Merge changes from topic "nnapisync_1.2" am: 96e08aa749
am: fdf9aed0ec
Change-Id: I9c679ad65e7cfa8de6882e7213e176e3788d12e4
This commit is contained in:
Przemyslaw Szczepaniak
android-build-merger
commit
c56c4315b2
13 changed files with 1632 additions and 1 deletions
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@ -25,6 +25,7 @@ cc_library_static {
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static_libs: [
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"android.hardware.neuralnetworks@1.0",
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"android.hardware.neuralnetworks@1.1",
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"android.hardware.neuralnetworks@1.2",
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"android.hidl.allocator@1.0",
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"android.hidl.memory@1.0",
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"libhidlmemory",
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@ -49,8 +50,9 @@ cc_test {
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],
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defaults: ["VtsHalTargetTestDefaults"],
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static_libs: [
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"android.hardware.neuralnetworks@1.1",
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"android.hardware.neuralnetworks@1.0",
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"android.hardware.neuralnetworks@1.1",
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"android.hardware.neuralnetworks@1.2",
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"android.hidl.allocator@1.0",
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"android.hidl.memory@1.0",
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"libhidlmemory",
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@ -275,6 +275,58 @@ void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> c
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EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
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}
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// TODO: Reduce code duplication.
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void Execute(const sp<V1_2::IDevice>& device, std::function<V1_2::Model(void)> create_model,
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std::function<bool(int)> is_ignored,
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const std::vector<MixedTypedExampleType>& examples) {
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V1_2::Model model = create_model();
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// see if service can handle model
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bool fullySupportsModel = false;
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Return<void> supportedCall = device->getSupportedOperations_1_2(
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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(supportedCall.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_2(
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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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sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
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// early termination if vendor service cannot fully prepare model
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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: Early termination of test because vendor service cannot "
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"prepare model that it does not support.";
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std::cout << "[ ] Early termination of test because vendor service cannot "
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"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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EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
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ASSERT_NE(nullptr, preparedModel.get());
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// TODO: Adjust the error limit based on testing.
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// If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
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float fpAtol = !model.relaxComputationFloat32toFloat16 ? 1e-5f : 5.0f * 0.0009765625f;
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// Set the relative tolerance to be 5ULP of the corresponding FP precision.
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float fpRtol = !model.relaxComputationFloat32toFloat16 ? 5.0f * 1.1920928955078125e-7f
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: 5.0f * 0.0009765625f;
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EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
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}
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} // namespace generated_tests
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} // namespace neuralnetworks
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@ -28,6 +28,7 @@ cc_test {
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static_libs: [
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"android.hardware.neuralnetworks@1.0",
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"android.hardware.neuralnetworks@1.1",
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"android.hardware.neuralnetworks@1.2",
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"android.hidl.allocator@1.0",
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"android.hidl.memory@1.0",
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"libhidlmemory",
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14
neuralnetworks/1.2/vts/OWNERS
Normal file
14
neuralnetworks/1.2/vts/OWNERS
Normal file
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@ -0,0 +1,14 @@
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# Neuralnetworks team
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butlermichael@google.com
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dgross@google.com
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jeanluc@google.com
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levp@google.com
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miaowang@google.com
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mikie@google.com
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mks@google.com
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pszczepaniak@google.com
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slavash@google.com
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# VTS team
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yim@google.com
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yuexima@google.com
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52
neuralnetworks/1.2/vts/functional/Android.bp
Normal file
52
neuralnetworks/1.2/vts/functional/Android.bp
Normal file
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@ -0,0 +1,52 @@
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//
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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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cc_test {
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name: "VtsHalNeuralnetworksV1_2TargetTest",
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srcs: [
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"BasicTests.cpp",
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"GeneratedTests.cpp",
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"ValidateModel.cpp",
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"ValidateRequest.cpp",
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"ValidationTests.cpp",
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"VtsHalNeuralnetworks.cpp",
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],
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defaults: ["VtsHalTargetTestDefaults"],
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static_libs: [
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"android.hardware.neuralnetworks@1.0",
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"android.hardware.neuralnetworks@1.1",
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"android.hardware.neuralnetworks@1.2",
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"android.hidl.allocator@1.0",
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"android.hidl.memory@1.0",
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"libhidlmemory",
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"libneuralnetworks_utils",
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"VtsHalNeuralnetworksTest_utils",
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],
