/* * 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. */ #define LOG_TAG "neuralnetworks_hidl_hal_test" #include "VtsHalNeuralnetworks.h" #include "Callbacks.h" #include "TestHarness.h" #include "Utils.h" #include <android-base/logging.h> #include <android/hidl/memory/1.0/IMemory.h> #include <hidlmemory/mapping.h> namespace android { namespace hardware { namespace neuralnetworks { namespace V1_0 { namespace vts { namespace functional { 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::MixedTyped; using test_helper::MixedTypedExampleType; using test_helper::for_all; ///////////////////////// UTILITY FUNCTIONS ///////////////////////// static void createPreparedModel(const sp<IDevice>& device, const V1_0::Model& model, sp<IPreparedModel>* preparedModel) { ASSERT_NE(nullptr, preparedModel); // see if service can handle model bool fullySupportsModel = false; Return<void> supportedOpsLaunchStatus = device->getSupportedOperations( model, [&fullySupportsModel](ErrorStatus status, const hidl_vec<bool>& supported) { ASSERT_EQ(ErrorStatus::NONE, status); ASSERT_NE(0ul, supported.size()); fullySupportsModel = std::all_of(supported.begin(), supported.end(), [](bool valid) { return valid; }); }); ASSERT_TRUE(supportedOpsLaunchStatus.isOk()); // 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)); // retrieve prepared model preparedModelCallback->wait(); ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus(); *preparedModel = preparedModelCallback->getPreparedModel(); // The getSupportedOperations call returns a list of operations that are // guaranteed not to fail if prepareModel is called, and // 'fullySupportsModel' is true i.f.f. the entire model is guaranteed. // If a driver has any doubt that it can prepare an operation, it must // return false. So here, if a driver isn't sure if it can support an // operation, but reports that it successfully prepared the model, the test // can continue. if (!fullySupportsModel && prepareReturnStatus != ErrorStatus::NONE) { ASSERT_EQ(nullptr, preparedModel->get()); LOG(INFO) << "NN VTS: Unable to test Request validation because vendor service cannot " "prepare model that it does not support."; std::cout << "[ ] Unable to test Request validation because vendor service " "cannot prepare model that it does not support." << std::endl; return; } ASSERT_EQ(ErrorStatus::NONE, prepareReturnStatus); ASSERT_NE(nullptr, preparedModel->get()); } // Primary validation function. This function will take a valid request, apply a // mutation to it to invalidate the request, then pass it to interface calls // that use the request. Note that the request here is passed by value, and any // mutation to the request does not leave this function. static void validate(const sp<IPreparedModel>& preparedModel, const std::string& message, Request request, const std::function<void(Request*)>& mutation) { mutation(&request); SCOPED_TRACE(message + " [execute]"); sp<ExecutionCallback> executionCallback = new ExecutionCallback(); ASSERT_NE(nullptr, executionCallback.get()); Return<ErrorStatus> executeLaunchStatus = preparedModel->execute(request, executionCallback); ASSERT_TRUE(executeLaunchStatus.isOk()); ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(executeLaunchStatus)); executionCallback->wait(); ErrorStatus executionReturnStatus = executionCallback->getStatus(); ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionReturnStatus); } // 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 // resizing the hidl_vec to one less. template <typename Type> static void hidl_vec_removeAt(hidl_vec<Type>* vec, uint32_t index) { if (vec) { std::rotate(vec->begin() + index, vec->begin() + index + 1, vec->end()); vec->resize(vec->size() - 1); } } template <typename Type> static uint32_t hidl_vec_push_back(hidl_vec<Type>* vec, const Type& value) { // assume vec is valid const uint32_t index = vec->size(); vec->resize(index + 1); (*vec)[index] = value; return index; } ///////////////////////// REMOVE INPUT //////////////////////////////////// static void removeInputTest(const sp<IPreparedModel>& preparedModel, const Request& request) { for (size_t input = 0; input < request.inputs.size(); ++input) { const std::string message = "removeInput: removed input " + std::to_string(input); validate(preparedModel, message, request, [input](Request* request) { hidl_vec_removeAt(&request->inputs, input); }); } } ///////////////////////// REMOVE OUTPUT //////////////////////////////////// static void removeOutputTest(const sp<IPreparedModel>& preparedModel, const Request& request) { for (size_t output = 0; output < request.outputs.size(); ++output) { const std::string message = "removeOutput: removed Output " + std::to_string(output); validate(preparedModel, message, request, [output](Request* request) { hidl_vec_removeAt(&request->outputs, output); }); } } ///////////////////////////// ENTRY POINT ////////////////////////////////// std::vector<Request> createRequests(const std::vector<MixedTypedExampleType>& examples) { const uint32_t INPUT = 0; const uint32_t OUTPUT = 1; std::vector<Request> requests; for (auto& example : examples) { const MixedTyped& inputs = example.first; const MixedTyped& outputs = example.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 V1_0::Model& model, const std::vector<Request>& requests) { // create IPreparedModel sp<IPreparedModel> preparedModel; ASSERT_NO_FATAL_FAILURE(createPreparedModel(device, model, &preparedModel)); if (preparedModel == nullptr) { return; } // validate each request for (const Request& request : requests) { removeInputTest(preparedModel, request); removeOutputTest(preparedModel, request); } } } // namespace functional } // namespace vts } // namespace V1_0 } // namespace neuralnetworks } // namespace hardware } // namespace android