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[NewIR]Support Instruction.Run in CINN for Runtime::Program #55680

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Jul 25, 2023
Merged

[NewIR]Support Instruction.Run in CINN for Runtime::Program #55680

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53 changes: 38 additions & 15 deletions paddle/cinn/hlir/framework/new_ir_compiler.h
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@
// limitations under the License.

#pragma once
#include <absl/types/variant.h>
#include <memory>
#include <unordered_map>
#include "paddle/cinn/common/context.h"
Expand All @@ -30,9 +31,15 @@ namespace cinn {
namespace hlir {
namespace framework {

// TODO(Aurelius): Need add name mapping logic in REGISTER_CINN_OP
// macros or attempt to unify Op name with Paddle and CINN.
static const std::unordered_map<std::string, std::string> OP_NAMES = {
struct CompatibleInfo {
static constexpr char* kInputPrefix = "input_";
static constexpr char* kOutputPrefix = "output_";
// TODO(Aurelius): Need add name mapping logic in REGISTER_CINN_OP
// macros or attempt to unify Op name with Paddle and CINN.
static const std::unordered_map<std::string, std::string> OP_NAMES;
};

const std::unordered_map<std::string, std::string> CompatibleInfo::OP_NAMES = {
{"pd.full", "fill_constant"}, {"pd.matmul", "matmul"}};

// TODO(Aurelius84): Need abstract this logic to implement Proxy for
Expand Down Expand Up @@ -70,18 +77,32 @@ class NewIRCompiler final {
compiler_->Build(build_module, "");

auto instructions = BuildInstructions(groups);

// TODO(Aurelius84): Instantiate all tensors on compile-time, which is
// controlled by 'options.with_instantiate_variables' in GraphCompiler.
// Moreover, it's better to implement InsertBufferHandlers() logic
// to automatically insert Malloc and Free instructions.
for (auto& name : scope_->var_names()) {
std::string var_name({name.data(), name.size()});
VLOG(4) << "Instantiate " << var_name << " on compile-time";
auto* var = scope_->Var<Tensor>(var_name);
auto& tensor = absl::get<Tensor>(*var);
tensor->mutable_data(target_, tensor->type());
}
return std::make_unique<Program>(scope_, std::move(instructions));
}

std::vector<ir::LoweredFunc> GetOpFunc(const ::ir::Operation& op, int idx) {
std::vector<ir::Tensor> inputs;
std::vector<common::CINNValue> cinn_inputs;
VLOG(4) << "GetOpFunc for op: " << op.name();
auto op_name = op.name();
VLOG(4) << "GetOpFunc for op: " << op_name;
// step 1: Deal with Oprands
for (int i = 0; i < op.num_operands(); ++i) {
auto in_value = op.operand(i);
// TODO(Aurelius84): For now, use addr as name but it's not wise.
std::string input_id = std::to_string(std::hash<::ir::Value>()(in_value));
std::string input_id = CompatibleInfo::kInputPrefix +
std::to_string(std::hash<::ir::Value>()(in_value));
// NOTE(Aurelius84): whether need to support other Type?
auto type_info =
in_value.type().dyn_cast<paddle::dialect::DenseTensorType>();
Expand All @@ -100,8 +121,7 @@ class NewIRCompiler final {
cinn_inputs.push_back(common::CINNValue(temp));
}
for (auto out_name : OpGetOutputNames(op)) {
cinn_inputs.push_back(
common::CINNValue(op.name().substr(3) + "_" + out_name));
cinn_inputs.push_back(common::CINNValue(out_name));
}