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header_libs: [
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"libneuralnetworks_headers",
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"libneuralnetworks_generated_test_harness_headers",
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"libneuralnetworks_generated_tests",
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],
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// Bug: http://b/74200014 - Disable arm32 asan since it triggers internal
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// error in ld.gold.
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arch: {
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arm: {
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sanitize: {
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never: true,
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},
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},
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},
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}
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45
neuralnetworks/1.2/vts/functional/BasicTests.cpp
Normal file
45
neuralnetworks/1.2/vts/functional/BasicTests.cpp
Normal file
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@ -0,0 +1,45 @@
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/*
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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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namespace android {
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namespace hardware {
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namespace neuralnetworks {
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namespace V1_2 {
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namespace vts {
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namespace functional {
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using V1_1::Capabilities;
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// create device test
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TEST_F(NeuralnetworksHidlTest, CreateDevice) {}
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// status test
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TEST_F(NeuralnetworksHidlTest, StatusTest) {
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Return<DeviceStatus> status = device->getStatus();
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ASSERT_TRUE(status.isOk());
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EXPECT_EQ(DeviceStatus::AVAILABLE, static_cast<DeviceStatus>(status));
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}
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} // namespace functional
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} // namespace vts
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} // namespace V1_2
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} // namespace neuralnetworks
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} // namespace hardware
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} // namespace android
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60
neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
Normal file
60
neuralnetworks/1.2/vts/functional/GeneratedTests.cpp
Normal file
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@ -0,0 +1,60 @@
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/*
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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 generated_tests {
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using ::test_helper::MixedTypedExampleType;
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extern void Execute(const sp<V1_2::IDevice>&, std::function<V1_2::Model(void)>,
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std::function<bool(int)>, const std::vector<MixedTypedExampleType>&);
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} // namespace generated_tests
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namespace V1_2 {
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namespace vts {
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namespace functional {
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using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
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using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
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using ::android::nn::allocateSharedMemory;
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// Mixed-typed examples
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typedef generated_tests::MixedTypedExampleType MixedTypedExample;
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// in frameworks/ml/nn/runtime/tests/generated/
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#include "all_generated_V1_0_vts_tests.cpp"
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#include "all_generated_V1_1_vts_tests.cpp"
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#include "all_generated_V1_2_vts_tests.cpp"
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} // namespace functional
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} // namespace vts
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} // namespace V1_2
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} // namespace neuralnetworks
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} // namespace hardware
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} // namespace android
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378
neuralnetworks/1.2/vts/functional/Models.h
Normal file
378
neuralnetworks/1.2/vts/functional/Models.h
Normal file
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@ -0,0 +1,378 @@
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/*
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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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#ifndef VTS_HAL_NEURALNETWORKS_V1_2_VTS_FUNCTIONAL_MODELS_H
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#define VTS_HAL_NEURALNETWORKS_V1_2_VTS_FUNCTIONAL_MODELS_H
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#define LOG_TAG "neuralnetworks_hidl_hal_test"
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#include "TestHarness.h"
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#include <android/hardware/neuralnetworks/1.0/types.h>
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#include <android/hardware/neuralnetworks/1.1/types.h>
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#include <android/hardware/neuralnetworks/1.2/types.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_2 {
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namespace vts {
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namespace functional {
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using MixedTypedExample = test_helper::MixedTypedExampleType;
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#define FOR_EACH_TEST_MODEL(FN) \
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FN(add) \
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FN(add_broadcast_quant8) \
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FN(add_quant8) \
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FN(add_relaxed) \
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FN(avg_pool_float_1) \
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FN(avg_pool_float_1_relaxed) \
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FN(avg_pool_float_2) \
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FN(avg_pool_float_2_relaxed) \
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FN(avg_pool_float_3) \
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FN(avg_pool_float_3_relaxed) \
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FN(avg_pool_float_4) \
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FN(avg_pool_float_4_relaxed) \
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FN(avg_pool_float_5) \
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FN(avg_pool_float_5_relaxed) \
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FN(avg_pool_quant8_1) \
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FN(avg_pool_quant8_2) \
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FN(avg_pool_quant8_3) \
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FN(avg_pool_quant8_4) \
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FN(avg_pool_quant8_5) \
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FN(batch_to_space) \
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FN(batch_to_space_float_1) \
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FN(batch_to_space_float_1_relaxed) \
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FN(batch_to_space_quant8_1) \
