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Merge changes from topics "executeFenced_tests", "nnapi-decouple-1.2"

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* changes:
  NNAPI VTS: decouple 1.2 tests from 1.3 types
  Add tests to make sure executeFenced validate unspecified output shapes
  Add more tests exercising IPreparedModel::executeFenced API
This commit is contained in:
Slava Shklyaev
2020-03-17 12:27:31 +00:00
committed by Gerrit Code Review
parent 326e2454d9 d09c0eef0b
commit 8db59c363b
7 changed files with 51 additions and 37 deletions
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14
neuralnetworks/1.2/vts/functional/Android.bp
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@@ -28,7 +28,7 @@ cc_library_static {
],
header_libs: [
"libbase_headers",
]
],
}
cc_test {
@@ -39,9 +39,9 @@ cc_test {
"CompilationCachingTests.cpp",
"GeneratedTestHarness.cpp",
"TestAssertions.cpp",
"ValidateBurst.cpp",
"ValidateModel.cpp",
"ValidateRequest.cpp",
"ValidateBurst.cpp",
"VtsHalNeuralnetworks.cpp",
],
local_include_dirs: ["include"],
@@ -50,18 +50,17 @@ cc_test {
"libnativewindow",
],
static_libs: [
"VtsHalNeuralNetworksV1_0_utils",
"VtsHalNeuralNetworksV1_2Callbacks",
"android.hardware.neuralnetworks@1.0",
"android.hardware.neuralnetworks@1.1",
"android.hardware.neuralnetworks@1.2",
"android.hardware.neuralnetworks@1.3",
"android.hidl.allocator@1.0",
"android.hidl.memory@1.0",
"libgmock",
"libhidlmemory",
"libneuralnetworks_generated_test_harness",
"libneuralnetworks_utils",
"VtsHalNeuralNetworksV1_0_utils",
"VtsHalNeuralNetworksV1_2Callbacks",
],
whole_static_libs: [
"neuralnetworks_generated_V1_0_example",
@@ -71,5 +70,8 @@ cc_test {
header_libs: [
"libneuralnetworks_headers",
],
test_suites: ["general-tests", "vts-core"],
test_suites: [
"general-tests",
"vts-core",
],
}

1
neuralnetworks/1.2/vts/functional/CompilationCachingTests.cpp
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@@ -32,7 +32,6 @@
#include "GeneratedTestHarness.h"
#include "MemoryUtils.h"
#include "TestHarness.h"
#include "Utils.h"
#include "VtsHalNeuralnetworks.h"
// Forward declaration of the mobilenet generated test models in

3
neuralnetworks/1.2/vts/functional/GeneratedTestHarness.cpp
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@@ -43,7 +43,6 @@
#include "ExecutionBurstController.h"
#include "MemoryUtils.h"
#include "TestHarness.h"
#include "Utils.h"
#include "VtsHalNeuralnetworks.h"
namespace android::hardware::neuralnetworks::V1_2::vts::functional {
@@ -273,7 +272,7 @@ void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestMo
int n;
std::tie(n, outputShapes, timing, std::ignore) =
controller->compute(request, testConfig.measureTiming, keys);
executionStatus = nn::convertToV1_0(nn::convertResultCodeToErrorStatus(n));
executionStatus = nn::legacyConvertResultCodeToErrorStatus(n);
break;
}

6
neuralnetworks/1.2/vts/functional/ValidateBurst.cpp
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@@ -23,7 +23,6 @@
#include "ExecutionBurstServer.h"
#include "GeneratedTestHarness.h"
#include "TestHarness.h"
#include "Utils.h"
#include <android-base/logging.h>
#include <chrono>
@@ -296,8 +295,7 @@ static void validateBurstFmqLength(const sp<IPreparedModel>& preparedModel,
// collect serialized result by running regular burst
const auto [nRegular, outputShapesRegular, timingRegular, fallbackRegular] =
controllerRegular->compute(request, MeasureTiming::NO, keys);
const ErrorStatus statusRegular =
nn::convertToV1_0(nn::convertResultCodeToErrorStatus(nRegular));
const ErrorStatus statusRegular = nn::legacyConvertResultCodeToErrorStatus(nRegular);
EXPECT_FALSE(fallbackRegular);
// skip test if regular burst output isn't useful for testing a failure
@@ -313,7 +311,7 @@ static void validateBurstFmqLength(const sp<IPreparedModel>& preparedModel,
// large enough to return the serialized result
const auto [nSmall, outputShapesSmall, timingSmall, fallbackSmall] =
controllerSmall->compute(request, MeasureTiming::NO, keys);
const ErrorStatus statusSmall = nn::convertToV1_0(nn::convertResultCodeToErrorStatus(nSmall));
const ErrorStatus statusSmall = nn::legacyConvertResultCodeToErrorStatus(nSmall);
EXPECT_NE(ErrorStatus::NONE, statusSmall);
EXPECT_EQ(0u, outputShapesSmall.size());
EXPECT_TRUE(badTiming(timingSmall));

