【new ir】add ir pybind api (#55745)

* add ir core

* add test

* modify name

* merge

* add test for __eq__

* shield  test for __eq__

* --amend

* Update new_ir_compiler.cc

paddle/cinn/hlir/framework/new_ir_compiler.cc

@@ -79,7 +79,7 @@ std::vector<ir::LoweredFunc> NewIRCompiler::GetOpFunc(const ::ir::Operation& op,
   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);
+    auto in_value = op.operand_source(i);
     // TODO(Aurelius84): For now, use addr as name but it's not wise.
     std::string input_id = CompatibleInfo::kInputPrefix +
                            std::to_string(std::hash<::ir::Value>()(in_value));
@@ -215,7 +215,7 @@ std::vector<std::string> NewIRCompiler::OpGetInputNames(
   std::vector<std::string> names;
   std::unordered_set<std::string> repeat;
   for (int i = 0; i < op.num_operands(); ++i) {
-    auto value = op.operand(i);
+    auto value = op.operand_source(i);
     std::string name = CompatibleInfo::kInputPrefix +
                        std::to_string(std::hash<::ir::Value>()(value));
     if (repeat.count(name)) {
@@ -264,7 +264,7 @@ std::shared_ptr<Scope> BuildScope(const Target& target,
 
   for (auto it = program.block()->begin(); it != program.block()->end(); ++it) {
     for (auto i = 0; i < (*it)->num_operands(); ++i) {
-      auto in_value = (*it)->operand(i);
+      auto in_value = (*it)->operand_source(i);
       create_var(CompatibleInfo::kInputPrefix, in_value);
     }
 

paddle/fluid/framework/new_executor/instruction/phi_kernel_instruction.cc

@@ -266,7 +266,7 @@ PhiKernelInstruction::PhiKernelInstruction(
   auto& no_need_buffer_ids = yaml_info_parser.NoNeedBufferIds();
   std::unordered_set<::ir::Value> no_need_buffer_values;
   for (size_t id = 0; id < no_need_buffer_ids.size(); id++) {
-    no_need_buffer_values.insert(op->operand(no_need_buffer_ids[id]));
+    no_need_buffer_values.insert(op->operand_source(no_need_buffer_ids[id]));
   }
   SetNoNeedBuffer(no_need_buffer_values);
   VLOG(6) << "finish process no need buffer";
@@ -302,7 +302,7 @@ void PhiKernelInstruction::InitInputsOutputsIds(
         variable_2_var_name) {
   std::unordered_map<ir::Value, std::vector<int>> inputs;
   for (size_t i = 0; i < op->num_operands(); i++) {
-    ir::Value value = op->operand(i);
+    ir::Value value = op->operand_source(i);
     if (value) {
       PADDLE_ENFORCE_NE(
           value_2_var_name.find(value),

paddle/fluid/ir/dialect/op_generator/op_member_func_gen.py

@@ -14,7 +14,7 @@
 
 # generator op member function
 
-OP_GET_INPUT_TEMPLATE = """  ir::Value {input_name}() {{ return operand({input_index}); }}
+OP_GET_INPUT_TEMPLATE = """  ir::Value {input_name}() {{ return operand_source({input_index}); }}
 """
 OP_GET_OUTPUT_TEMPLATE = """  ir::OpResult {output_name}() {{ return result({output_index}); }}
 """

paddle/fluid/ir/dialect/op_generator/op_verify_gen.py

@@ -40,26 +40,26 @@ void {op_name}::Verify() {{}}
 """
 