VLOG(4) << "inputs.size(): " << inputs.size();
Expand All @@ -124,14 +144,14 @@ class NewIRCompiler final {
{
VLOG(4) << "op.attributes():" << op.attributes().size();
auto attrs = utils::ConvertAttributes(op.attributes());
node_attrs.node_name = OP_NAMES.at(op.name());
node_attrs.node_name = CompatibleInfo::OP_NAMES.at(op_name);
node_attrs.attr_store = std::move(attrs);
}
auto& strategy = Operator::GetAttrs<StrategyFunction>("CINNStrategy");
// NOTE(Aurelius84): Do we need replace all hlir::framework Operator with
// ::ir::Program ？
const hlir::framework::Operator* cinn_op =
Operator::Get(OP_NAMES.at(op.name()));
Operator::Get(CompatibleInfo::OP_NAMES.at(op_name));
auto impl = OpStrategy::SelectImpl(
strategy[cinn_op](node_attrs, inputs, out_types, out_shapes, target_));
common::CINNValuePack C =
Expand Down Expand Up @@ -223,7 +243,8 @@ class NewIRCompiler final {
std::unordered_set<std::string> repeat;
for (int i = 0; i < op.num_operands(); ++i) {
auto value = op.operand(i);
std::string name = std::to_string(std::hash<::ir::Value>()(value));
std::string name = CompatibleInfo::kInputPrefix +
std::to_string(std::hash<::ir::Value>()(value));
if (repeat.count(name)) {
continue;
}
Expand All @@ -237,7 +258,8 @@ class NewIRCompiler final {
std::vector<std::string> names;
for (int i = 0; i < op.num_results(); ++i) {
auto value = op.result(i);
std::string name = std::to_string(std::hash<::ir::Value>()(value));
std::string name = CompatibleInfo::kOutputPrefix +
std::to_string(std::hash<::ir::Value>()(value));
names.push_back(std::move(name));
}
return names;
Expand All @@ -257,11 +279,12 @@ std::shared_ptr<Scope> BuildScope(const Target& target,
std::unordered_set<::ir::Value> visited;
auto scope = std::make_shared<Scope>();

auto create_var = [&](::ir::Value value) {
auto create_var = [&](const std::string& name_prefix, ::ir::Value value) {
if (visited.count(value) > 0) return;
visited.emplace(value);

std::string name = std::to_string(std::hash<::ir::Value>()(value));
std::string name =
name_prefix + std::to_string(std::hash<::ir::Value>()(value));
auto type_info = value.type().dyn_cast<paddle::dialect::DenseTensorType>();
auto* var = scope->Var<Tensor>(name);
auto& tensor = absl::get<Tensor>(*var);
Expand All @@ -279,12 +302,12 @@ std::shared_ptr<Scope> BuildScope(const Target& target,
// visit OpOprands
for (auto i = 0; i < (*it)->num_operands(); ++i) {
auto in_value = (*it)->operand(i);
create_var(in_value);
create_var(CompatibleInfo::kInputPrefix, in_value);
}

for (auto i = 0; i < (*it)->num_results(); ++i) {
auto out_value = (*it)->result(i);
create_var(out_value);
create_var(CompatibleInfo::kOutputPrefix, out_value);
}
}
return scope;
Expand Down
20 changes: 15 additions & 5 deletions test/cpp/ir/cinn/graph_compiler_new_ir_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -24,6 +24,7 @@
#include "paddle/cinn/frontend/net_builder.h"
#include "paddle/cinn/frontend/optimize.h"
#include "paddle/cinn/hlir/framework/graph_compiler.h"
#include "paddle/cinn/utils/data_util.h"

#include "paddle/cinn/hlir/framework/new_ir_compiler.h"

Expand All @@ -33,15 +34,16 @@ TEST(GraphCompier, TestNewIR) {
::ir::Program program(ctx);
::ir::Builder builder = ::ir::Builder(ctx, program.block());

const float value = 2.0;
auto full_op_x =
builder.Build<paddle::dialect::FullOp>(std::vector<int64_t>{64, 128},
1.0,
value,
phi::DataType::FLOAT32,
phi::CPUPlace());

auto full_op_y =
builder.Build<paddle::dialect::FullOp>(std::vector<int64_t>{128, 64},
2.0,
value,
phi::DataType::FLOAT32,
phi::CPUPlace());
// TODO(Aurelius84): test more op
Expand All @@ -61,7 +63,15 @@ TEST(GraphCompier, TestNewIR) {
cinn::hlir::framework::NewIRCompiler ir_compiler(program, target, scope);
auto runtime_program = ir_compiler.Build();

// FIXME(Aurelius84): It raised illegal memory access while deconstructor
// after running all instruction, but it's ok under GLOG_v=10.
// ASSERT_NO_THROW(runtime_program->Execute());
ASSERT_NO_THROW(runtime_program->Execute());

for (auto& var_name : scope->var_names()) {
std::string name = {var_name.begin(), var_name.end()};
std::vector<float> data =
cinn::GetTensorData<float>(scope->GetTensor(name), target);
for (int i = 0; i < data.size(); ++i) {
LOG_FIRST_N(INFO, 3) << "data: " << data[i];
ASSERT_NEAR(data[i], value, 1e-5);
}
}
}