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fix: Update floor division schema replacement in lowering #1464

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Merged
merged 1 commit into from
Nov 21, 2022
Merged

fix: Update floor division schema replacement in lowering #1464

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7 changes: 7 additions & 0 deletions core/lowering/passes/remove_unnecessary_casts.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -131,6 +131,13 @@ void RemoveSingleUse0DTensors(std::shared_ptr<torch::jit::Graph>& g) {
user->outputs()[0]->replaceAllUsesWith(new_node->outputs()[0]);
user->destroy();
break;
case c10::aten::floor_divide:
new_node = g->create(c10::aten::floordiv, user->inputs(), 1);
new_node->insertAfter(user);
new_node->outputs()[0]->setType(c10::IntType::get());
user->outputs()[0]->replaceAllUsesWith(new_node->outputs()[0]);
user->destroy();
break;
default:
new_node = g->create(user->kind(), user->inputs(), 1);
new_node->insertAfter(user);
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133 changes: 133 additions & 0 deletions tests/core/lowering/test_remove_unnecessary_casts.cpp
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Expand Up @@ -153,3 +153,136 @@ TEST(LoweringPasses, RemoveSingleUse0DTensorsFloatCorrectly) {

ASSERT_TRUE(!torch::jit::findPatternMatches(*tg, *sg).empty());
}

TEST(LoweringPasses, RemoveSingleUse0DTensorsFloorDivIntCorrectly) {
std::string source_graph = R"IR(
graph(%0: int):
%1: Tensor = prim::Constant[value=[7]]()
%3: Tensor = prim::NumToTensor(%0)
%4: Tensor = aten::floor_divide(%1, %3)
%5: int = aten::Int(%4)
return (%5))IR";
std::string target_graph = R"IR(
graph(%0: int):
%1: int = prim::Constant[value=7]()
%4: int = aten::floordiv(%1, %0)
return (%4))IR";

torch_tensorrt::core::util::logging::get_logger().set_reportable_log_level(
torch_tensorrt::core::util::logging::LogLevel::kGRAPH);
auto sg = std::make_shared<torch::jit::Graph>();
torch::jit::parseIR(source_graph, sg.get());

auto first_op = *(sg->block()->nodes().begin());
torch::jit::WithInsertPoint guard(first_op);
torch::jit::Value* r = sg->insertConstant(c10::scalar_to_tensor(7), c10::nullopt, first_op->scope());
r->copyMetadata(first_op->output());
r->setType(c10::TensorType::get());
first_op->output()->replaceAllUsesWith(r);
first_op->destroy();

torch_tensorrt::core::lowering::passes::RemoveSingleUse0DTensors(sg);

auto tg = std::make_shared<torch::jit::Graph>();
torch::jit::parseIR(target_graph, tg.get());

ASSERT_TRUE(!torch::jit::findPatternMatches(*tg, *sg).empty());
}

TEST(LoweringPasses, RemoveSingleUse0DTensorsFloorDivFloatCorrectly) {
std::string source_graph = R"IR(
graph(%0: float):
%1: Tensor = prim::Constant[value=[8.]]()
%3: Tensor = prim::NumToTensor(%0)
%4: Tensor = aten::floor_divide(%1, %3)
%5: float = aten::Float(%4)
return (%5))IR";
std::string target_graph = R"IR(
graph(%0: float):
%1: float = prim::Constant[value=8.]()
%4: float = aten::floordiv(%1, %0)
return (%4))IR";

torch_tensorrt::core::util::logging::get_logger().set_reportable_log_level(
torch_tensorrt::core::util::logging::LogLevel::kGRAPH);
auto sg = std::make_shared<torch::jit::Graph>();
torch::jit::parseIR(source_graph, sg.get());

auto first_op = *(sg->block()->nodes().begin());
torch::jit::WithInsertPoint guard(first_op);
torch::jit::Value* r = sg->insertConstant(c10::scalar_to_tensor(8.0), c10::nullopt, first_op->scope());
r->copyMetadata(first_op->output());
r->setType(c10::TensorType::get());
first_op->output()->replaceAllUsesWith(r);
first_op->destroy();

torch_tensorrt::core::lowering::passes::RemoveSingleUse0DTensors(sg);

auto tg = std::make_shared<torch::jit::Graph>();
torch::jit::parseIR(target_graph, tg.get());

ASSERT_TRUE(!torch::jit::findPatternMatches(*tg, *sg).empty());
}

TEST(LoweringPasses, RemoveSingleUse0DTensorsFloorDivIntValuesAgree) {
std::string source_graph_no_inputs = R"IR(
graph():
%0: int = prim::Constant[value=2]()
%11: int = prim::Constant[value=7]()
%3: Tensor = prim::NumToTensor(%0)
%1: Tensor = prim::NumToTensor(%11)
%4: Tensor = aten::floor_divide(%1, %3)
%50: int = aten::Int(%4)
%5: Tensor = prim::NumToTensor(%50)
return (%5))IR";
std::string target_graph_no_inputs = R"IR(
graph():
%0: int = prim::Constant[value=2]()
%1: int = prim::Constant[value=7]()
%40: int = aten::floordiv(%1, %0)
%4: Tensor = prim::NumToTensor(%40)
return (%4))IR";

auto g_in = std::make_shared<torch::jit::Graph>();
auto g_out = std::make_shared<torch::jit::Graph>();

torch::jit::parseIR(source_graph_no_inputs, g_in.get());
torch::jit::parseIR(target_graph_no_inputs, g_out.get());

auto jit_pre_results = torch_tensorrt::tests::util::EvaluateGraphJIT(g_in, {});
auto jit_post_results = torch_tensorrt::tests::util::EvaluateGraphJIT(g_out, {});

ASSERT_TRUE(torch_tensorrt::tests::util::exactlyEqual(jit_pre_results[0].toTensor(), jit_post_results[0].toTensor()));
}

TEST(LoweringPasses, RemoveSingleUse0DTensorsFloorDivFloatValuesAgree) {
std::string source_graph_no_inputs = R"IR(
graph():
%0: float = prim::Constant[value=2.]()
%11: float = prim::Constant[value=7.]()
%3: Tensor = prim::NumToTensor(%0)
%1: Tensor = prim::NumToTensor(%11)
%4: Tensor = aten::floor_divide(%1, %3)
%50: float = aten::Float(%4)
%5: Tensor = prim::NumToTensor(%50)
return (%5))IR";
std::string target_graph_no_inputs = R"IR(
graph():
%0: float = prim::Constant[value=2.]()
%1: float = prim::Constant[value=7.]()
%40: float = aten::floordiv(%1, %0)
%4: Tensor = prim::NumToTensor(%40)
return (%4))IR";

auto g_in = std::make_shared<torch::jit::Graph>();
auto g_out = std::make_shared<torch::jit::Graph>();

torch::jit::parseIR(source_graph_no_inputs, g_in.get());
torch::jit::parseIR(target_graph_no_inputs, g_out.get());

auto jit_pre_results = torch_tensorrt::tests::util::EvaluateGraphJIT(g_in, {});
auto jit_post_results = torch_tensorrt::tests::util::EvaluateGraphJIT(g_out, {});

ASSERT_TRUE(
torch_tensorrt::tests::util::almostEqual(jit_pre_results[0].toTensor(), jit_post_results[0].toTensor(), 2e-6));
}