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FN(batch_to_space_relaxed) \
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FN(concat_float_1) \
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FN(concat_float_1_relaxed) \
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FN(concat_float_2) \
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FN(concat_float_2_relaxed) \
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FN(concat_float_3) \
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FN(concat_float_3_relaxed) \
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FN(concat_quant8_1) \
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FN(concat_quant8_2) \
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FN(concat_quant8_3) \
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FN(conv_1_h3_w2_SAME) \
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FN(conv_1_h3_w2_SAME_relaxed) \
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FN(conv_1_h3_w2_VALID) \
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FN(conv_1_h3_w2_VALID_relaxed) \
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FN(conv_3_h3_w2_SAME) \
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FN(conv_3_h3_w2_SAME_relaxed) \
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FN(conv_3_h3_w2_VALID) \
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FN(conv_3_h3_w2_VALID_relaxed) \
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FN(conv_float) \
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FN(conv_float_2) \
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FN(conv_float_2_relaxed) \
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FN(conv_float_channels) \
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FN(conv_float_channels_relaxed) \
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FN(conv_float_channels_weights_as_inputs) \
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FN(conv_float_channels_weights_as_inputs_relaxed) \
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FN(conv_float_large) \
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FN(conv_float_large_relaxed) \
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FN(conv_float_large_weights_as_inputs) \
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FN(conv_float_large_weights_as_inputs_relaxed) \
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FN(conv_float_relaxed) \
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FN(conv_float_weights_as_inputs) \
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FN(conv_float_weights_as_inputs_relaxed) \
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FN(conv_quant8) \
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FN(conv_quant8_2) \
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FN(conv_quant8_channels) \
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FN(conv_quant8_channels_weights_as_inputs) \
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FN(conv_quant8_large) \
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FN(conv_quant8_large_weights_as_inputs) \
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FN(conv_quant8_overflow) \
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FN(conv_quant8_overflow_weights_as_inputs) \
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FN(conv_quant8_weights_as_inputs) \
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FN(depth_to_space_float_1) \
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FN(depth_to_space_float_1_relaxed) \
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FN(depth_to_space_float_2) \
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FN(depth_to_space_float_2_relaxed) \
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FN(depth_to_space_float_3) \
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FN(depth_to_space_float_3_relaxed) \
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FN(depth_to_space_quant8_1) \
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FN(depth_to_space_quant8_2) \
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FN(depthwise_conv) \
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FN(depthwise_conv2d_float) \
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FN(depthwise_conv2d_float_2) \
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FN(depthwise_conv2d_float_2_relaxed) \
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FN(depthwise_conv2d_float_large) \
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FN(depthwise_conv2d_float_large_2) \
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FN(depthwise_conv2d_float_large_2_relaxed) \
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FN(depthwise_conv2d_float_large_2_weights_as_inputs) \
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FN(depthwise_conv2d_float_large_2_weights_as_inputs_relaxed) \
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FN(depthwise_conv2d_float_large_relaxed) \
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FN(depthwise_conv2d_float_large_weights_as_inputs) \
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FN(depthwise_conv2d_float_large_weights_as_inputs_relaxed) \
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FN(depthwise_conv2d_float_relaxed) \
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FN(depthwise_conv2d_float_weights_as_inputs) \
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FN(depthwise_conv2d_float_weights_as_inputs_relaxed) \
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FN(depthwise_conv2d_quant8) \
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FN(depthwise_conv2d_quant8_2) \
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FN(depthwise_conv2d_quant8_large) \
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FN(depthwise_conv2d_quant8_large_weights_as_inputs) \
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FN(depthwise_conv2d_quant8_weights_as_inputs) \
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FN(depthwise_conv_relaxed) \
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FN(dequantize) \
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FN(dequantize_relaxed) \
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FN(div) \
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FN(div_broadcast_float) \
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FN(div_broadcast_float_relaxed) \
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FN(div_relaxed) \
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FN(embedding_lookup) \
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FN(embedding_lookup_relaxed) \
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FN(floor) \
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FN(floor_relaxed) \
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FN(fully_connected_float) \
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FN(fully_connected_float_2) \
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FN(fully_connected_float_2_relaxed) \
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FN(fully_connected_float_4d_simple) \
|
||||
FN(fully_connected_float_4d_simple_relaxed) \
|
||||
FN(fully_connected_float_large) \
|
||||
FN(fully_connected_float_large_relaxed) \
|
||||
FN(fully_connected_float_large_weights_as_inputs) \
|
||||
FN(fully_connected_float_large_weights_as_inputs_relaxed) \
|
||||
FN(fully_connected_float_relaxed) \
|
||||
FN(fully_connected_float_weights_as_inputs) \
|
||||
FN(fully_connected_float_weights_as_inputs_relaxed) \
|
||||
FN(fully_connected_quant8) \
|
||||
FN(fully_connected_quant8_2) \
|
||||
FN(fully_connected_quant8_large) \
|
||||
FN(fully_connected_quant8_large_weights_as_inputs) \
|
||||
FN(fully_connected_quant8_weights_as_inputs) \
|
||||
FN(hashtable_lookup_float) \
|
||||
FN(hashtable_lookup_float_relaxed) \
|
||||
FN(hashtable_lookup_quant8) \
|
||||
FN(l2_normalization) \
|
||||
FN(l2_normalization_2) \
|
||||
FN(l2_normalization_2_relaxed) \
|
||||
FN(l2_normalization_large) \
|
||||
FN(l2_normalization_large_relaxed) \
|
||||
FN(l2_normalization_relaxed) \
|
||||
FN(l2_pool_float) \
|
||||
FN(l2_pool_float_2) \
|
||||
FN(l2_pool_float_2_relaxed) \
|
||||
FN(l2_pool_float_large) \
|
||||
FN(l2_pool_float_large_relaxed) \
|
||||
FN(l2_pool_float_relaxed) \
|
||||
FN(local_response_norm_float_1) \
|
||||
FN(local_response_norm_float_1_relaxed) \
|
||||
FN(local_response_norm_float_2) \
|
||||
FN(local_response_norm_float_2_relaxed) \
|
||||
FN(local_response_norm_float_3) \
|
||||
FN(local_response_norm_float_3_relaxed) \
|
||||
FN(local_response_norm_float_4) \
|
||||
FN(local_response_norm_float_4_relaxed) \
|
||||
FN(logistic_float_1) \
|
||||
FN(logistic_float_1_relaxed) \
|
||||
FN(logistic_float_2) \
|
||||
FN(logistic_float_2_relaxed) \
|
||||
FN(logistic_quant8_1) \
|
||||
FN(logistic_quant8_2) \
|
||||
FN(lsh_projection) \
|
||||
FN(lsh_projection_2) \
|
||||
FN(lsh_projection_2_relaxed) \
|
||||