 INPUT_TYPE_CHECK_TEMPLATE = """
-  PADDLE_ENFORCE((*this)->operand({index}).type().isa<{standard}>(),
+  PADDLE_ENFORCE((*this)->operand_source({index}).type().isa<{standard}>(),
                   phi::errors::PreconditionNotMet("Type validation failed for the {index}th input."));"""
 INPUT_VECTORTYPE_CHECK_TEMPLATE = """
-  if (auto vec_type = (*this)->operand({index}).type().dyn_cast<ir::VectorType>()) {{
+  if (auto vec_type = (*this)->operand_source({index}).type().dyn_cast<ir::VectorType>()) {{
       for (size_t i = 0; i < vec_type.size(); ++i) {{
         PADDLE_ENFORCE(vec_type[i].isa<{standard}>(),
                        phi::errors::PreconditionNotMet("Type validation failed for the {index}th input."));
       }}
   }}
   else {{
-    PADDLE_ENFORCE((*this)->operand({index}).type().isa<{standard}>(),
+    PADDLE_ENFORCE((*this)->operand_source({index}).type().isa<{standard}>(),
                    phi::errors::PreconditionNotMet("Type validation failed for the {index}th input."));
   }}"""
 INPUT_OPTIONAL_TYPE_CHECK_TEMPLATE = """
-  if (auto val = (*this)->op_operand({index})) {{
+  if (auto val = (*this)->operand({index})) {{
     PADDLE_ENFORCE(val.type().isa<{standard}>(),
                    phi::errors::PreconditionNotMet("Type validation failed for the {index}th input."));
   }}"""
 INPUT_OPTIONAL_VECTORTYPE_CHECK_TEMPLATE = """
-  if (auto val =  (*this)->op_operand({index})) {{
+  if (auto val =  (*this)->operand({index})) {{
     if (auto vec_type = val.type().dyn_cast<ir::VectorType>()) {{
       for (size_t i = 0; i < vec_type.size(); i++) {{
         PADDLE_ENFORCE(vec_type[i].isa<{standard}>(),

paddle/fluid/ir/phi_kernel_adaptor/phi_kernel_util.cc

@@ -140,7 +140,7 @@ void CheckInputVars(
   size_t input_num = op->num_operands();
   if (input_num > 0) {
     for (size_t i = 0; i < input_num; ++i) {
-      auto value = op->operand(i);
+      auto value = op->operand_source(i);
       if (value) {
         PADDLE_ENFORCE_NE(
             value_2_var_name.find(value),
@@ -298,7 +298,7 @@ void HandleForSpecialOp(
     tensor_array->clear();
     size_t input_num = op->num_operands();
     for (size_t i = 0; i < input_num; ++i) {
-      auto value = op->operand(i);
+      auto value = op->operand_source(i);
       PADDLE_ENFORCE_EQ(
           value_2_var_name->count(value),
           true,
@@ -315,7 +315,7 @@ void HandleForSpecialOp(
                           .dyn_cast<ir::StrAttribute>()
                           .AsString();
 
-    auto value = op->operand(0);
+    auto value = op->operand_source(0);
     // change opreand name to param_name
     auto orig_name = value_2_var_name->at(value);
 
@@ -336,7 +336,7 @@ void HandleForSpecialOp(
     auto var_name =
         op->attributes().at("name").dyn_cast<ir::StrAttribute>().AsString();
 
-    auto value = op->operand(0);
+    auto value = op->operand_source(0);
     // change opreand name to param_name
     auto orig_name = value_2_var_name->at(value);
 
@@ -372,7 +372,7 @@ void HandleForSpecialOp(
   if (op_name == "builtin.slice") {
     VLOG(6) << "Handle for builtin.slice";
     auto out_value = op->result(0);
-    auto in_value = op->operand(0);
+    auto in_value = op->operand_source(0);
     PADDLE_ENFORCE_EQ(value_2_var_name->count(in_value),
                       true,
                       phi::errors::PreconditionNotMet(
@@ -426,7 +426,7 @@ void HandleForInplaceOp(
     if (yaml_parser.HasInplace(value_name)) {
       std::string inplace_name = yaml_parser.InplaceName(value_name);
       ir::Value inplace_value =
-          op->operand(yaml_parser.InputName2Id().at(inplace_name));
+          op->operand_source(yaml_parser.InputName2Id().at(inplace_name));
       std::string var_name = value_2_var_name->at(inplace_value);
       VLOG(4) << "inplace: " << value_name << " -> " << inplace_name
               << " (var: " << var_name << ")";
@@ -547,7 +547,7 @@ void BuildRuntimeContext(
         true,
         phi::errors::NotFound("param [%s] MUST in name2id map", name));
     auto index = op_yaml_info.InputName2Id().at(name);
-    ir::Value ptr = op->operand(index);
+    ir::Value ptr = op->operand_source(index);
 
