[PIR] pir onednn support shape op

paddle/fluid/framework/new_executor/instruction/onednn/onednn_instruction.cc

@@ -361,6 +361,26 @@ OneDNNPhiKernelInstruction::OneDNNPhiKernelInstruction(
   phi::MetaConfig new_config = infer_meta_context_.GetMetaConfig();
   new_config.is_run_mkldnn_kernel = true;
   infer_meta_context_.SetMetaConfig(new_config);
+
+  // Step5: Handle skip_transform_inputs
+  if (op_attributes.count("skip_transform_inputs")) {
+    std::vector<pir::Attribute> skip_transform_inputs =
+        op->attributes()
+            .at("skip_transform_inputs")
+            .dyn_cast<pir::ArrayAttribute>()
+            .AsVector();
+
+    for (auto& input : skip_transform_inputs) {
+      auto input_name = input.dyn_cast<pir::StrAttribute>().AsString();
+      auto pair = kernel_context_.InputRangeAt(
+          yaml_info_parser.InputName2Id().at(input_name));
+      VLOG(6) << "skip_transform_input = " << input_name;
+      for (int i = pair.first; i < pair.second; ++i) {
+        skip_format_tensors_.insert(i);
+        VLOG(6) << input_name << " index = " << i;
+      }
+    }
+  }
 }
 
 OneDNNPhiKernelInstruction::~OneDNNPhiKernelInstruction() {
@@ -381,6 +401,9 @@ void OneDNNPhiKernelInstruction::Run() {
     if (!input->initialized()) {
       continue;
     }
+    if (skip_format_tensors_.count(i)) {
+      continue;
+    }
     VLOG(6) << "input[" << i << "].layout() = " << input->layout();
     if (input->layout() != phi::DataLayout::ONEDNN) {
       phi::DataLayout from_layout = input->layout();

paddle/fluid/framework/new_executor/instruction/onednn/onednn_instruction.h

@@ -69,6 +69,7 @@ class OneDNNPhiKernelInstruction : public InstructionBase {
   const ValueExecutionInfo* value_exec_info_;  // not owned
 
   std::set<int> data_format_tensors_{};
+  std::set<int> skip_format_tensors_{};
   phi::DataLayout input_layout_{phi::DataLayout::kAnyLayout};
   std::map<std::string, phi::Attribute> extra_attr_{};
   std::map<std::string, phi::Attribute> ctx_attr_{};

paddle/fluid/framework/new_executor/instruction/onednn/onednn_legacy_instruction.cc

@@ -217,7 +217,7 @@ OneDNNLegacyKernelInstruction::OneDNNLegacyKernelInstruction(
             .at("data_format_tensors")
             .dyn_cast<pir::ArrayAttribute>()
             .AsVector();
-    std::vector<std::string> layout_transform_inputs;
+
     auto& op_normalizer = paddle::translator::OpNameNormalizer::instance();
     std::string fluid_op_name = yaml_info_parser.GetOriginOpName();
     for (auto& attr : data_format_tensors_attr) {
@@ -231,6 +231,24 @@ OneDNNLegacyKernelInstruction::OneDNNLegacyKernelInstruction(
   phi::MetaConfig new_config = infer_meta_context_.GetMetaConfig();
   new_config.is_run_mkldnn_kernel = true;
   infer_meta_context_.SetMetaConfig(new_config);
+
+  // Step4: Handle skip_transform_inputs
+  if (op_attributes.count("skip_transform_inputs")) {
+    std::vector<pir::Attribute> skip_transform_inputs =
+        op->attributes()
+            .at("skip_transform_inputs")
+            .dyn_cast<pir::ArrayAttribute>()
+            .AsVector();
+
+    auto& op_normalizer = paddle::translator::OpNameNormalizer::instance();
+    std::string fluid_op_name = yaml_info_parser.GetOriginOpName();
+
+    for (auto& input : skip_transform_inputs) {
+      auto input_name = input.dyn_cast<pir::StrAttribute>().AsString();
+      skip_format_tensors_.insert(
+          op_normalizer.GetLegacyArgName(fluid_op_name, input_name));
+    }
+  }
 }
 
 OneDNNLegacyKernelInstruction::~OneDNNLegacyKernelInstruction() {
@@ -247,6 +265,9 @@ void OneDNNLegacyKernelInstruction::Run() {
   // Step1. TransLayout
   auto inputs = kernel_context_->InNameList();
   for (auto& input_name : inputs) {
+    if (skip_format_tensors_.count(*input_name)) {
+      continue;
+    }
     auto input_vars = kernel_context_->MultiInputVar(*input_name);
     for (auto& var : input_vars) {
       if (var->IsType<phi::DenseTensor>()) {

paddle/fluid/framework/new_executor/instruction/onednn/onednn_legacy_instruction.h