FN(lsh_projection_relaxed) \
|
||||
FN(lsh_projection_weights_as_inputs) \
|
||||
FN(lsh_projection_weights_as_inputs_relaxed) \
|
||||
FN(lstm) \
|
||||
FN(lstm2) \
|
||||
FN(lstm2_relaxed) \
|
||||
FN(lstm2_state) \
|
||||
FN(lstm2_state2) \
|
||||
FN(lstm2_state2_relaxed) \
|
||||
FN(lstm2_state_relaxed) \
|
||||
FN(lstm3) \
|
||||
FN(lstm3_relaxed) \
|
||||
FN(lstm3_state) \
|
||||
FN(lstm3_state2) \
|
||||
FN(lstm3_state2_relaxed) \
|
||||
FN(lstm3_state3) \
|
||||
FN(lstm3_state3_relaxed) \
|
||||
FN(lstm3_state_relaxed) \
|
||||
FN(lstm_relaxed) \
|
||||
FN(lstm_state) \
|
||||
FN(lstm_state2) \
|
||||
FN(lstm_state2_relaxed) \
|
||||
FN(lstm_state_relaxed) \
|
||||
FN(max_pool_float_1) \
|
||||
FN(max_pool_float_1_relaxed) \
|
||||
FN(max_pool_float_2) \
|
||||
FN(max_pool_float_2_relaxed) \
|
||||
FN(max_pool_float_3) \
|
||||
FN(max_pool_float_3_relaxed) \
|
||||
FN(max_pool_float_4) \
|
||||
FN(max_pool_float_4_relaxed) \
|
||||
FN(max_pool_quant8_1) \
|
||||
FN(max_pool_quant8_2) \
|
||||
FN(max_pool_quant8_3) \
|
||||
FN(max_pool_quant8_4) \
|
||||
FN(mean) \
|
||||
FN(mean_float_1) \
|
||||
FN(mean_float_1_relaxed) \
|
||||
FN(mean_float_2) \
|
||||
FN(mean_float_2_relaxed) \
|
||||
FN(mean_quant8_1) \
|
||||
FN(mean_quant8_2) \
|
||||
FN(mean_relaxed) \
|
||||
FN(mobilenet_224_gender_basic_fixed) \
|
||||
FN(mobilenet_224_gender_basic_fixed_relaxed) \
|
||||
FN(mobilenet_quantized) \
|
||||
FN(mul) \
|
||||
FN(mul_broadcast_quant8) \
|
||||
FN(mul_quant8) \
|
||||
FN(mul_relaxed) \
|
||||
FN(mul_relu) \
|
||||
FN(mul_relu_relaxed) \
|
||||
FN(pad) \
|
||||
FN(pad_float_1) \
|
||||
FN(pad_float_1_relaxed) \
|
||||
FN(pad_relaxed) \
|
||||
FN(relu1_float_1) \
|
||||
FN(relu1_float_1_relaxed) \
|
||||
FN(relu1_float_2) \
|
||||
FN(relu1_float_2_relaxed) \
|
||||
FN(relu1_quant8_1) \
|
||||
FN(relu1_quant8_2) \
|
||||
FN(relu6_float_1) \
|
||||
FN(relu6_float_1_relaxed) \
|
||||
FN(relu6_float_2) \
|
||||
FN(relu6_float_2_relaxed) \
|
||||
FN(relu6_quant8_1) \
|
||||
FN(relu6_quant8_2) \
|
||||
FN(relu_float_1) \
|
||||
FN(relu_float_1_relaxed) \
|
||||
FN(relu_float_2) \
|
||||
FN(relu_float_2_relaxed) \
|
||||
FN(relu_quant8_1) \
|
||||
FN(relu_quant8_2) \
|
||||
FN(reshape) \
|
||||
FN(reshape_quant8) \
|
||||
FN(reshape_quant8_weights_as_inputs) \
|
||||
FN(reshape_relaxed) \
|
||||
FN(reshape_weights_as_inputs) \
|
||||
FN(reshape_weights_as_inputs_relaxed) \
|
||||
FN(resize_bilinear) \
|
||||
FN(resize_bilinear_2) \
|
||||
FN(resize_bilinear_2_relaxed) \
|
||||
FN(resize_bilinear_relaxed) \
|
||||
FN(rnn) \
|
||||
FN(rnn_relaxed) \
|
||||
FN(rnn_state) \
|
||||
FN(rnn_state_relaxed) \
|
||||
FN(softmax_float_1) \
|
||||
FN(softmax_float_1_relaxed) \
|
||||
FN(softmax_float_2) \
|
||||
FN(softmax_float_2_relaxed) \
|
||||
FN(softmax_quant8_1) \
|
||||
FN(softmax_quant8_2) \
|
||||
FN(space_to_batch) \
|
||||
FN(space_to_batch_float_1) \
|
||||
FN(space_to_batch_float_1_relaxed) \
|
||||
FN(space_to_batch_float_2) \
|
||||
FN(space_to_batch_float_2_relaxed) \
|
||||
FN(space_to_batch_float_3) \
|
||||
FN(space_to_batch_float_3_relaxed) \
|
||||
FN(space_to_batch_quant8_1) \
|
||||
FN(space_to_batch_quant8_2) \
|
||||
FN(space_to_batch_quant8_3) \
|
||||
FN(space_to_batch_relaxed) \
|
||||
FN(space_to_depth_float_1) \
|
||||
FN(space_to_depth_float_1_relaxed) \
|
||||
FN(space_to_depth_float_2) \
|
||||
FN(space_to_depth_float_2_relaxed) \
|
||||
FN(space_to_depth_float_3) \
|
||||
FN(space_to_depth_float_3_relaxed) \
|
||||
FN(space_to_depth_quant8_1) \
|
||||
FN(space_to_depth_quant8_2) \
|
||||
FN(squeeze) \
|
||||
FN(squeeze_float_1) \
|
||||
FN(squeeze_float_1_relaxed) \
|
||||
FN(squeeze_quant8_1) \
|
||||
FN(squeeze_relaxed) \
|
||||
FN(strided_slice) \
|
||||
FN(strided_slice_float_1) \
|
||||
FN(strided_slice_float_10) \
|
||||
FN(strided_slice_float_10_relaxed) \
|
||||
FN(strided_slice_float_11) \
|
||||
FN(strided_slice_float_11_relaxed) \
|
||||
FN(strided_slice_float_1_relaxed) \
|
||||
FN(strided_slice_float_2) \
|
||||
FN(strided_slice_float_2_relaxed) \
|
||||
FN(strided_slice_float_3) \
|
||||
FN(strided_slice_float_3_relaxed) \
|
||||
FN(strided_slice_float_4) \
|
||||
FN(strided_slice_float_4_relaxed) \
|
||||
FN(strided_slice_float_5) \
|
||||
FN(strided_slice_float_5_relaxed) \
|
||||
FN(strided_slice_float_6) \
|
||||
FN(strided_slice_float_6_relaxed) \
|
||||
FN(strided_slice_float_7) \
|
||||
FN(strided_slice_float_7_relaxed) \
|
||||
FN(strided_slice_float_8) \
|
||||
FN(strided_slice_float_8_relaxed) \
|
||||
FN(strided_slice_float_9) \
|
||||
FN(strided_slice_float_9_relaxed) \
|
||||
FN(strided_slice_qaunt8_10) \
|
||||
FN(strided_slice_qaunt8_11) \
|
||||
FN(strided_slice_quant8_1) \
|
||||
FN(strided_slice_quant8_2) \
|
||||
FN(strided_slice_quant8_3) \
|
||||
FN(strided_slice_quant8_4) \
|
||||
FN(strided_slice_quant8_5) \
|
||||
FN(strided_slice_quant8_6) \
|
||||
FN(strided_slice_quant8_7) \
|
||||
FN(strided_slice_quant8_8) \
|
||||
FN(strided_slice_quant8_9) \
|
||||
FN(strided_slice_relaxed) \
|
||||
FN(sub) \
|
||||
FN(sub_broadcast_float) \
|
||||
FN(sub_broadcast_float_relaxed) \
|
||||
FN(sub_relaxed) \
|
||||
FN(svdf) \
|
||||
FN(svdf2) \
|
||||
FN(svdf2_relaxed) \
|
||||
FN(svdf_relaxed) \
|
||||
FN(svdf_state) \
|
||||
FN(svdf_state_relaxed) \
|
||||
FN(tanh) \
|
||||
FN(tanh_relaxed) \
|
||||
FN(transpose) \
|
||||
FN(transpose_float_1) \
|
||||
FN(transpose_float_1_relaxed) \
|
||||
FN(transpose_quant8_1) \
|
||||
FN(transpose_relaxed)
|
||||
|
||||
#define FORWARD_DECLARE_GENERATED_OBJECTS(function) \
|
||||
namespace function { \
|
||||
extern std::vector<MixedTypedExample> examples; \
|
||||
Model createTestModel(); \
|
||||
}
|
||||
|
||||
FOR_EACH_TEST_MODEL(FORWARD_DECLARE_GENERATED_OBJECTS)
|
||||
|
||||
#undef FORWARD_DECLARE_GENERATED_OBJECTS
|
||||
|
||||
} // namespace functional
|
||||
} // namespace vts
|
||||
} // namespace V1_2
|
||||
} // namespace neuralnetworks
|
||||
} // namespace hardware
|
||||
} // namespace android
|
||||
|
||||
#endif // VTS_HAL_NEURALNETWORKS_V1_2_VTS_FUNCTIONAL_MODELS_H
|
||||
538
neuralnetworks/1.2/vts/functional/ValidateModel.cpp
Normal file
538
neuralnetworks/1.2/vts/functional/ValidateModel.cpp
Normal file
|
|
@ -0,0 +1,538 @@
|
|||
/*
|
||||
* 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"
|
||||
|
||||
namespace android {
|
||||
namespace hardware {
|
||||
namespace neuralnetworks {
|
||||
namespace V1_2 {
|
||||
|
||||
using V1_0::IPreparedModel;
|
||||
using V1_0::Operand;
|
||||
using V1_0::OperandLifeTime;
|
||||
using V1_0::OperandType;
|
||||
using V1_1::ExecutionPreference;
|
||||
|
||||
namespace vts {
|
||||
namespace functional {
|
||||
|
||||
using ::android::hardware::neuralnetworks::V1_0::implementation::ExecutionCallback;
|
||||
using ::android::hardware::neuralnetworks::V1_0::implementation::PreparedModelCallback;
|
||||
|
||||
///////////////////////// UTILITY FUNCTIONS /////////////////////////
|
||||
|
||||
static void validateGetSupportedOperations(const sp<IDevice>& device, const std::string& message,
|
||||
const Model& model) {
|
||||
SCOPED_TRACE(message + " [getSupportedOperations_1_2]");
|
||||
|
||||
Return<void> ret =
|
||||
device->getSupportedOperations_1_2(model, [&](ErrorStatus status, const hidl_vec<bool>&) {
|
||||
EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, status);
|
||||
});
|
||||
EXPECT_TRUE(ret.isOk());
|
||||
}
|
||||
|
||||
static void validatePrepareModel(const sp<IDevice>& device, const std::string& message,
|
||||
const Model& model, ExecutionPreference preference) {
|
||||
SCOPED_TRACE(message + " [prepareModel_1_2]");
|
||||
|
||||
sp<PreparedModelCallback> preparedModelCallback = new PreparedModelCallback();
|
||||
ASSERT_NE(nullptr, preparedModelCallback.get());
|
||||
Return<ErrorStatus> prepareLaunchStatus =
|
||||
device->prepareModel_1_2(model, preference, preparedModelCallback);
|
||||
ASSERT_TRUE(prepareLaunchStatus.isOk());
|
||||
ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, static_cast<ErrorStatus>(prepareLaunchStatus));
|
||||
|
||||
preparedModelCallback->wait();
|
||||
ErrorStatus prepareReturnStatus = preparedModelCallback->getStatus();
|
||||
ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, prepareReturnStatus);
|
||||
sp<IPreparedModel> preparedModel = preparedModelCallback->getPreparedModel();
|
||||
ASSERT_EQ(nullptr, preparedModel.get());
|
||||
}
|
||||
|
||||
static bool validExecutionPreference(ExecutionPreference preference) {
|
||||
return preference == ExecutionPreference::LOW_POWER ||
|
||||
preference == ExecutionPreference::FAST_SINGLE_ANSWER ||
|
||||
preference == ExecutionPreference::SUSTAINED_SPEED;
|
||||
}
|
||||
|
||||
// Primary validation function. This function will take a valid model, apply a
|
||||
// mutation to it to invalidate the model, then pass it to interface calls that
|
||||
// use the model. Note that the model here is passed by value, and any mutation
|
||||
// to the model does not leave this function.
