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Clean up Clip tests
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@adrianlizarraga
adrianlizarraga committed Sep 19, 2023
1 parent 80c8fb4 commit e5de983
Showing 1 changed file with 22 additions and 47 deletions.
69 changes: 22 additions & 47 deletions onnxruntime/test/providers/qnn/clip_op_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -17,7 +17,8 @@ namespace test {
// Runs a model with a Clip operator on the QNN CPU backend. Checks the graph node assignment
// and that inference outputs for QNN EP and CPU EP match.
template <typename DataType>
static void RunClipTestOnCPU(const std::vector<TestInputDef<DataType>>& input_defs,
static void RunClipTestOnCPU(const TestInputDef<DataType>& input_def,
const std::vector<TestInputDef<DataType>>& min_max_defs,
ExpectedEPNodeAssignment expected_ep_assignment,
int opset = 13) {
ProviderOptions provider_options;
Expand All @@ -28,7 +29,7 @@ static void RunClipTestOnCPU(const std::vector<TestInputDef<DataType>>& input_de
provider_options["backend_path"] = "libQnnCpu.so";
#endif

RunQnnModelTest(BuildOpTestCase<DataType>("Clip", input_defs, {}, {}),
RunQnnModelTest(BuildOpTestCase<DataType, DataType>("Clip", {input_def}, min_max_defs, {}),
provider_options,
opset,
expected_ep_assignment);
Expand All @@ -41,26 +42,27 @@ static void RunClipTestOnCPU(const std::vector<TestInputDef<DataType>>& input_de
// Test that Clip with a dynamic min or max input is not supported by QNN EP.
TEST_F(QnnCPUBackendTests, Clip_Dynamic_MinMax_Unsupported) {
// Dynamic min input is not supported.
RunClipTestOnCPU<float>({TestInputDef<float>({1, 3, 4, 4}, false, -10.0f, 10.0f),
TestInputDef<float>({}, false /* is_initializer */, {-5.0f})},
RunClipTestOnCPU<float>(TestInputDef<float>({1, 3, 4, 4}, false, -10.0f, 10.0f),
{TestInputDef<float>({}, false /* is_initializer */, {-5.0f})},
ExpectedEPNodeAssignment::None); // Should not be assigned to QNN EP.
// Dynamic max input is not supported.
RunClipTestOnCPU<float>({TestInputDef<float>({1, 3, 4, 4}, false, -10.0f, 10.0f),
TestInputDef<float>({}, true, {-5.0f}),
RunClipTestOnCPU<float>(TestInputDef<float>({1, 3, 4, 4}, false, -10.0f, 10.0f),
{TestInputDef<float>({}, true, {-5.0f}),
TestInputDef<float>({}, false, {5.0f})},
ExpectedEPNodeAssignment::None); // Should not be assigned to QNN EP.
}

// Test Clip with default min/max.
TEST_F(QnnCPUBackendTests, Clip_4D_f32_DefaultMinMax) {
RunClipTestOnCPU<float>({TestInputDef<float>({1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48))},
RunClipTestOnCPU<float>(TestInputDef<float>({1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48)),
{}, // Don't specify min/max inputs.
ExpectedEPNodeAssignment::All);
}

// Test Clip with 5D input.
TEST_F(QnnCPUBackendTests, Clip_5D_f32) {
RunClipTestOnCPU<float>({TestInputDef<float>({1, 1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48)),
TestInputDef<float>({}, true, {-5.0f}),
RunClipTestOnCPU<float>(TestInputDef<float>({1, 1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48)),
{TestInputDef<float>({}, true, {-5.0f}),
TestInputDef<float>({}, true, {5.0f})},
ExpectedEPNodeAssignment::All);
}
Expand All @@ -70,42 +72,11 @@ TEST_F(QnnCPUBackendTests, Clip_5D_f32) {
// HTP tests:
//