     auto in_var_name = name_map.at(ptr);
     VLOG(6) << "ctx->EmplaceBackInput: " << name << "\t" << in_var_name;
@@ -603,7 +603,7 @@ std::shared_ptr<paddle::framework::OperatorBase> BuildOperatorBase(
         true,
         phi::errors::NotFound("param [%s] MUST in name2id map", name));
     auto index = op_yaml_info.InputName2Id().at(name);
-    ir::Value ptr = op->operand(index);
+    ir::Value ptr = op->operand_source(index);
 
     auto in_var_name = name_map.at(ptr);
 

paddle/fluid/ir/phi_kernel_adaptor/phi_kernel_util.h

@@ -92,7 +92,7 @@ void BuildPhiContext(ir::Operation* op,
         true,
         phi::errors::NotFound("param [%s] MUST in name2id map", t));
     auto index = op_yaml_info.InputName2Id().at(t);
-    ir::Value ptr = op->operand(index);
+    ir::Value ptr = op->operand_source(index);
     if (!ptr) {
       phi::DenseTensor* ptr = nullptr;
       OutType in_ptr(ptr);
@@ -128,7 +128,7 @@ void BuildPhiContext(ir::Operation* op,
   for (auto& t : vec_kernel_fn_attr_params) {
     if (name2id.count(t)) {
       // tensor attribute, get information from input
-      ir::Value ptr = op->operand(name2id.at(t));
+      ir::Value ptr = op->operand_source(name2id.at(t));
 
       auto in_var_name = name_map.at(ptr);
 

paddle/fluid/ir/transforms/constant_folding_pass.cc

@@ -114,12 +114,13 @@ class ConstantFoldingPattern : public ir::RewritePattern {
     std::vector<ir::OpResult> op_inputs;
     for (uint32_t i = 0; i < op->num_operands(); i++) {
       PADDLE_ENFORCE_EQ(
-          op->operand(i).type().isa<paddle::dialect::DenseTensorType>(),
+          op->operand_source(i).type().isa<paddle::dialect::DenseTensorType>(),
           true,
           phi::errors::InvalidArgument(
               "Op's input must be a dense tensor type."));
 
-      auto [param_name, param] = ir::GetParameterFromValue(op->operand(i));
+      auto [param_name, param] =
+          ir::GetParameterFromValue(op->operand_source(i));
       program->SetParameter(param_name,
                             std::make_unique<ir::Parameter>(*param));
 
@@ -128,8 +129,8 @@ class ConstantFoldingPattern : public ir::RewritePattern {
           param_var,
           phi::errors::InvalidArgument("Parameter var not in scope."));
 
-      auto get_parameter_op =
-          builder.Build<ir::GetParameterOp>(param_name, op->operand(i).type());
+      auto get_parameter_op = builder.Build<ir::GetParameterOp>(
+          param_name, op->operand_source(i).type());
       op_inputs.push_back(get_parameter_op->result(0));
     }
 

paddle/fluid/ir/transforms/pd_op_to_kernel_pass.cc

@@ -97,7 +97,7 @@ phi::KernelKey GetKernelKey(
       } else if (input_map.count(slot_name)) {
         // parse from input
         int in_index = input_map.at(slot_name);
-        auto type = map_value_pair.at(op->operand(in_index)).type();
+        auto type = map_value_pair.at(op->operand_source(in_index)).type();
 