|
||||
static void validate(const sp<IDevice>& device, const std::string& message, Model model,
|
||||
const std::function<void(Model*)>& mutation,
|
||||
ExecutionPreference preference = ExecutionPreference::FAST_SINGLE_ANSWER) {
|
||||
mutation(&model);
|
||||
if (validExecutionPreference(preference)) {
|
||||
validateGetSupportedOperations(device, message, model);
|
||||
}
|
||||
validatePrepareModel(device, message, model, preference);
|
||||
}
|
||||
|
||||
// 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;
|
||||
}
|
||||
|
||||
static uint32_t addOperand(Model* model) {
|
||||
return hidl_vec_push_back(&model->operands,
|
||||
{
|
||||
.type = OperandType::INT32,
|
||||
.dimensions = {},
|
||||
.numberOfConsumers = 0,
|
||||
.scale = 0.0f,
|
||||
.zeroPoint = 0,
|
||||
.lifetime = OperandLifeTime::MODEL_INPUT,
|
||||
.location = {.poolIndex = 0, .offset = 0, .length = 0},
|
||||
});
|
||||
}
|
||||
|
||||
static uint32_t addOperand(Model* model, OperandLifeTime lifetime) {
|
||||
uint32_t index = addOperand(model);
|
||||
model->operands[index].numberOfConsumers = 1;
|
||||
model->operands[index].lifetime = lifetime;
|
||||
return index;
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE MODEL OPERAND TYPE /////////////////////////
|
||||
|
||||
static const int32_t invalidOperandTypes[] = {
|
||||
static_cast<int32_t>(OperandType::FLOAT32) - 1, // lower bound fundamental
|
||||
static_cast<int32_t>(OperandType::TENSOR_QUANT8_ASYMM) + 1, // upper bound fundamental
|
||||
static_cast<int32_t>(OperandType::OEM) - 1, // lower bound OEM
|
||||
static_cast<int32_t>(OperandType::TENSOR_OEM_BYTE) + 1, // upper bound OEM
|
||||
};
|
||||
|
||||
static void mutateOperandTypeTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
|
||||
for (int32_t invalidOperandType : invalidOperandTypes) {
|
||||
const std::string message = "mutateOperandTypeTest: operand " +
|
||||
std::to_string(operand) + " set to value " +
|
||||
std::to_string(invalidOperandType);
|
||||
validate(device, message, model, [operand, invalidOperandType](Model* model) {
|
||||
model->operands[operand].type = static_cast<OperandType>(invalidOperandType);
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE OPERAND RANK /////////////////////////
|
||||
|
||||
static uint32_t getInvalidRank(OperandType type) {
|
||||
switch (type) {
|
||||
case OperandType::FLOAT32:
|
||||
case OperandType::INT32:
|
||||
case OperandType::UINT32:
|
||||
return 1;
|
||||
case OperandType::TENSOR_FLOAT32:
|
||||
case OperandType::TENSOR_INT32:
|
||||
case OperandType::TENSOR_QUANT8_ASYMM:
|
||||
return 0;
|
||||
default:
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
|
||||
static void mutateOperandRankTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
|
||||
const uint32_t invalidRank = getInvalidRank(model.operands[operand].type);
|
||||
const std::string message = "mutateOperandRankTest: operand " + std::to_string(operand) +
|
||||
" has rank of " + std::to_string(invalidRank);
|
||||
validate(device, message, model, [operand, invalidRank](Model* model) {
|
||||
model->operands[operand].dimensions = std::vector<uint32_t>(invalidRank, 0);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE OPERAND SCALE /////////////////////////
|
||||
|
||||
static float getInvalidScale(OperandType type) {
|
||||
switch (type) {
|
||||
case OperandType::FLOAT32:
|
||||
case OperandType::INT32:
|
||||
case OperandType::UINT32:
|
||||
case OperandType::TENSOR_FLOAT32:
|
||||
return 1.0f;
|
||||
case OperandType::TENSOR_INT32:
|
||||
return -1.0f;
|
||||
case OperandType::TENSOR_QUANT8_ASYMM:
|
||||
return 0.0f;
|
||||
default:
|
||||
return 0.0f;
|
||||
}
|
||||
}
|
||||
|
||||
static void mutateOperandScaleTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
|
||||
const float invalidScale = getInvalidScale(model.operands[operand].type);
|
||||
const std::string message = "mutateOperandScaleTest: operand " + std::to_string(operand) +
|
||||
" has scale of " + std::to_string(invalidScale);
|
||||
validate(device, message, model, [operand, invalidScale](Model* model) {
|
||||
model->operands[operand].scale = invalidScale;
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE OPERAND ZERO POINT /////////////////////////
|
||||
|
||||
static std::vector<int32_t> getInvalidZeroPoints(OperandType type) {
|
||||
switch (type) {
|
||||
case OperandType::FLOAT32:
|
||||
case OperandType::INT32:
|
||||
case OperandType::UINT32:
|
||||
case OperandType::TENSOR_FLOAT32:
|
||||
case OperandType::TENSOR_INT32:
|
||||
return {1};
|
||||
case OperandType::TENSOR_QUANT8_ASYMM:
|
||||
return {-1, 256};
|
||||
default:
|
||||
return {};
|
||||
}
|
||||
}
|
||||
|
||||
static void mutateOperandZeroPointTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
|
||||
const std::vector<int32_t> invalidZeroPoints =
|
||||
getInvalidZeroPoints(model.operands[operand].type);
|
||||
for (int32_t invalidZeroPoint : invalidZeroPoints) {
|
||||
const std::string message = "mutateOperandZeroPointTest: operand " +
|
||||
std::to_string(operand) + " has zero point of " +
|
||||
std::to_string(invalidZeroPoint);
|
||||
validate(device, message, model, [operand, invalidZeroPoint](Model* model) {
|
||||
model->operands[operand].zeroPoint = invalidZeroPoint;
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE EXTRA ??? /////////////////////////
|
||||
|
||||
// TODO: Operand::lifetime
|
||||
// TODO: Operand::location
|
||||
|
||||
///////////////////////// VALIDATE OPERATION OPERAND TYPE /////////////////////////
|
||||
|
||||
static void mutateOperand(Operand* operand, OperandType type) {
|
||||
Operand newOperand = *operand;
|
||||
newOperand.type = type;
|
||||
switch (type) {
|
||||
case OperandType::FLOAT32:
|
||||
case OperandType::INT32:
|
||||
case OperandType::UINT32:
|
||||
newOperand.dimensions = hidl_vec<uint32_t>();
|
||||
newOperand.scale = 0.0f;
|
||||
newOperand.zeroPoint = 0;
|
||||
break;
|
||||
case OperandType::TENSOR_FLOAT32:
|
||||
newOperand.dimensions =
|
||||
operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
|
||||
newOperand.scale = 0.0f;
|
||||
newOperand.zeroPoint = 0;
|
||||
break;
|
||||
case OperandType::TENSOR_INT32:
|
||||
newOperand.dimensions =
|
||||
operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
|
||||
newOperand.zeroPoint = 0;
|
||||
break;
|
||||
case OperandType::TENSOR_QUANT8_ASYMM:
|
||||
newOperand.dimensions =
|
||||
operand->dimensions.size() > 0 ? operand->dimensions : hidl_vec<uint32_t>({1});
|
||||
newOperand.scale = operand->scale != 0.0f ? operand->scale : 1.0f;
|
||||
break;
|
||||
case OperandType::OEM:
|
||||
case OperandType::TENSOR_OEM_BYTE:
|
||||
default:
|
||||
break;
|
||||
}
|
||||
*operand = newOperand;
|
||||
}
|
||||
|
||||
static bool mutateOperationOperandTypeSkip(size_t operand, const Model& model) {
|
||||
// LSH_PROJECTION's second argument is allowed to have any type. This is the
|
||||
// only operation that currently has a type that can be anything independent
|
||||
// from any other type. Changing the operand type to any other type will
|
||||
// result in a valid model for LSH_PROJECTION. If this is the case, skip the
|
||||
// test.
