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Update module/test .pte file
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Differential Revision: D62260916

Pull Request resolved: pytorch#5116
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@lucylq
lucylq authored Sep 5, 2024
1 parent 89829b5 commit 3c58237
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Showing 4 changed files with 61 additions and 48 deletions.
105 changes: 57 additions & 48 deletions extension/module/test/module_test.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ namespace torch::executor {
class ModuleTest : public ::testing::Test {
protected:
static void SetUpTestSuite() {
model_path_ = std::getenv("RESOURCES_PATH") + std::string("/model.pte");
model_path_ = std::getenv("RESOURCES_PATH") + std::string("/add.pte");
}

static std::string model_path_;
Expand Down Expand Up @@ -95,17 +95,16 @@ TEST_F(ModuleTest, TestMethodMeta) {
const auto meta = module.method_meta("forward");
EXPECT_TRUE(meta.ok());
EXPECT_STREQ(meta->name(), "forward");
EXPECT_EQ(meta->num_inputs(), 1);
EXPECT_EQ(meta->num_inputs(), 2);
EXPECT_EQ(*(meta->input_tag(0)), Tag::Tensor);
EXPECT_EQ(meta->num_outputs(), 1);
EXPECT_EQ(*(meta->output_tag(0)), Tag::Tensor);

const auto input_meta = meta->input_tensor_meta(0);
EXPECT_TRUE(input_meta.ok());
EXPECT_EQ(input_meta->scalar_type(), ScalarType::Float);
EXPECT_EQ(input_meta->sizes().size(), 2);
EXPECT_EQ(input_meta->sizes().size(), 1);
EXPECT_EQ(input_meta->sizes()[0], 1);
EXPECT_EQ(input_meta->sizes()[1], 2);

const auto output_meta = meta->output_tensor_meta(0);
EXPECT_TRUE(output_meta.ok());
Expand All @@ -124,19 +123,22 @@ TEST_F(ModuleTest, TestNonExistentMethodMeta) {
TEST_F(ModuleTest, TestExecute) {
Module module(model_path_);

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());

const auto result = module.execute("forward", Tensor(&tensor));
const auto result =
module.execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result.ok());

EXPECT_TRUE(result.ok());
EXPECT_TRUE(module.is_loaded());
EXPECT_TRUE(module.is_method_loaded("forward"));

const auto data = result->at(0).toTensor().const_data_ptr<float>();

EXPECT_NEAR(data[0], 1.5, 1e-5);
EXPECT_NEAR(data[0], 2, 1e-5);
}

TEST_F(ModuleTest, TestExecutePreload) {
Expand All @@ -145,17 +147,18 @@ TEST_F(ModuleTest, TestExecutePreload) {
const auto error = module.load();
EXPECT_EQ(error, Error::Ok);

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());

const auto result = module.execute("forward", Tensor(&tensor));
const auto result =
module.execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result.ok());

const auto data = result->at(0).toTensor().const_data_ptr<float>();

EXPECT_NEAR(data[0], 1.5, 1e-5);
EXPECT_NEAR(data[0], 2, 1e-5);
}

TEST_F(ModuleTest, TestExecutePreload_method) {
Expand All @@ -164,17 +167,18 @@ TEST_F(ModuleTest, TestExecutePreload_method) {
const auto error = module.load_method("forward");
EXPECT_EQ(error, Error::Ok);

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());

const auto result = module.execute("forward", Tensor(&tensor));
const auto result =
module.execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result.ok());

const auto data = result->at(0).toTensor().const_data_ptr<float>();

EXPECT_NEAR(data[0], 1.5, 1e-5);
EXPECT_NEAR(data[0], 2, 1e-5);
}

TEST_F(ModuleTest, TestExecutePreloadProgramAndMethod) {
Expand All @@ -186,17 +190,18 @@ TEST_F(ModuleTest, TestExecutePreloadProgramAndMethod) {
const auto load_method_error = module.load_method("forward");
EXPECT_EQ(load_method_error, Error::Ok);

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());

const auto result = module.execute("forward", Tensor(&tensor));
const auto result =
module.execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result.ok());

const auto data = result->at(0).toTensor().const_data_ptr<float>();

EXPECT_NEAR(data[0], 1.5, 1e-5);
EXPECT_NEAR(data[0], 2, 1e-5);
}

TEST_F(ModuleTest, TestExecuteOnNonExistent) {
Expand All @@ -218,41 +223,42 @@ TEST_F(ModuleTest, TestExecuteOnCurrupted) {
TEST_F(ModuleTest, TestGet) {
Module module(model_path_);

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());

const auto result = module.get("forward", Tensor(&tensor));
const auto result = module.get("forward", {Tensor(&tensor), Tensor(&tensor)});

