[NewIR]Fix new ir concat split bug (#55419)

* fix new ir concat op bug

* fix bug

* using add_n_with_kernel instead of add_n impl

* fix pd_op yaml bug

* fix bug

paddle/fluid/ir/dialect/pd_op.yaml

@@ -116,7 +116,42 @@
   - {typename: Tensor, name: out, optional: false, intermediate: false}
   no_need_buffer: null
   data_transform: null
-  invoke: {func: add_n_impl, args: inputs}
+  infer_meta:
+    func: AddNInferMeta
+    param: [inputs]
+  kernel:
+    func: [add_n]
+    param: [inputs]
+    backend: null
+    layout: null
+    data_type: null
+    dispatch: {fetch: null}
+    force_backend: null
+  backward: add_n_grad
+
+- name: add_n_with_kernel
+  inputs:
+  - typename: Tensor[]
+    name: inputs
+    optional: false
+    no_need_buffer: false
+    data_transform: {}
+  attrs: []
+  outputs:
+  - {typename: Tensor, name: out, optional: false, intermediate: false}
+  no_need_buffer: null
+  data_transform: null
+  infer_meta:
+    func: AddNInferMeta
+    param: [inputs]
+  kernel:
+    func: [add_n]
+    param: [inputs]
+    backend: null
+    layout: null
+    data_type: null
+    dispatch: {fetch: null}
+    force_backend: null
   backward: add_n_grad
 
 - name: write_to_array

paddle/fluid/ir/phi_kernel_adaptor/phi_kernel_util.cc

@@ -350,7 +350,6 @@ void BuildScope(const ir::Block& block,
           << paddle::framework::GenScopeTreeDebugInfo(
                  const_cast<paddle::framework::Scope*>(inner_scope->root()));
 
-  // int count = value_2_var_name->size();
   for (auto it = block.begin(); it != block.end(); ++it) {
     ir::Operation* op = *it;
 

paddle/fluid/ir/transforms/pd_op_to_kernel_pass.cc

@@ -65,7 +65,6 @@ phi::KernelKey GetKernelKey(
   phi::Backend kernel_backend = phi::Backend::UNDEFINED;
   phi::DataLayout kernel_layout = phi::DataLayout::UNDEFINED;
   phi::DataType kernel_data_type = phi::DataType::UNDEFINED;
-
   if (op_info_parser != nullptr) {
     // only suppurt non vector input for now
     int tensor_input_number = op_info_parser->InputTensorNumber();
@@ -84,12 +83,36 @@ 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();
+
+        if (type.isa<paddle::dialect::AllocatedDenseTensorType>()) {
+          kernel_data_type = TransToPhiDataType(
+              type.dyn_cast<paddle::dialect::AllocatedDenseTensorType>()
+                  .dtype());
+        } else if (type.isa<ir::VectorType>()) {
+          auto vec_data = type.dyn_cast<ir::VectorType>().data();
+          if (vec_data.size() == 0) {
+            kernel_data_type = phi::DataType::UNDEFINED;
+          } else {
+            if (vec_data[0].isa<paddle::dialect::AllocatedDenseTensorType>()) {
+              kernel_data_type = TransToPhiDataType(
+                  vec_data[0]
+                      .dyn_cast<paddle::dialect::AllocatedDenseTensorType>()
+                      .dtype());
+            } else {
+              PADDLE_THROW(phi::errors::Unimplemented(
+                  "Only support DenseTensorType in vector"));
+            }
+          }
+        } else if (type.isa<paddle::dialect::AllocatedSelectedRowsType>()) {
+          kernel_data_type = TransToPhiDataType(
+              type.dyn_cast<paddle::dialect::AllocatedSelectedRowsType>()
+                  .dtype());
+        } else {
+          PADDLE_THROW(phi::errors::Unimplemented(
+              "Only support DenseTensorType, SelectedRows, VectorType"));
+        }
 
-        dialect::DenseTensorType type =
-            op->operand(in_index)
-                .type()
-                .dyn_cast<paddle::dialect::DenseTensorType>();
-        kernel_data_type = TransToPhiDataType(type.dtype());
       } else {
         PADDLE_ENFORCE_EQ(attr_map.count(slot_name),
                           true,
@@ -146,7 +169,6 @@ phi::KernelKey GetKernelKey(
       if (op_info_parser != nullptr && op_info_parser->IsTensorAttribute(i)) {
         continue;
       }
-
       auto input_tmp = op->operand(i);
       // NOTE: if not input_tmp, it's an optional input
       if (!input_tmp) {

