperations_1_1 call returns a list of operations that are
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// guaranteed not to fail if prepareModel_1_1 is called, and
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// 'fullySupportsModel' is true i.f.f. the entire model is guaranteed.
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// If a driver has any doubt that it can prepare an operation, it must
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// return false. So here, if a driver isn't sure if it can support an
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// operation, but reports that it successfully prepared the model, the test
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// can continue.
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if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) {
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ASSERT_EQ(nullptr, preparedModel->get());
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LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot "
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"prepare model that it does not support.";
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std::cout << "[ ] Unable to test Request validation because vendor service "
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"cannot prepare model that it does not support."
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<< std::endl;
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return;
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}
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ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus);
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ASSERT_NE(nullptr, preparedModel->get());
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}
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// Primary validation function. This function will take a valid request, apply a
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// mutation to it to invalidate the request, then pass it to interface calls
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// that use the request. Note that the request here is passed by value, and any
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// mutation to the request does not leave this function.
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static void validate(const sp<IPreparedModel>& preparedModel, const std::string& message,
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Request request, const std::function<void(Request*)>& mutation) {
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mutation(&request);
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SCOPED_TRACE(message + " [execute]");
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sp<ExecutionCallback> executionCallback = new ExecutionCallback();
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ASSERT_NE(nullptr, executionCallback.get());
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Return<ErrorStatus> executeLaunchStatus = preparedModel->execute(request, executionCallback);
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ASSERT_TRUE(executeLaunchStatus.isOk());
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ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(executeLaunchStatus));
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executionCallback->wait();
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ErrorStatus executionReturnStatus = executionCallback->getStatus();
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ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionReturnStatus);
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}
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// Delete element from hidl_vec. hidl_vec doesn't support a "remove" operation,
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// so this is efficiently accomplished by moving the element to the end and
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// resizing the hidl_vec to one less.
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template <typename Type>
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static void hidl_vec_removeAt(hidl_vec<Type>* vec, uint32_t index) {
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if (vec) {
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std::rotate(vec->begin() + index, vec->begin() + index + 1, vec->end());
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vec->resize(vec->size() - 1);
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}
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}
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template <typename Type>
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static uint32_t hidl_vec_push_back(hidl_vec<Type>* vec, const Type& value) {
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// assume vec is valid
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const uint32_t index = vec->size();
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vec->resize(index + 1);
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(*vec)[index] = value;
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return index;
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}
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///////////////////////// REMOVE INPUT ////////////////////////////////////
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static void removeInputTest(const sp<IPreparedModel>& preparedModel, const Request& request) {
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for (size_t input = 0; input < request.inputs.size(); ++input) {
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const std::string message = "removeInput: removed input " + std::to_string(input);
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validate(preparedModel, message, request,
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[input](Request* request) { hidl_vec_removeAt(&request->inputs, input); });
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}
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}
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///////////////////////// REMOVE OUTPUT ////////////////////////////////////
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static void removeOutputTest(const sp<IPreparedModel>& preparedModel, const Request& request) {
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for (size_t output = 0; output < request.outputs.size(); ++output) {
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const std::string message = "removeOutput: removed Output " + std::to_string(output);
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validate(preparedModel, message, request,
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[output](Request* request) { hidl_vec_removeAt(&request->outputs, output); });
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}
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}
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///////////////////////////// ENTRY POINT //////////////////////////////////
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std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples) {
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const uint32_t INPUT = 0;
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const uint32_t OUTPUT = 1;
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std::vector<Request> requests;
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for (auto& example : examples) {
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const MixedTyped& inputs = example.operands.first;
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const MixedTyped& outputs = example.operands.second;
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std::vector<RequestArgument> inputs_info, outputs_info;
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uint32_t inputSize = 0, outputSize = 0;
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// This function only partially specifies the metadata (vector of RequestArguments).
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// The contents are copied over below.
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for_all(inputs, [&inputs_info, &inputSize](int index, auto, auto s) {
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if (inputs_info.size() <= static_cast<size_t>(index)) inputs_info.resize(index + 1);
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RequestArgument arg = {
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.location = {.poolIndex = INPUT, .offset = 0, .length = static_cast<uint32_t>(s)},
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.dimensions = {},
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};
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RequestArgument arg_empty = {
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.hasNoValue = true,
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};
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inputs_info[index] = s ? arg : arg_empty;
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inputSize += s;
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});
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// Compute offset for inputs 1 and so on
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{
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size_t offset = 0;
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for (auto& i : inputs_info) {
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if (!i.hasNoValue) i.location.offset = offset;
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offset += i.location.length;
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}
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}
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// Go through all outputs, initialize RequestArgument descriptors
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for_all(outputs, [&outputs_info, &outputSize](int index, auto, auto s) {
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if (outputs_info.size() <= static_cast<size_t>(index)) outputs_info.resize(index + 1);
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RequestArgument arg = {
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.location = {.poolIndex = OUTPUT, .offset = 0, .length = static_cast<uint32_t>(s)},
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.dimensions = {},
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};
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outputs_info[index] = arg;
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outputSize += s;
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});
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// Compute offset for outputs 1 and so on
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{
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size_t offset = 0;
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for (auto& i : outputs_info) {
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i.location.offset = offset;
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offset += i.location.length;
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}
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}
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std::vector<hidl_memory> pools = {nn::allocateSharedMemory(inputSize),
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nn::allocateSharedMemory(outputSize)};
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if (pools[INPUT].size() == 0 || pools[OUTPUT].size() == 0) {
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return {};
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}
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// map pool
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sp<IMemory> inputMemory = mapMemory(pools[INPUT]);
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if (inputMemory == nullptr) {
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return {};
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}
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char* inputPtr = reinterpret_cast<char*>(static_cast<void*>(inputMemory->getPointer()));
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if (inputPtr == nullptr) {
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return {};
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}
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// initialize pool
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inputMemory->update();
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for_all(inputs, [&inputs_info, inputPtr](int index, auto p, auto s) {
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char* begin = (char*)p;
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char* end = begin + s;
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// TODO: handle more than one input
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std::copy(begin, end, inputPtr + inputs_info[index].location.offset);
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});
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inputMemory->commit();
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requests.push_back({.inputs = inputs_info, .outputs = outputs_info, .pools = pools});
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}
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return requests;
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}
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void ValidationTest::validateRequests(const V1_1::Model& model,
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const std::vector<Request>& requests) {
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// create IPreparedModel
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sp<IPreparedModel> preparedModel;
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ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel));
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if (preparedModel == nullptr) {
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return;
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}
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// validate each request
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for (const Request& request : requests) {
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removeInputTest(preparedModel, request);
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removeOutputTest(preparedModel, request);
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}
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}
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} // namespace functional
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} // namespace vts
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} // namespace V1_1
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} // namespace neuralnetworks
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} // namespace hardware
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} // namespace android
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