EXPECT_TRUE(result.ok());
const auto data = result->toTensor().const_data_ptr<float>();
EXPECT_NEAR(data[0], 1.5, 1e-5);
EXPECT_NEAR(data[0], 2, 1e-5);
}

TEST_F(ModuleTest, TestForward) {
auto module = std::make_unique<Module>(model_path_);

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());
const auto result = module->forward(Tensor(&tensor));

const auto result = module->forward({Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result.ok());

const auto data = result->at(0).toTensor().const_data_ptr<float>();

EXPECT_NEAR(data[0], 1.5, 1e-5);
EXPECT_NEAR(data[0], 2, 1e-5);

std::array<float, 2> input2{2, 3};
TensorImpl tensor2(
ScalarType::Float, sizes.size(), sizes.data(), input2.data());
const auto result2 = module->forward(Tensor(&tensor2));
const auto result2 = module->forward({Tensor(&tensor2), Tensor(&tensor2)});
EXPECT_TRUE(result2.ok());

const auto data2 = result->at(0).toTensor().const_data_ptr<float>();

EXPECT_NEAR(data2[0], 2.5, 1e-5);
EXPECT_NEAR(data2[0], 4, 1e-5);
}

TEST_F(ModuleTest, TestForwardWithInvalidInputs) {
Expand Down Expand Up @@ -303,23 +309,26 @@ TEST_F(ModuleTest, TestProgramSharingAndDataLoaderManagement) {
EXPECT_EQ(load_error, Error::Ok);
EXPECT_TRUE(module1->is_loaded());

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());

auto result1 = module1->execute("forward", Tensor(&tensor));
auto result1 =
module1->execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result1.ok());

auto module2 = std::make_unique<Module>(module1->program());

auto result2 = module2->execute("forward", Tensor(&tensor));
auto result2 =
module2->execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result2.ok());

module1 = std::make_unique<Module>("/path/to/nonexistent/file.pte");
EXPECT_FALSE(module1->is_loaded());

auto result3 = module2->execute("forward", Tensor(&tensor));
auto result3 =
module2->execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result3.ok());
}

Expand Down Expand Up @@ -351,17 +360,17 @@ TEST_F(ModuleTest, TestProgramPersistenceAndReuseAfterModuleDestruction) {

EXPECT_EQ(module.program(), shared_program);

std::array<float, 2> input{1, 2};
std::array<int32_t, 2> sizes{1, 2};
std::array<float, 1> input{1};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), input.data());

auto result = module.execute("forward", Tensor(&tensor));
auto result = module.execute("forward", {Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result.ok());

auto data = result->at(0).toTensor().const_data_ptr<float>();

EXPECT_NEAR(data[0], 1.5, 1e-5);
EXPECT_NEAR(data[0], 2, 1e-5);
}

TEST_F(ModuleTest, TestConcurrentExecutionWithSharedProgram) {
Expand All @@ -379,24 +388,24 @@ TEST_F(ModuleTest, TestConcurrentExecutionWithSharedProgram) {
EXPECT_TRUE(program != nullptr);

auto thread = [](std::shared_ptr<Program> program,
const std::array<float, 2>& input) {
const std::array<float, 1>& input) {
Module module(program);
std::array<int32_t, 2> sizes{1, 2};
std::array<int32_t, 1> sizes{1};
TensorImpl tensor(
ScalarType::Float, sizes.size(), sizes.data(), (void*)input.data());

const auto result = module.forward(Tensor(&tensor));
const auto result = module.forward({Tensor(&tensor), Tensor(&tensor)});
EXPECT_TRUE(result.ok());

const auto data = result->at(0).toTensor().const_data_ptr<float>();
EXPECT_NEAR(data[0], (input[0] + input[1]) / 2.0, 1e-5);
EXPECT_NEAR(data[0], (input[0] * 2), 1e-5);
};

std::thread t1(thread, program, std::array<float, 2>{1, 2});
std::thread t2(thread, program, std::array<float, 2>{2, 3});
std::thread t3(thread, program, std::array<float, 2>{3, 4});
std::thread t4(thread, program, std::array<float, 2>{4, 5});
std::thread t5(thread, program, std::array<float, 2>{5, 6});
std::thread t1(thread, program, std::array<float, 1>{1});
std::thread t2(thread, program, std::array<float, 1>{2});
std::thread t3(thread, program, std::array<float, 1>{3});
std::thread t4(thread, program, std::array<float, 1>{4});
std::thread t5(thread, program, std::array<float, 1>{5});

t1.join();
t2.join();
Expand Down
4 changes: 4 additions & 0 deletions extension/module/test/resources/README.md
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@@ -0,0 +1,4 @@
## Resources

### model.pte
- generated via `buck2 run fbcode//executorch/examples/portable/scripts:export -- --model_name="add"` after D62209852.
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