@@ -68,6 +68,7 @@ class OneDNNLegacyKernelInstruction : public InstructionBase {
   const ValueExecutionInfo* value_exec_info_;  // not owned
 
   std::set<std::string> data_format_tensors_{};
+  std::set<std::string> skip_format_tensors_{};
   phi::DataLayout input_layout_{phi::DataLayout::kAnyLayout};
 };
 

paddle/fluid/pir/dialect/op_generator/op_gen.py

@@ -273,7 +273,7 @@ class {TEST_API} {op_name} : public pir::Op<{op_name}{interfaces}{traits}> {{
   std::vector<paddle::dialect::OpOutputInfo> outputs = {{ {outputs} }};
   pir::AttributeMap extra_attr_default_value;
   {extra_attr_default_value_code}
-  paddle::dialect::OpRunTimeInfo run_time_info = paddle::dialect::OpRunTimeInfo("{infer_meta_func}", {{"{infer_meta_param}"}}, "{kernel_func}", {{"{kernel_param}"}}, {{{kernel_key_dtype}}}, {{{kernel_key_backend}}}, {{{inplace}}}, {{{view}}}, {{{extra_args}}}, extra_attr_default_value, {{{data_format_tensors}}}, {is_onednn_only}, {dynamic_fallback});
+  paddle::dialect::OpRunTimeInfo run_time_info = paddle::dialect::OpRunTimeInfo("{infer_meta_func}", {{"{infer_meta_param}"}}, "{kernel_func}", {{"{kernel_param}"}}, {{{kernel_key_dtype}}}, {{{kernel_key_backend}}}, {{{inplace}}}, {{{view}}}, {{{extra_args}}}, {{{skip_transform_inputs}}}, extra_attr_default_value, {{{data_format_tensors}}}, {is_onednn_only}, {dynamic_fallback});
   return std::make_tuple(inputs, attributes, outputs, run_time_info, "{origin_op_name}");
 }}
 """
@@ -1788,6 +1788,22 @@ def AutoCodeGen(op_info_items, all_op_info_items, namespaces, dialect_name):
                         )
                     else:
                         extra_attr_default_value_code_str = ""
+                    skip_transform_inputs = ""
+                    if op_info.data_transform_map is not None:
+                        if "skip_transform" in op_info.data_transform_map:
+                            skip_transform = op_info.data_transform_map[
+                                "skip_transform"
+                            ]
+                            if skip_transform is not None:
+                                skip_transform_input_names = []
+                                for input in skip_transform:
+                                    skip_transform_input_names.append(input)
+
+                                skip_transform_inputs = (
+                                    '"'
+                                    + '", "'.join(skip_transform_input_names)
+                                    + '"'
+                                )
 
                     op_info_func_str = OP_INFO_ONEDNN_TEMPLATE.format(
                         op_name=op_class_name,
@@ -1805,6 +1821,7 @@ def AutoCodeGen(op_info_items, all_op_info_items, namespaces, dialect_name):
                         view=view_str,
                         origin_op_name=op_info.op_yaml_item['name'],
                         extra_args=extra_args,
+                        skip_transform_inputs=skip_transform_inputs,
                         data_format_tensors=data_format_tensors,
                         is_onednn_only="true"
                         if op_info.is_onednn_only

paddle/fluid/pir/dialect/operator/ir/ops_onednn_extra.yaml

@@ -224,8 +224,8 @@
 
 # - op : sgd_dense_param_sparse_grad
 
-# - op : shape
-#   extra_args : str mkldnn_data_type="float32"
+- op : shape
+  extra_args : str mkldnn_data_type="float32"
 
 - op : shuffle_channel
 

paddle/fluid/pir/dialect/operator/utils/op_yaml_info_util.h

@@ -95,6 +95,7 @@ struct OpRunTimeInfo {
   std::vector<std::pair<std::string, std::string>> inplace;
   std::vector<std::pair<std::string, std::string>> view;
   std::vector<std::string> extra_args;
+  std::vector<std::string> skip_transform_inputs;
   pir::AttributeMap extra_args_default_value;
   std::vector<std::string> data_format_tensors;
   bool is_onednn_only;
@@ -109,6 +110,7 @@ struct OpRunTimeInfo {
                 const std::vector<std::pair<std::string, std::string>>& inplace,
                 const std::vector<std::pair<std::string, std::string>>& view,
                 const std::vector<std::string>& extra_args = {},
+                const std::vector<std::string>& skip_transform_inputs = {},
                 const pir::AttributeMap& extra_args_default_value = {{}},
                 const std::vector<std::string>& data_format_tensors = {},
                 bool is_onednn_only = false,
@@ -122,6 +124,7 @@ struct OpRunTimeInfo {
         inplace(inplace),
         view(view),
         extra_args(extra_args),
+        skip_transform_inputs(skip_transform_inputs),
         extra_args_default_value(extra_args_default_value),
         data_format_tensors(data_format_tensors),
         is_onednn_only(is_onednn_only),

paddle/fluid/pir/transforms/pd_op_to_kernel_pass.cc

@@ -2327,6 +2327,13 @@ pir::Operation* BuildKernelOp(
     op_attribute.emplace(
         "extra_args",
         pir::ArrayAttribute::get(pir::IrContext::Instance(), extra_args));
+    std::vector<pir::Attribute> skip_transform_inputs;
+    for (auto& arg : op_info_parser->OpRuntimeInfo().skip_transform_inputs) {
+      skip_transform_inputs.push_back(pir::StrAttribute::get(ctx, arg));
+    }
+    op_attribute.emplace("skip_transform_inputs",
+                         pir::ArrayAttribute::get(pir::IrContext::Instance(),
+                                                  skip_transform_inputs));
     std::vector<pir::Attribute> data_format_tensors;
     for (auto& input : op_info_parser->OpRuntimeInfo().data_format_tensors) {
       data_format_tensors.push_back(pir::StrAttribute::get(ctx, input));

test/mkldnn/test_shape_mkldnn_op.py

@@ -35,7 +35,7 @@ def config(self):
         self.dtype = np.float32
 
     def test_check_output(self):
-        self.check_output_with_place(core.CPUPlace())
+        self.check_output_with_place(core.CPUPlace(), check_pir_onednn=True)
 
 
 class TestShape0DFP32OneDNNOp(TestShape3DFP32OneDNNOp):