         if (type.isa<paddle::dialect::AllocatedDenseTensorType>()) {
           kernel_data_type = TransToPhiDataType(
@@ -151,7 +151,7 @@ phi::KernelKey GetKernelKey(
       if (op->name() == "pd.uniform") {
         // try to process uniform, use shape to determin backend
         // TODO(phlrain): shuold support other initilize op
-        auto define_op = op->operand(0).GetDefiningOp();
+        auto define_op = op->operand_source(0).GetDefiningOp();
         if (define_op->name() == "pd.full_int_array") {
           auto shape = define_op->attributes()
                            .at("value")
@@ -183,7 +183,7 @@ phi::KernelKey GetKernelKey(
       if (op_info_parser != nullptr && op_info_parser->IsTensorAttribute(i)) {
         continue;
       }
-      auto input_tmp = op->operand(i);
+      auto input_tmp = op->operand_source(i);
       // NOTE: if not input_tmp, it's an optional input
       if (!input_tmp) {
         continue;
@@ -341,7 +341,7 @@ std::unique_ptr<ir::Program> PdOpLowerToKernelPass(ir::Program* prog,
 
     if ((*it)->num_operands() > 0) {
       for (size_t i = 0; i < (*it)->num_operands(); ++i) {
-        auto cur_in = (*it)->operand(i);
+        auto cur_in = (*it)->operand_source(i);
         if (!cur_in) {
           vec_inputs.push_back(ir::OpResult());
           continue;

paddle/fluid/ir/transforms/transform_general_functions.cc

@@ -64,7 +64,7 @@ Operation* GetDefiningOpForInput(Operation* op, uint32_t index) {
       index < op->num_operands(),
       true,
       phi::errors::InvalidArgument("Intput operand's index must be valid."));
-  return op->operand(index).GetDefiningOp();
+  return op->operand_source(index).GetDefiningOp();
 }
 
 Operation* GetFirstUseOperationForOutput(Operation* op, uint32_t index) {

paddle/fluid/pybind/ir.cc

@@ -77,6 +77,8 @@ void BindProgram(py::module *m) {
 void BindBlock(py::module *m) {
   py::class_<Block> block(*m, "Block");
   block.def("front", &Block::front, return_value_policy::reference)
+      .def("get_parent_program",
+           [](Block &self) { return self.GetParentOp()->GetParentProgram(); })
       .def("get_ops",
            [](Block &self) -> py::list {
              py::list op_list;
@@ -94,19 +96,22 @@ void BindBlock(py::module *m) {
 void BindOperation(py::module *m) {
   py::class_<Operation> op(*m, "Operation");
   op.def("name", &Operation::name)
-      .def("get_parent",
+      .def("get_parent_block",
            py::overload_cast<>(&Operation::GetParent),
            return_value_policy::reference)
-      .def("get_parent",
+      .def("get_parent_block",
            py::overload_cast<>(&Operation::GetParent, py::const_),
            return_value_policy::reference)
+      .def("num_operands", &Operation::num_operands)
       .def("num_results", &Operation::num_results)
+      .def("operand", &Operation::operand)
       .def("result", &Operation::result)
+      .def("operand_source", &Operation::operand_source)
       .def("operands",
            [](Operation &self) -> py::list {
              py::list op_list;
              for (uint32_t i = 0; i < self.num_operands(); i++) {
-               op_list.append(self.op_operand(i));
+               op_list.append(self.operand(i));
              }
              return op_list;
            })
@@ -118,6 +123,14 @@ void BindOperation(py::module *m) {
              }
              return op_list;
            })
+      .def("operands_source",
+           [](Operation &self) -> py::list {
+             py::list op_list;
+             for (uint32_t i = 0; i < self.num_operands(); i++) {
+               op_list.append(self.operand_source(i));
+             }
+             return op_list;
+           })
       .def("get_input_names",
            [](Operation &self) -> py::list {
              py::list op_list;
@@ -159,8 +172,11 @@ void BindOperation(py::module *m) {
 
