[CINN] Add rules for cinn_to_pd

paddle/cinn/hlir/dialect/operator/ir/manual_op.cc

@@ -264,7 +264,7 @@ void SplitOp::Build(pir::Builder& builder,             // NOLINT
                     pir::Value input,
                     const std::vector<int>& sections,
                     int axis) {
-  VLOG(4) << "Start build ConcatOp";
+  VLOG(4) << "Start build SplitOp";
 
   argument.inputs.push_back(input);
 

paddle/cinn/hlir/dialect/operator/ir/ops.yaml

@@ -58,21 +58,25 @@
   interfaces : paddle::dialect::InferSymbolicShapeInterface
 
 - op : reduce_prod
-  args : (Tensor x, int64_t[] dim,  bool keep_dim)
+  args : (Tensor x, int64_t[] dim,  bool keep_dim, bool reduce_all)
   output : Tensor(out)
   infer_meta :
     func : ReduceInferMeta
+    param : [x, dim, keep_dim]
   kernel :
     func : frobenius_norm
+    param : [x, dim, keep_dim]
   interfaces : paddle::dialect::InferSymbolicShapeInterface
 
 - op : reduce_sum
-  args : (Tensor x, int64_t[] dim,  bool keep_dim)
+  args : (Tensor x, int64_t[] dim,  bool keep_dim, DataType dtype=DataType::UNDEFINED)
   output : Tensor(out)
   infer_meta :
     func : ReduceInferMeta
+    param : [x, dim, keep_dim]
   kernel :
     func : frobenius_norm
+    param : [x, dim, keep_dim]
   interfaces : paddle::dialect::InferSymbolicShapeInterface
 
 - op : reshape

paddle/cinn/hlir/dialect/operator/transforms/accuracy_check_pass.cc

@@ -75,10 +75,7 @@ class AddAccuracyCheckPattern
         }
       }
       pir::Operation* pd_op =
-          cinn::dialect::details::RewriteCinnOpToPdOp(op, builder);
-      for (uint32_t i = 0; i < op->num_results(); ++i) {
-        ir_mapping.Add(op->result(i), pd_op->result(i));
-      }
+          cinn::dialect::details::RewriteCinnOpToPdOp(op, ir_mapping, builder);
     };
 
     const auto& ClonePdOp = [&](::pir::Operation* op) -> void {
@@ -106,7 +103,7 @@ class AddAccuracyCheckPattern
 
 class AccuarcyCheckPass : public pir::Pass {
  public:
-  AccuarcyCheckPass() : pir::Pass("accuarcy_check_pass", /*opt_level=*/4) {}
+  AccuarcyCheckPass() : pir::Pass("accuracy_check_pass", /*opt_level=*/4) {}
 
   bool Initialize(pir::IrContext* context) override {
     pir::RewritePatternSet ps(context);

paddle/cinn/hlir/dialect/operator/transforms/add_cinn_pass.cc

@@ -45,6 +45,7 @@
 #include "paddle/cinn/hlir/dialect/operator/transforms/pd_to_cinn_pass.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/pir_to_py_code_converter.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/replace_dynamic_expand_pass.h"
+#include "paddle/cinn/hlir/dialect/operator/transforms/shape_ops_fallback_to_phi_pass.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/split_generate_shape_into_shape_ops_pass.h"
 #include "paddle/fluid/pir/transforms/build_cinn_pass.h"
 #include "paddle/fluid/pir/transforms/general/dead_code_elimination_pass.h"
@@ -161,6 +162,10 @@ void ApplyDivideGroupOpToFusionOpPass(
     pass_manager->AddPass(
         cinn::dialect::ir::CreateDivideGroupOpToFusionOpPass());
   }
+
+  pass_manager->AddPass(cinn::dialect::ir::CreateSingleOpFallbackToPhiPass());
+  pass_manager->AddPass(cinn::dialect::ir::CreateShapeOpsFallbackToPhiPass());
+
   pass_manager->Run(program);
 }
 
@@ -181,7 +186,6 @@ void ApplyCinnLowerPass(
     pass_manager->AddPass(std::move(pass.value()));
   }
 