|
||||
for (const Operation& operation : model.operations) {
|
||||
if (operation.type == OperationType::LSH_PROJECTION && operand == operation.inputs[1]) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
static void mutateOperationOperandTypeTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
|
||||
if (mutateOperationOperandTypeSkip(operand, model)) {
|
||||
continue;
|
||||
}
|
||||
for (OperandType invalidOperandType : hidl_enum_range<OperandType>{}) {
|
||||
// Do not test OEM types
|
||||
if (invalidOperandType == model.operands[operand].type ||
|
||||
invalidOperandType == OperandType::OEM ||
|
||||
invalidOperandType == OperandType::TENSOR_OEM_BYTE) {
|
||||
continue;
|
||||
}
|
||||
const std::string message = "mutateOperationOperandTypeTest: operand " +
|
||||
std::to_string(operand) + " set to type " +
|
||||
toString(invalidOperandType);
|
||||
validate(device, message, model, [operand, invalidOperandType](Model* model) {
|
||||
mutateOperand(&model->operands[operand], invalidOperandType);
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE MODEL OPERATION TYPE /////////////////////////
|
||||
|
||||
static const int32_t invalidOperationTypes[] = {
|
||||
static_cast<int32_t>(OperationType::ADD) - 1, // lower bound fundamental
|
||||
static_cast<int32_t>(OperationType::TRANSPOSE) + 1, // upper bound fundamental
|
||||
static_cast<int32_t>(OperationType::OEM_OPERATION) - 1, // lower bound OEM
|
||||
static_cast<int32_t>(OperationType::OEM_OPERATION) + 1, // upper bound OEM
|
||||
};
|
||||
|
||||
static void mutateOperationTypeTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
for (int32_t invalidOperationType : invalidOperationTypes) {
|
||||
const std::string message = "mutateOperationTypeTest: operation " +
|
||||
std::to_string(operation) + " set to value " +
|
||||
std::to_string(invalidOperationType);
|
||||
validate(device, message, model, [operation, invalidOperationType](Model* model) {
|
||||
model->operations[operation].type =
|
||||
static_cast<OperationType>(invalidOperationType);
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE MODEL OPERATION INPUT OPERAND INDEX /////////////////////////
|
||||
|
||||
static void mutateOperationInputOperandIndexTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
const uint32_t invalidOperand = model.operands.size();
|
||||
for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
|
||||
const std::string message = "mutateOperationInputOperandIndexTest: operation " +
|
||||
std::to_string(operation) + " input " +
|
||||
std::to_string(input);
|
||||
validate(device, message, model, [operation, input, invalidOperand](Model* model) {
|
||||
model->operations[operation].inputs[input] = invalidOperand;
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE MODEL OPERATION OUTPUT OPERAND INDEX /////////////////////////
|
||||
|
||||
static void mutateOperationOutputOperandIndexTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
const uint32_t invalidOperand = model.operands.size();
|
||||
for (size_t output = 0; output < model.operations[operation].outputs.size(); ++output) {
|
||||
const std::string message = "mutateOperationOutputOperandIndexTest: operation " +
|
||||
std::to_string(operation) + " output " +
|
||||
std::to_string(output);
|
||||
validate(device, message, model, [operation, output, invalidOperand](Model* model) {
|
||||
model->operations[operation].outputs[output] = invalidOperand;
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// REMOVE OPERAND FROM EVERYTHING /////////////////////////
|
||||
|
||||
static void removeValueAndDecrementGreaterValues(hidl_vec<uint32_t>* vec, uint32_t value) {
|
||||
if (vec) {
|
||||
// remove elements matching "value"
|
||||
auto last = std::remove(vec->begin(), vec->end(), value);
|
||||
vec->resize(std::distance(vec->begin(), last));
|
||||
|
||||
// decrement elements exceeding "value"
|
||||
std::transform(vec->begin(), vec->end(), vec->begin(),
|
||||
[value](uint32_t v) { return v > value ? v-- : v; });
|
||||
}
|
||||
}
|
||||
|
||||
static void removeOperand(Model* model, uint32_t index) {
|
||||
hidl_vec_removeAt(&model->operands, index);
|
||||
for (Operation& operation : model->operations) {
|
||||
removeValueAndDecrementGreaterValues(&operation.inputs, index);
|
||||
removeValueAndDecrementGreaterValues(&operation.outputs, index);
|
||||
}
|
||||
removeValueAndDecrementGreaterValues(&model->inputIndexes, index);
|
||||
removeValueAndDecrementGreaterValues(&model->outputIndexes, index);
|
||||
}
|
||||
|
||||
static void removeOperandTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operand = 0; operand < model.operands.size(); ++operand) {
|
||||
const std::string message = "removeOperandTest: operand " + std::to_string(operand);
|
||||
validate(device, message, model,
|
||||
[operand](Model* model) { removeOperand(model, operand); });
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// REMOVE OPERATION /////////////////////////
|
||||
|
||||
static void removeOperation(Model* model, uint32_t index) {
|
||||
for (uint32_t operand : model->operations[index].inputs) {
|
||||
model->operands[operand].numberOfConsumers--;
|
||||
}
|
||||
hidl_vec_removeAt(&model->operations, index);
|
||||
}
|
||||
|
||||
static void removeOperationTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
const std::string message = "removeOperationTest: operation " + std::to_string(operation);
|
||||
validate(device, message, model,
|
||||
[operation](Model* model) { removeOperation(model, operation); });
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// REMOVE OPERATION INPUT /////////////////////////
|
||||
|
||||
static void removeOperationInputTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
for (size_t input = 0; input < model.operations[operation].inputs.size(); ++input) {
|
||||
const Operation& op = model.operations[operation];
|
||||
// CONCATENATION has at least 2 inputs, with the last element being
|
||||
// INT32. Skip this test if removing one of CONCATENATION's
|
||||
// inputs still produces a valid model.