3
neuralnetworks/1.2/vts/functional/ValidateRequest.cpp
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@@ -22,7 +22,6 @@
#include "ExecutionBurstController.h"
#include "GeneratedTestHarness.h"
#include "TestHarness.h"
#include "Utils.h"
#include "VtsHalNeuralnetworks.h"
namespace android::hardware::neuralnetworks::V1_2::vts::functional {
@@ -107,7 +106,7 @@ static void validate(const sp<IPreparedModel>& preparedModel, const std::string&
// execute and verify
const auto [n, outputShapes, timing, fallback] = burst->compute(request, measure, keys);
const ErrorStatus status = nn::convertToV1_0(nn::convertResultCodeToErrorStatus(n));
const ErrorStatus status = nn::legacyConvertResultCodeToErrorStatus(n);
EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, status);
EXPECT_EQ(outputShapes.size(), 0);
EXPECT_TRUE(badTiming(timing));

54
neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
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@@ -626,21 +626,28 @@ void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>&
ErrorStatus result;
hidl_handle syncFenceHandle;
sp<IFencedExecutionCallback> fencedCallback;
Return<void> ret = preparedModel->executeFenced(
request, {}, testConfig.measureTiming, {}, loopTimeoutDuration, {},
[&result, &syncFenceHandle, &fencedCallback](
ErrorStatus error, const hidl_handle& handle,
const sp<IFencedExecutionCallback>& callback) {
result = error;
syncFenceHandle = handle;
fencedCallback = callback;
});
auto callbackFunc = [&result, &syncFenceHandle, &fencedCallback](
ErrorStatus error, const hidl_handle& handle,
const sp<IFencedExecutionCallback>& callback) {
result = error;
syncFenceHandle = handle;
fencedCallback = callback;
};
Return<void> ret =
preparedModel->executeFenced(request, {}, testConfig.measureTiming, {},
loopTimeoutDuration, {}, callbackFunc);
ASSERT_TRUE(ret.isOk());
if (result != ErrorStatus::NONE) {
ASSERT_EQ(syncFenceHandle.getNativeHandle(), nullptr);
ASSERT_EQ(fencedCallback, nullptr);
executionStatus = ErrorStatus::GENERAL_FAILURE;
executionStatus = result;
} else if (syncFenceHandle.getNativeHandle()) {
// If a sync fence is returned, try start another run waiting for the sync fence.
ret = preparedModel->executeFenced(request, {syncFenceHandle},
testConfig.measureTiming, {},
loopTimeoutDuration, {}, callbackFunc);
ASSERT_TRUE(ret.isOk());
ASSERT_EQ(result, ErrorStatus::NONE);
waitForSyncFence(syncFenceHandle.getNativeHandle()->data[0]);
}
if (result == ErrorStatus::NONE) {
@@ -656,9 +663,7 @@ void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>&
}
}
// The driver is allowed to reject executeFenced, and if they do, we should skip.
if ((testConfig.outputType != OutputType::FULLY_SPECIFIED ||
testConfig.executor == Executor::FENCED) &&
if (testConfig.outputType != OutputType::FULLY_SPECIFIED &&
executionStatus == ErrorStatus::GENERAL_FAILURE) {
if (skipped != nullptr) {
*skipped = true;
@@ -691,12 +696,22 @@ void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>&
outputShapes.size() == testModel.main.outputIndexes.size());
break;
case OutputType::UNSPECIFIED:
if (testConfig.executor == Executor::FENCED) {
// For Executor::FENCED, the output shape must be fully specified.
ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus);
return;
}
// If the model output operands are not fully specified, outputShapes must have
// the same number of elements as the number of outputs.
ASSERT_EQ(ErrorStatus::NONE, executionStatus);
ASSERT_EQ(outputShapes.size(), testModel.main.outputIndexes.size());
break;
case OutputType::INSUFFICIENT:
if (testConfig.executor == Executor::FENCED) {
// For Executor::FENCED, the output shape must be fully specified.
ASSERT_EQ(ErrorStatus::INVALID_ARGUMENT, executionStatus);
return;
}
ASSERT_EQ(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, executionStatus);
ASSERT_EQ(outputShapes.size(), testModel.main.outputIndexes.size());
ASSERT_FALSE(outputShapes[0].isSufficient);
@@ -739,12 +754,12 @@ void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>&
case TestKind::DYNAMIC_SHAPE: {
outputTypesList = {OutputType::UNSPECIFIED, OutputType::INSUFFICIENT};
measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};
executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST, Executor::FENCED};
} break;
case TestKind::MEMORY_DOMAIN: {
outputTypesList = {OutputType::FULLY_SPECIFIED};
measureTimingList = {MeasureTiming::NO};
executorList = {Executor::ASYNC, Executor::SYNC};
executorList = {Executor::ASYNC, Executor::SYNC, Executor::FENCED};
memoryType = MemoryType::DEVICE;
} break;
case TestKind::FENCED_COMPUTE: {
@@ -921,8 +936,13 @@ INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest, [](const TestModel& testModel
INSTANTIATE_GENERATED_TEST(MemoryDomainTest,
[](const TestModel& testModel) { return !testModel.expectFailure; });
INSTANTIATE_GENERATED_TEST(FencedComputeTest,
[](const TestModel& testModel) { return !testModel.expectFailure; });
INSTANTIATE_GENERATED_TEST(FencedComputeTest, [](const TestModel& testModel) {
return !testModel.expectFailure &&
std::all_of(testModel.main.outputIndexes.begin(), testModel.main.outputIndexes.end(),
[&testModel](uint32_t index) {
return testModel.main.operands[index].data.size() > 0;
});
});
INSTANTIATE_GENERATED_TEST(QuantizationCouplingTest, [](const TestModel& testModel) {
return testModel.hasQuant8CoupledOperands() && testModel.main.operations.size() == 1;