paddle/fluid/ir_adaptor/translator/op_translator.cc

@@ -977,7 +977,8 @@ struct SplitOpTranscriber : public OpTranscriber {
     // process sections
     int num = paddle::get<int>(op_desc.GetAttr("num"));
     if (num <= 0) {
-      if (op_desc.HasInput("SectionsTensorList")) {
+      if (op_desc.HasInput("SectionsTensorList") &&
+          op_desc.Input("SectionsTensorList").size() > 0) {
         // get SectionsTensorList from input
 
         auto sec_tensor_list = op_desc.Input("SectionsTensorList");
@@ -989,7 +990,7 @@ struct SplitOpTranscriber : public OpTranscriber {
         ir::Attribute new_attr = attribute_translator(
             "paddle::dialect::IntArrayAttribute", op_desc.GetAttr("sections"));
         auto sec_defin_op =
-            InsertFullOperationForAttributeInput(ctx, program, new_attr);
+            InsertFullArrayOperationForAttributeInput(ctx, program, new_attr);
         op_inputs.push_back(sec_defin_op->result(0));
       }
     }
@@ -1087,6 +1088,26 @@ struct FetchOpTranscriber : public OpTranscriber {
   }
 };
 
+// NOTE, add_n op in legacy ops don't have a kernel, so we use a new op for now
+struct AddNOpTranscriber : public OpTranscriber {
+  ir::OpInfo LoopkUpOpInfo(ir::IrContext* ctx, const OpDesc& op_desc) override {
+    std::string target_op_name =
+        kTargetDialectPrefix + OpNameCompatibleMapping(op_desc.Type());
+    if (IsInplace(op_desc)) {
+      target_op_name += "_";
+    } else {
+      target_op_name += "_with_kernel";
+    }
+    const auto& op_info = ctx->GetRegisteredOpInfo(target_op_name);
+    if (!op_info) {
+      IR_THROW(
+          "Op assign_value should have corresponding OpInfo pd.assign_value_");
+    }
+
+    return op_info;
+  }
+};
+
 OpTranslator::OpTranslator() {
   general_handler = OpTranscriber();
   special_handlers["feed"] = FeedOpTranscriber();
@@ -1098,6 +1119,7 @@ OpTranslator::OpTranslator() {
   special_handlers["assign_value"] = AssignValueOpTranscriber();
   special_handlers["increment"] = IncrementOpTranscriber();
   special_handlers["rnn"] = RnnOpTranscriber();
+  special_handlers["add_n"] = AddNOpTranscriber();
 }
 
 }  // namespace translator

paddle/phi/api/yaml/op_compat.yaml

@@ -2534,6 +2534,15 @@
     out : Out
   extra :
     attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
+  int_array :
+    starts :
+      data_type : int
+      tensor_name : StartsTensor
+      tensors_name : StartsTensorList
+    ends :
+      data_type : int
+      tensor_name : EndsTensor
+      tensors_name : EndsTensorList
 
 - op : slogdet(slogdeterminant)
   backward : slogdet_grad(slogdeterminant_grad)

paddle/phi/kernels/cpu/fetch_kernel.cc

@@ -24,6 +24,7 @@ void FetchKernel(const Context& dev_ctx,
                  const DenseTensor& x,
                  DenseTensor* out) {
   phi::Copy(dev_ctx, x, phi::CPUPlace(), true, out);
+  out->set_lod(x.lod());
 }
 }  // namespace phi
 PD_REGISTER_KERNEL(fetch,

python/paddle/fluid/executor.py

@@ -855,11 +855,18 @@ class _ExecutorCache:
             if build_strategy is None or build_strategy.enable_inplace
             else False
         )
+
         enable_addto = (
             True
             if build_strategy is not None and build_strategy.enable_addto
             else False
         )
+
+        if os.getenv("FLAGS_enable_new_ir_in_executor"):
+            # todo(phlrain), skip inplace add addto pass in new IR
+            enable_inplace = False
+            enable_addto = False
+
         if enable_inplace or enable_addto:
             # inplace should skip feed and fetch var
             skip_var_names = eval(_get_program_cache_key(feed, fetch_list))

test/legacy_test/eager_op_test.py

@@ -2309,6 +2309,8 @@ class OpTest(unittest.TestCase):
                 self.op_type
                 not in compile_vs_runtime_white_list.COMPILE_RUN_OP_WHITE_LIST
             ):
+                if os.getenv("FLAGS_enable_new_ir_in_executor"):
+                    return
                 self.check_compile_vs_runtime(fetch_list, outs)
 
     def check_output_customized(self, checker, custom_place=None):