|
||||
if (op.type == OperationType::CONCATENATION && op.inputs.size() > 2 &&
|
||||
input != op.inputs.size() - 1) {
|
||||
continue;
|
||||
}
|
||||
const std::string message = "removeOperationInputTest: operation " +
|
||||
std::to_string(operation) + ", input " +
|
||||
std::to_string(input);
|
||||
validate(device, message, model, [operation, input](Model* model) {
|
||||
uint32_t operand = model->operations[operation].inputs[input];
|
||||
model->operands[operand].numberOfConsumers--;
|
||||
hidl_vec_removeAt(&model->operations[operation].inputs, input);
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// REMOVE OPERATION OUTPUT /////////////////////////
|
||||
|
||||
static void removeOperationOutputTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
for (size_t output = 0; output < model.operations[operation].outputs.size(); ++output) {
|
||||
const std::string message = "removeOperationOutputTest: operation " +
|
||||
std::to_string(operation) + ", output " +
|
||||
std::to_string(output);
|
||||
validate(device, message, model, [operation, output](Model* model) {
|
||||
hidl_vec_removeAt(&model->operations[operation].outputs, output);
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// MODEL VALIDATION /////////////////////////
|
||||
|
||||
// TODO: remove model input
|
||||
// TODO: remove model output
|
||||
// TODO: add unused operation
|
||||
|
||||
///////////////////////// ADD OPERATION INPUT /////////////////////////
|
||||
|
||||
static void addOperationInputTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
const std::string message = "addOperationInputTest: operation " + std::to_string(operation);
|
||||
validate(device, message, model, [operation](Model* model) {
|
||||
uint32_t index = addOperand(model, OperandLifeTime::MODEL_INPUT);
|
||||
hidl_vec_push_back(&model->operations[operation].inputs, index);
|
||||
hidl_vec_push_back(&model->inputIndexes, index);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// ADD OPERATION OUTPUT /////////////////////////
|
||||
|
||||
static void addOperationOutputTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (size_t operation = 0; operation < model.operations.size(); ++operation) {
|
||||
const std::string message =
|
||||
"addOperationOutputTest: operation " + std::to_string(operation);
|
||||
validate(device, message, model, [operation](Model* model) {
|
||||
uint32_t index = addOperand(model, OperandLifeTime::MODEL_OUTPUT);
|
||||
hidl_vec_push_back(&model->operations[operation].outputs, index);
|
||||
hidl_vec_push_back(&model->outputIndexes, index);
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////// VALIDATE EXECUTION PREFERENCE /////////////////////////
|
||||
|
||||
static const int32_t invalidExecutionPreferences[] = {
|
||||
static_cast<int32_t>(ExecutionPreference::LOW_POWER) - 1, // lower bound
|
||||
static_cast<int32_t>(ExecutionPreference::SUSTAINED_SPEED) + 1, // upper bound
|
||||
};
|
||||
|
||||
static void mutateExecutionPreferenceTest(const sp<IDevice>& device, const Model& model) {
|
||||
for (int32_t preference : invalidExecutionPreferences) {
|
||||
const std::string message =
|
||||
"mutateExecutionPreferenceTest: preference " + std::to_string(preference);
|
||||
validate(device, message, model, [](Model*) {},
|
||||
static_cast<ExecutionPreference>(preference));
|
||||
}
|
||||
}
|
||||
|
||||
////////////////////////// ENTRY POINT //////////////////////////////
|
||||
|
||||
void ValidationTest::validateModel(const Model& model) {
|
||||
mutateOperandTypeTest(device, model);
|
||||
mutateOperandRankTest(device, model);
|
||||
mutateOperandScaleTest(device, model);
|
||||
mutateOperandZeroPointTest(device, model);
|
||||
mutateOperationOperandTypeTest(device, model);
|
||||
mutateOperationTypeTest(device, model);
|
||||
mutateOperationInputOperandIndexTest(device, model);
|
||||
mutateOperationOutputOperandIndexTest(device, model);
|
||||
removeOperandTest(device, model);
|
||||
removeOperationTest(device, model);
|
||||
removeOperationInputTest(device, model);
|
||||
removeOperationOutputTest(device, model);
|
||||
addOperationInputTest(device, model);
|
||||
addOperationOutputTest(device, model);
|
||||
mutateExecutionPreferenceTest(device, model);
|
||||
}
|
||||
|
||||
} // namespace functional
|
||||
} // namespace vts
|
||||
} // namespace V1_2
|
||||
} // namespace neuralnetworks
|
||||
} // namespace hardware
|
||||
} // namespace android
|
||||
261
neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
Normal file
261
neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
Normal file
|
|
@ -0,0 +1,261 @@
|
|||
/*
|
||||
* 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_2 {
|
||||
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::for_all;
|
||||
using test_helper::MixedTyped;
|
||||
using test_helper::MixedTypedExampleType;
|
||||
|
||||
///////////////////////// UTILITY FUNCTIONS /////////////////////////
|
||||
|
||||
static void createPreparedModel(const sp<IDevice>& device, const Model& model,
|
||||
sp<IPreparedModel>* preparedModel) {
|
||||
ASSERT_NE(nullptr, preparedModel);
|
||||
|
||||
// see if service can handle model
|
||||
bool fullySupportsModel = false;
|
||||
Return<void> supportedOpsLaunchStatus = device->getSupportedOperations_1_2(
|
||||
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_1_2(
|
||||
model, ExecutionPreference::FAST_SINGLE_ANSWER, 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_1_2 call returns a list of operations that are
|
||||
// guaranteed not to fail if prepareModel_1_2 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 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_2
|
||||
} // namespace neuralnetworks
|
||||
} // namespace hardware
|
||||
} // namespace android
|
||||
50
neuralnetworks/1.2/vts/functional/ValidationTests.cpp
Normal file
50
neuralnetworks/1.2/vts/functional/ValidationTests.cpp
Normal file
|
|
@ -0,0 +1,50 @@
|
|||
/*
|
||||
* 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 "Models.h"
|
||||
#include "VtsHalNeuralnetworks.h"
|
||||
|
||||
namespace android {
|
||||
namespace hardware {
|
||||
namespace neuralnetworks {
|
||||
namespace V1_2 {
|
||||
namespace vts {
|
||||
namespace functional {
|
||||
|
||||
// forward declarations
|
||||
std::vector<Request> createRequests(const std::vector<MixedTypedExample>& examples);
|
||||
|
||||
// generate validation tests
|
||||
#define VTS_CURRENT_TEST_CASE(TestName) \
|
||||
TEST_F(ValidationTest, TestName) { \
|
||||
const Model model = TestName::createTestModel(); \
|
||||
const std::vector<Request> requests = createRequests(TestName::examples); \
|
||||
validateModel(model); \
|
||||
validateRequests(model, requests); \
|
||||
}
|
||||
|
||||
FOR_EACH_TEST_MODEL(VTS_CURRENT_TEST_CASE)
|
||||
|
||||
#undef VTS_CURRENT_TEST_CASE
|
||||
|
||||
} // namespace functional
|
||||
} // namespace vts
|
||||
} // namespace V1_2
|
||||
} // namespace neuralnetworks
|
||||
} // namespace hardware
|
||||
} // namespace android
|
||||
86
neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
Normal file
86
neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.cpp
Normal file
|
|
@ -0,0 +1,86 @@
|
|||
/*
|
||||
* 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"
|
||||
|
||||
namespace android {
|
||||
namespace hardware {
|
||||
namespace neuralnetworks {
|
||||
namespace V1_2 {
|
||||
namespace vts {
|
||||
namespace functional {
|
||||
|
||||
// A class for test environment setup
|
||||
NeuralnetworksHidlEnvironment::NeuralnetworksHidlEnvironment() {}
|
||||
|
||||
NeuralnetworksHidlEnvironment::~NeuralnetworksHidlEnvironment() {}
|
||||
|
||||
NeuralnetworksHidlEnvironment* NeuralnetworksHidlEnvironment::getInstance() {
|
||||
// This has to return a "new" object because it is freed inside
|
||||
// ::testing::AddGlobalTestEnvironment when the gtest is being torn down
|
||||
static NeuralnetworksHidlEnvironment* instance = new NeuralnetworksHidlEnvironment();
|
||||
return instance;
|
||||
}
|
||||
|
||||
void NeuralnetworksHidlEnvironment::registerTestServices() {
|
||||
registerTestService<IDevice>();
|
||||
}
|
||||
|
||||
// The main test class for NEURALNETWORK HIDL HAL.