7
neuralnetworks/1.3/vts/functional/ValidateBurst.cpp
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@@ -23,7 +23,6 @@
#include "ExecutionBurstServer.h"
#include "GeneratedTestHarness.h"
#include "TestHarness.h"
#include "Utils.h"
#include <android-base/logging.h>
#include <chrono>
@@ -302,8 +301,7 @@ static void validateBurstFmqLength(const sp<IPreparedModel>& preparedModel,
// collect serialized result by running regular burst
const auto [nRegular, outputShapesRegular, timingRegular, fallbackRegular] =
controllerRegular->compute(request, MeasureTiming::NO, keys);
const V1_0::ErrorStatus statusRegular =
nn::convertToV1_0(nn::convertResultCodeToErrorStatus(nRegular));
const V1_0::ErrorStatus statusRegular = nn::legacyConvertResultCodeToErrorStatus(nRegular);
EXPECT_FALSE(fallbackRegular);
// skip test if regular burst output isn't useful for testing a failure
@@ -319,8 +317,7 @@ static void validateBurstFmqLength(const sp<IPreparedModel>& preparedModel,
// large enough to return the serialized result
const auto [nSmall, outputShapesSmall, timingSmall, fallbackSmall] =
controllerSmall->compute(request, MeasureTiming::NO, keys);
const V1_0::ErrorStatus statusSmall =
nn::convertToV1_0(nn::convertResultCodeToErrorStatus(nSmall));
const V1_0::ErrorStatus statusSmall = nn::legacyConvertResultCodeToErrorStatus(nSmall);
EXPECT_NE(V1_0::ErrorStatus::NONE, statusSmall);
EXPECT_EQ(0u, outputShapesSmall.size());
EXPECT_TRUE(badTiming(timingSmall));