 void BindValue(py::module *m) {
   py::class_<Value> value(*m, "Value");
-  value.def(
-      "get_defining_op", &Value::GetDefiningOp, return_value_policy::reference);
+  value
+      .def("get_defining_op",
+           &Value::GetDefiningOp,
+           return_value_policy::reference)
+      .def("__eq__", &Value::operator==);
 }
 
 void BindOpOperand(py::module *m) {

paddle/ir/core/ir_printer.cc

@@ -239,7 +239,7 @@ void IrPrinter::PrintOpOperands(const Operation* op) {
   std::vector<Value> op_operands;
   op_operands.reserve(num_op_operands);
   for (size_t idx = 0; idx < num_op_operands; idx++) {
-    op_operands.push_back(op->operand(idx));
+    op_operands.push_back(op->operand_source(idx));
   }
   PrintInterleave(
       op_operands.begin(),
@@ -254,7 +254,7 @@ void IrPrinter::PrintOperandsType(const Operation* op) {
   std::vector<Type> op_operand_types;
   op_operand_types.reserve(num_op_operands);
   for (size_t idx = 0; idx < num_op_operands; idx++) {
-    auto op_operand = op->op_operand(idx);
+    auto op_operand = op->operand(idx);
     if (op_operand) {
       op_operand_types.push_back(op_operand.type());
     } else {

paddle/ir/core/op_base.h

@@ -88,7 +88,9 @@ class IR_API OpBase {
 
   const AttributeMap &attributes() const { return operation()->attributes(); }
 
-  Value operand(uint32_t index) const { return operation()->operand(index); }
+  Value operand_source(uint32_t index) const {
+    return operation()->operand_source(index);
+  }
 
   OpResult result(uint32_t index) const { return operation()->result(index); }
 

paddle/ir/core/operation.cc

@@ -40,7 +40,7 @@ Operation *Operation::Create(OperationArgument &&argument) {
 
 // Allocate the required memory based on the size and number of inputs, outputs,
 // and operators, and construct it in the order of: OpOutlineResult,
-// OpInlineResult, Operation, Operand.
+// OpInlineResult, Operation, operand.
 Operation *Operation::Create(const std::vector<ir::OpResult> &inputs,
                              const AttributeMap &attributes,
                              const std::vector<ir::Type> &output_types,
@@ -132,7 +132,7 @@ void Operation::Destroy() {
 
   // 4. Deconstruct OpOperand.
   for (size_t idx = 0; idx < num_operands_; idx++) {
-    op_operand(idx).impl()->~OpOperandImpl();
+    operand(idx).impl()->~OpOperandImpl();
   }
   // 5. Free memory.
   uint32_t max_inline_result_num =
@@ -186,7 +186,7 @@ ir::OpResult Operation::result(uint32_t index) const {
   }
 }
 
-OpOperand Operation::op_operand(uint32_t index) const {
+OpOperand Operation::operand(uint32_t index) const {
   if (index >= num_operands_) {
     IR_THROW("index exceeds OP input range.");
   }
@@ -195,8 +195,8 @@ OpOperand Operation::op_operand(uint32_t index) const {
   return OpOperand(reinterpret_cast<const detail::OpOperandImpl *>(ptr));
 }
 
-Value Operation::operand(uint32_t index) const {
-  OpOperand val = op_operand(index);
+Value Operation::operand_source(uint32_t index) const {
+  OpOperand val = operand(index);
   return val ? val.source() : Value();
 }
 

paddle/ir/core/operation.h

@@ -55,9 +55,9 @@ class IR_API alignas(8) Operation final {
 
   OpResult result(uint32_t index) const;
 
-  OpOperand op_operand(uint32_t index) const;
+  OpOperand operand(uint32_t index) const;
 
-  Value operand(uint32_t index) const;
+  Value operand_source(uint32_t index) const;
 
