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Adds float16 support to generated tests.

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Uses the _Float16 type (ISO/IEC TS 18661-3:2015) for storage.

Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Bug: 113563458
Change-Id: I1779b828d397b5354dc854c68d21c159cd5b582c
Merged-In: I1779b828d397b5354dc854c68d21c159cd5b582c
(cherry picked from commit efa4c814fb)
This commit is contained in:
Michael K. Sanders 2018-10-30 14:44:48 +00:00 committed by Lev Proleev
parent a8efddc558
commit 650fd186e4
1 changed files with 20 additions and 19 deletions
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39
neuralnetworks/1.0/vts/functional/GeneratedTestHarness.cpp
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@ -45,6 +45,7 @@ using ::test_helper::for_each;
using ::test_helper::Int32Operands;
using ::test_helper::MixedTyped;
using ::test_helper::MixedTypedExample;
using ::test_helper::MixedTypedIndex;
using ::test_helper::Quant8Operands;
using ::test_helper::resize_accordingly;
@ -63,14 +64,16 @@ void copy_back(MixedTyped* dst, const std::vector<RequestArgument>& ra, char* sr
copy_back_<int32_t>(dst, ra, src);
copy_back_<uint8_t>(dst, ra, src);
copy_back_<int16_t>(dst, ra, src);
static_assert(4 == std::tuple_size<MixedTyped>::value,
copy_back_<_Float16>(dst, ra, src);
static_assert(5 == std::tuple_size<MixedTyped>::value,
"Number of types in MixedTyped changed, but copy_back function wasn't updated");
}
// Top level driver for models and examples generated by test_generator.py
// Test driver for those generated from ml/nn/runtime/test/spec
void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool(int)> is_ignored,
const std::vector<MixedTypedExample>& examples, float fpAtol = 1e-5f,
const std::vector<MixedTypedExample>& examples,
bool hasRelaxedFloat32Model = false, float fpAtol = 1e-5f,
float fpRtol = 1e-5f) {
const uint32_t INPUT = 0;
const uint32_t OUTPUT = 1;
@ -78,13 +81,20 @@ void EvaluatePreparedModel(sp<IPreparedModel>& preparedModel, std::function<bool
int example_no = 1;
for (auto& example : examples) {
SCOPED_TRACE(example_no++);
const MixedTyped& inputs = example.operands.first;
const MixedTyped& golden = example.operands.second;
const bool hasFloat16Inputs = !std::get<MixedTypedIndex<_Float16>::index>(inputs).empty();
if (hasRelaxedFloat32Model || hasFloat16Inputs) {
// TODO: Adjust the error limit based on testing.
// If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
fpAtol = 5.0f * 0.0009765625f;
// Set the relative tolerance to be 5ULP of the corresponding FP precision.
fpRtol = 5.0f * 0.0009765625f;
}
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) {
@ -228,7 +238,8 @@ void Execute(const sp<V1_0::IDevice>& device, std::function<V1_0::Model(void)> c
ASSERT_NE(nullptr, preparedModel.get());
float fpAtol = 1e-5f, fpRtol = 5.0f * 1.1920928955078125e-7f;
EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
EvaluatePreparedModel(preparedModel, is_ignored, examples,
/*hasRelaxedFloat32Model=*/false, fpAtol, fpRtol);
}
void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> create_model,
@ -272,13 +283,8 @@ void Execute(const sp<V1_1::IDevice>& device, std::function<V1_1::Model(void)> c
EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel.get());
// TODO: Adjust the error limit based on testing.
// If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
float fpAtol = !model.relaxComputationFloat32toFloat16 ? 1e-5f : 5.0f * 0.0009765625f;
// Set the relative tolerance to be 5ULP of the corresponding FP precision.
float fpRtol = !model.relaxComputationFloat32toFloat16 ? 5.0f * 1.1920928955078125e-7f
: 5.0f * 0.0009765625f;
EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
EvaluatePreparedModel(preparedModel, is_ignored, examples,
model.relaxComputationFloat32toFloat16);
}
// TODO: Reduce code duplication.
@ -323,13 +329,8 @@ void Execute(const sp<V1_2::IDevice>& device, std::function<V1_2::Model(void)> c
EXPECT_EQ(ErrorStatus::NONE, prepareReturnStatus);
ASSERT_NE(nullptr, preparedModel.get());
// TODO: Adjust the error limit based on testing.
// If in relaxed mode, set the absolute tolerance to be 5ULP of FP16.
float fpAtol = !model.relaxComputationFloat32toFloat16 ? 1e-5f : 5.0f * 0.0009765625f;
// Set the relative tolerance to be 5ULP of the corresponding FP precision.
float fpRtol = !model.relaxComputationFloat32toFloat16 ? 5.0f * 1.1920928955078125e-7f
: 5.0f * 0.0009765625f;
EvaluatePreparedModel(preparedModel, is_ignored, examples, fpAtol, fpRtol);
EvaluatePreparedModel(preparedModel, is_ignored, examples,
model.relaxComputationFloat32toFloat16);
}
} // namespace generated_tests