|
||||
NeuralnetworksHidlTest::NeuralnetworksHidlTest() {}
|
||||
|
||||
NeuralnetworksHidlTest::~NeuralnetworksHidlTest() {}
|
||||
|
||||
void NeuralnetworksHidlTest::SetUp() {
|
||||
::testing::VtsHalHidlTargetTestBase::SetUp();
|
||||
device = ::testing::VtsHalHidlTargetTestBase::getService<IDevice>(
|
||||
NeuralnetworksHidlEnvironment::getInstance());
|
||||
ASSERT_NE(nullptr, device.get());
|
||||
}
|
||||
|
||||
void NeuralnetworksHidlTest::TearDown() {
|
||||
device = nullptr;
|
||||
::testing::VtsHalHidlTargetTestBase::TearDown();
|
||||
}
|
||||
|
||||
} // namespace functional
|
||||
} // namespace vts
|
||||
|
||||
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus) {
|
||||
return os << toString(errorStatus);
|
||||
}
|
||||
|
||||
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus) {
|
||||
return os << toString(deviceStatus);
|
||||
}
|
||||
|
||||
} // namespace V1_2
|
||||
} // namespace neuralnetworks
|
||||
} // namespace hardware
|
||||
} // namespace android
|
||||
|
||||
using android::hardware::neuralnetworks::V1_2::vts::functional::NeuralnetworksHidlEnvironment;
|
||||
|
||||
int main(int argc, char** argv) {
|
||||
::testing::AddGlobalTestEnvironment(NeuralnetworksHidlEnvironment::getInstance());
|
||||
::testing::InitGoogleTest(&argc, argv);
|
||||
NeuralnetworksHidlEnvironment::getInstance()->init(&argc, argv);
|
||||
|
||||
int status = RUN_ALL_TESTS();
|
||||
return status;
|
||||
}
|
||||
92
neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
Normal file
92
neuralnetworks/1.2/vts/functional/VtsHalNeuralnetworks.h
Normal file
|
|
@ -0,0 +1,92 @@
|
|||
/*
|
||||
* 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.
|
||||
*/
|
||||
|
||||
#ifndef VTS_HAL_NEURALNETWORKS_V1_2_H
|
||||
#define VTS_HAL_NEURALNETWORKS_V1_2_H
|
||||
|
||||
#include <android/hardware/neuralnetworks/1.0/types.h>
|
||||
#include <android/hardware/neuralnetworks/1.1/types.h>
|
||||
#include <android/hardware/neuralnetworks/1.2/IDevice.h>
|
||||
#include <android/hardware/neuralnetworks/1.2/types.h>
|
||||
|
||||
#include <VtsHalHidlTargetTestBase.h>
|
||||
#include <VtsHalHidlTargetTestEnvBase.h>
|
||||
|
||||
#include <android-base/macros.h>
|
||||
#include <gtest/gtest.h>
|
||||
#include <iostream>
|
||||
#include <vector>
|
||||
|
||||
namespace android {
|
||||
namespace hardware {
|
||||
namespace neuralnetworks {
|
||||
namespace V1_2 {
|
||||
|
||||
using V1_0::DeviceStatus;
|
||||
using V1_0::ErrorStatus;
|
||||
using V1_0::Request;
|
||||
|
||||
namespace vts {
|
||||
namespace functional {
|
||||
|
||||
// A class for test environment setup
|
||||
class NeuralnetworksHidlEnvironment : public ::testing::VtsHalHidlTargetTestEnvBase {
|
||||
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlEnvironment);
|
||||
NeuralnetworksHidlEnvironment();
|
||||
~NeuralnetworksHidlEnvironment() override;
|
||||
|
||||
public:
|
||||
static NeuralnetworksHidlEnvironment* getInstance();
|
||||
void registerTestServices() override;
|
||||
};
|
||||
|
||||
// The main test class for NEURALNETWORKS HIDL HAL.
|
||||
class NeuralnetworksHidlTest : public ::testing::VtsHalHidlTargetTestBase {
|
||||
DISALLOW_COPY_AND_ASSIGN(NeuralnetworksHidlTest);
|
||||
|
||||
public:
|
||||
NeuralnetworksHidlTest();
|
||||
~NeuralnetworksHidlTest() override;
|
||||
void SetUp() override;
|
||||
void TearDown() override;
|
||||
|
||||
protected:
|
||||
sp<IDevice> device;
|
||||
};
|
||||
|
||||
// Tag for the validation tests
|
||||
class ValidationTest : public NeuralnetworksHidlTest {
|
||||
protected:
|
||||
void validateModel(const Model& model);
|
||||
void validateRequests(const Model& model, const std::vector<Request>& request);
|
||||
};
|
||||
|
||||
// Tag for the generated tests
|
||||
class GeneratedTest : public NeuralnetworksHidlTest {};
|
||||
|
||||
} // namespace functional
|
||||
} // namespace vts
|
||||
|
||||
// pretty-print values for error messages
|
||||
::std::ostream& operator<<(::std::ostream& os, ErrorStatus errorStatus);
|
||||
::std::ostream& operator<<(::std::ostream& os, DeviceStatus deviceStatus);
|
||||
|
||||
} // namespace V1_2
|
||||
} // namespace neuralnetworks
|
||||
} // namespace hardware
|
||||
} // namespace android
|
||||
|
||||
#endif // VTS_HAL_NEURALNETWORKS_V1_2_H
|
||||
Loading…
Reference in a new issue