   /// Returns the region held by this operation at position 'index'.
   Region &region(unsigned index);

paddle/ir/pattern_rewrite/pattern_rewrite_driver.cc

@@ -131,7 +131,7 @@ class GreedyPatternRewriteDriver : public ir::PatternRewriter {
 
   void NotifyOperationRemoved(ir::Operation* op) override {
     for (uint32_t i = 0; i < op->num_operands(); ++i) {
-      AddOperandToWorklist(op->operand(i));
+      AddOperandToWorklist(op->operand_source(i));
     }
     for (uint32_t i = 0; i < op->num_regions(); ++i) {
       auto& region = op->region(i);

test/cpp/ir/core/ir_program_test.cc

@@ -174,9 +174,9 @@ TEST(program_test, program) {
   // (8) Def SetParameterOp(c, "c")
   auto op4 = builder.Build<ir::SetParameterOp>(op3->result(0), "c");
 
-  EXPECT_EQ(op4->op_operand(0).type().dialect().id(), paddle_dialect->id());
+  EXPECT_EQ(op4->operand(0).type().dialect().id(), paddle_dialect->id());
   Interface *c_interface =
-      op4->op_operand(0).type().dialect().GetRegisteredInterface<Interface>();
+      op4->operand(0).type().dialect().GetRegisteredInterface<Interface>();
   //   ir::Parameter *parameter_c =
   //       c_interface->VariableToParameter(variable_c.get());
   std::unique_ptr<ir::Parameter> parameter_c =

test/cpp/ir/core/ir_value_test.cc

@@ -91,10 +91,10 @@ TEST(value_test, value_test) {
 
   // Test 2: op1_first_output -> op4_first_input
   ir::OpResult op1_first_output = op1->result(0);
-  ir::OpOperand op4_first_input = op4->op_operand(0);
+  ir::OpOperand op4_first_input = op4->operand(0);
 
   EXPECT_EQ(op1_first_output.first_use(), op4_first_input);
-  ir::OpOperand op3_first_input = op3->op_operand(0);
+  ir::OpOperand op3_first_input = op3->operand(0);
 
   EXPECT_EQ(op4_first_input.next_use(), op3_first_input);
   EXPECT_EQ(op3_first_input.next_use(), nullptr);
@@ -110,11 +110,11 @@ TEST(value_test, value_test) {
   // a = OP1(); b = OP2(); c = OP3(a, b); d, e, f, g, h, i, j = OP4(a, c);
   //
   c.ReplaceUsesWithIf(b, [](ir::OpOperand) { return true; });
-  EXPECT_EQ(op4->operand(1), b);
+  EXPECT_EQ(op4->operand_source(1), b);
   EXPECT_TRUE(c.use_empty());
 
   b.ReplaceAllUsesWith(a);
-  EXPECT_EQ(op4->operand(1), a);
+  EXPECT_EQ(op4->operand_source(1), a);
   EXPECT_TRUE(b.use_empty());
 