// Returns a function that builds a model with a QDQ Clip operator. Only the first input is quantized.
template <typename InputQType>
inline GetTestQDQModelFn<InputQType> BuildQDQClipTestCase(const std::vector<TestInputDef<float>>& input_defs) {
return [input_defs](ModelTestBuilder& builder, std::vector<QuantParams<InputQType>>& output_qparams) {
const size_t num_inputs = input_defs.size();
std::vector<NodeArg*> op_inputs;
op_inputs.reserve(num_inputs);

for (size_t i = 0; i < num_inputs; i++) {
const TestInputDef<float>& input_def = input_defs[i];
NodeArg* input = MakeTestInput<float>(builder, input_def);

if (i == 0) { // Only input 0 is quantized.
QuantParams<InputQType> input_qparams = GetTestInputQuantParams<InputQType>(input_def);
NodeArg* input_after_qdq = AddQDQNodePair<InputQType>(builder, input, input_qparams.scale,
input_qparams.zero_point);
op_inputs.push_back(input_after_qdq);
} else {
op_inputs.push_back(input);
}
}

// Op -> op_output
auto* clip_output = builder.MakeIntermediate();
builder.AddNode("Clip", op_inputs, {clip_output});

// op_output -> Q -> DQ -> output
AddQDQNodePairWithOutputAsGraphOutput<InputQType>(builder, clip_output, output_qparams[0].scale,
output_qparams[0].zero_point);
};
}

// Runs a QDQ Clip model on the QNN (HTP) EP and the ORT CPU EP. Checks the graph node assignment and that inference
// running the QDQ model on QNN EP is at least as accurate as on ORT CPU EP (when compared to the baseline float32 model).
template <typename QType>
static void RunQDQClipTestOnHTP(const std::vector<TestInputDef<float>>& input_defs,
static void RunQDQClipTestOnHTP(const TestInputDef<float>& input_def,
const std::vector<TestInputDef<float>>& min_max_defs,
ExpectedEPNodeAssignment expected_ep_assignment,
int opset = 13) {
ProviderOptions provider_options;
Expand All @@ -116,8 +87,11 @@ static void RunQDQClipTestOnHTP(const std::vector<TestInputDef<float>>& input_de
provider_options["backend_path"] = "libQnnHtp.so";
#endif

TestQDQModelAccuracy(BuildOpTestCase<float>("Clip", input_defs, {}, {}), // baseline float32 model
BuildQDQClipTestCase<QType>(input_defs), // QDQ model
auto f32_model_builder = BuildOpTestCase<float, float>("Clip", {input_def}, {min_max_defs}, {});
auto qdq_model_builder = BuildQDQOpTestCase<QType, float>("Clip", {input_def}, {min_max_defs}, {});

TestQDQModelAccuracy(f32_model_builder,
qdq_model_builder,
provider_options,
opset,
expected_ep_assignment);
Expand All @@ -130,14 +104,15 @@ static void RunQDQClipTestOnHTP(const std::vector<TestInputDef<float>>& input_de
// - ClipQuantFusion: Fuses Clip -> QuantizeLinear resulting in Q1 -> DQ1 -> Q2' -> DQ2
// - DoubleQDQPairsRemover: Simplifies remaining Q1 -> DQ1 -> Q2' -> DQ2 sequence to Q1 -> DQ2.
TEST_F(QnnHTPBackendTests, Clip_U8_DefaultMinMax_Rank4) {
RunQDQClipTestOnHTP<uint8_t>({TestInputDef<float>({1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48))},
RunQDQClipTestOnHTP<uint8_t>(TestInputDef<float>({1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48)),
{}, // Don't specify min/max inputs.
ExpectedEPNodeAssignment::All);
}

// Test QDQ Clip with non-default min and max inputs. QNN EP will get a graph with a Clip operator.
TEST_F(QnnHTPBackendTests, Clip_U8_Rank4) {
RunQDQClipTestOnHTP<uint8_t>({TestInputDef<float>({1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48)),
TestInputDef<float>({}, true, {-5.0f}),
RunQDQClipTestOnHTP<uint8_t>(TestInputDef<float>({1, 3, 4, 4}, false, GetFloatDataInRange(-10.0f, 10.0f, 48)),
{TestInputDef<float>({}, true, {-5.0f}),
TestInputDef<float>({}, true, {5.0f})},
ExpectedEPNodeAssignment::All);
}
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