   // destroy

test/cpp/ir/pattern_rewrite/pattern_rewrite_test.cc

@@ -386,10 +386,10 @@ class Conv2dFusionOpTest : public ir::Op<Conv2dFusionOpTest,
                     ir::OpResult residual_,
                     ir::AttributeMap attributes);
   void Verify();
-  ir::Value input() { return operand(0); }
-  ir::Value filter() { return operand(1); }
-  ir::Value bias() { return operand(2); }
-  ir::Value residual() { return operand(3); }
+  ir::Value input() { return operand_source(0); }
+  ir::Value filter() { return operand_source(1); }
+  ir::Value bias() { return operand_source(2); }
+  ir::Value residual() { return operand_source(3); }
   ir::OpResult output() { return result(0); }
   ir::OpResult outputs() { return result(1); }
   ir::Attribute attribute(const std::string &name) {
@@ -752,19 +752,25 @@ void Conv2dFusionOpTest::Verify() {
         4u,
         phi::errors::PreconditionNotMet(
             "The size %d of inputs must be equal to 4.", input_size));
-    PADDLE_ENFORCE(
-        (*this)->operand(0).type().isa<paddle::dialect::DenseTensorType>(),
+    PADDLE_ENFORCE((*this)
+                       ->operand_source(0)
+                       .type()
+                       .isa<paddle::dialect::DenseTensorType>(),
                    phi::errors::PreconditionNotMet(
                        "Type validation failed for the 0th input."));
-    PADDLE_ENFORCE(
-        (*this)->operand(1).type().isa<paddle::dialect::DenseTensorType>(),
+    PADDLE_ENFORCE((*this)
+                       ->operand_source(1)
+                       .type()
+                       .isa<paddle::dialect::DenseTensorType>(),
                    phi::errors::PreconditionNotMet(
                        "Type validation failed for the 1th input."));
-    PADDLE_ENFORCE(
-        (*this)->operand(2).type().isa<paddle::dialect::DenseTensorType>(),
+    PADDLE_ENFORCE((*this)
+                       ->operand_source(2)
+                       .type()
+                       .isa<paddle::dialect::DenseTensorType>(),
                    phi::errors::PreconditionNotMet(
                        "Type validation failed for the 2th input."));
-    if (auto val = (*this)->op_operand(3)) {
+    if (auto val = (*this)->operand(3)) {
       PADDLE_ENFORCE(val.type().isa<paddle::dialect::DenseTensorType>(),
                      phi::errors::PreconditionNotMet(
                          "Type validation failed for the 3th input."));

test/ir/new_ir/test_ir_pybind.py

@@ -30,8 +30,8 @@ def get_ir_program():
         x_s = paddle.static.data('x', [4, 4], x.dtype)
         x_s.stop_gradient = False
         y_s = paddle.matmul(x_s, x_s)
-        y_s = paddle.add(x_s, y_s)
-        y_s = paddle.tanh(y_s)
+        z_s = paddle.add(y_s, y_s)
+        k_s = paddle.tanh(z_s)
     newir_program = ir.translate_to_new_ir(main_program.desc)
     return newir_program
 
@@ -41,6 +41,11 @@ class TestPybind(unittest.TestCase):
         newir_program = get_ir_program()
         print(newir_program)
 
+        block = newir_program.block()
+        program = block.get_parent_program()
+
+        self.assertEqual(newir_program, program)
+
     def test_block(self):
         newir_program = get_ir_program()
         block = newir_program.block()
@@ -57,7 +62,7 @@ class TestPybind(unittest.TestCase):
         matmul_op = newir_program.block().get_ops()[1]
         add_op = newir_program.block().get_ops()[2]
         tanh_op = newir_program.block().get_ops()[3]
-        parent_block = tanh_op.get_parent()
+        parent_block = tanh_op.get_parent_block()
         parent_ops_num = len(parent_block.get_ops())
         self.assertEqual(parent_ops_num, 4)
         self.assertEqual(tanh_op.num_results(), 1)
@@ -79,6 +84,13 @@ class TestPybind(unittest.TestCase):
         matmul_op.result(0).set_stop_gradient(True)
         self.assertEqual(matmul_op.result(0).get_stop_gradient(), True)
 
+        result_set = set()
+        for opresult in matmul_op.results():
+            result_set.add(opresult)
+
+        # self.assertTrue(add_op.operands()[0].source() in result_set)
+        # self.assertEqual(add_op.operands_source()[0] , matmul_op.results()[0],)
+
         self.assertEqual(
             tanh_op.operands()[0].source().get_defining_op().name(), "pd.add"
         )
@@ -87,6 +99,11 @@ class TestPybind(unittest.TestCase):
         self.assertEqual(
             tanh_op.operands()[0].source().get_defining_op().name(), "pd.matmul"
         )
+
+        self.assertEqual(
+            tanh_op.operands()[0].source().get_defining_op(),
+            tanh_op.operands_source()[0].get_defining_op(),
+        )
         self.assertEqual(add_op.result(0).use_empty(), True)
 
     def test_type(self):