-  pass_manager->AddPass(cinn::dialect::ir::CreateSingleOpFallbackToPhiPass());
   if (FLAGS_enable_cinn_accuracy_check) {
     VLOG(0) << "Enable CINN Accuracy Check Pass";
     pass_manager->AddPass(cinn::dialect::ir::CreateAccuarcyCheckPass());

paddle/cinn/hlir/dialect/operator/transforms/cinn_to_pd_util.cc

@@ -23,6 +23,7 @@
 #include "paddle/fluid/pir/dialect/operator/ir/op_type.h"
 #include "paddle/fluid/pir/dialect/operator/ir/pd_op.h"
 #include "paddle/pir/include/core/builtin_dialect.h"
+#include "paddle/pir/include/core/ir_mapping.h"
 namespace cinn::dialect::details {
 
 pir::Attribute ArrayAttributeToIntArrayAttribute(
@@ -36,37 +37,147 @@ pir::Attribute ArrayAttributeToIntArrayAttribute(
   return attr_data;
 }
 
+const auto& handler_reduce_sum_op =
+    [](::pir::Operation* op,
+       ::pir::IrMapping& ir_mapping,                    // NOLINT
+       ::pir::Builder& builder) -> ::pir::Operation* {  // NOLINT
+  VLOG(6) << "transform " << op->name() << " from cinn_op to pd_op";
+  auto attrs = op->attributes();
+
+  pir::Attribute attr_axis = ArrayAttributeToIntArrayAttribute(
+      attrs.at("dim").dyn_cast<::pir::ArrayAttribute>());
+  attrs.insert({"axis", attr_axis});
+  attrs.insert({"dtype", attrs["dtype"]});
+  attrs.insert({"keepdim", attrs["keep_dim"]});
+  attrs.erase("dim");
+  attrs.erase("keep_dim");
+
+  auto pd_op = builder.Build<paddle::dialect::SumOp>(
+      ir_mapping.Lookup(op->operand_source(0)), attrs);
+  for (uint32_t i = 0; i < op->num_results(); ++i) {
+    ir_mapping.Add(op->result(i), pd_op->result(i));
+  }
+  return pd_op;
+};
+
 const auto& handler_reduce_max_op =
-    [&](::pir::Operation* op,
-        const ::pir::Builder& builder) -> ::pir::Operation* {
+    [](::pir::Operation* op,
+       ::pir::IrMapping& ir_mapping,                    // NOLINT
+       ::pir::Builder& builder) -> ::pir::Operation* {  // NOLINT
   VLOG(6) << "transform " << op->name() << " from cinn_op to pd_op";
-  auto cinn_op = op->dyn_cast<cinn::dialect::ReduceMaxOp>();
-  auto attr = cinn_op.attributes();
+  auto attrs = op->attributes();
 
   // TODO(chenxi67): 1. CINN op Dialect Normalization；2.AST Op compute
   // Normalization
   pir::Attribute attr_axis = ArrayAttributeToIntArrayAttribute(
-      attr.at("dim").dyn_cast<::pir::ArrayAttribute>());
-  attr.insert({"axis", attr_axis});
-  attr.insert({"keepdim", attr["keep_dim"]});
-  attr.erase("dim");
-  attr.erase("keep_dim");
-
-  auto pd_op =
-      const_cast<::pir::Builder*>(&builder)->Build<paddle::dialect::MaxOp>(
-          cinn_op.operand_source(0), attr);
+      attrs.at("dim").dyn_cast<::pir::ArrayAttribute>());
+  attrs.insert({"axis", attr_axis});
+  attrs.insert({"keepdim", attrs["keep_dim"]});
+  attrs.erase("dim");
+  attrs.erase("keep_dim");
+
+  auto pd_op = builder.Build<paddle::dialect::MaxOp>(
+      ir_mapping.Lookup(op->operand_source(0)), attrs);
+  for (uint32_t i = 0; i < op->num_results(); ++i) {
+    ir_mapping.Add(op->result(i), pd_op->result(i));
+  }
+  return pd_op;
+};
+
+const auto& handler_reduce_min_op =
+    [](::pir::Operation* op,
+       ::pir::IrMapping& ir_mapping,                    // NOLINT
+       ::pir::Builder& builder) -> ::pir::Operation* {  // NOLINT
+  VLOG(6) << "transform " << op->name() << " from cinn_op to pd_op";
+  auto attrs = op->attributes();
+
+  pir::Attribute attr_axis = ArrayAttributeToIntArrayAttribute(
+      attrs.at("dim").dyn_cast<::pir::ArrayAttribute>());
+  attrs.insert({"axis", attr_axis});
+  attrs.insert({"keepdim", attrs["keep_dim"]});
+  attrs.erase("dim");
+  attrs.erase("keep_dim");
+
+  auto pd_op = builder.Build<paddle::dialect::MinOp>(
+      ir_mapping.Lookup(op->operand_source(0)), attrs);
+  for (uint32_t i = 0; i < op->num_results(); ++i) {
+    ir_mapping.Add(op->result(i), pd_op->result(i));
+  }
+  return pd_op;
+};
+
+const auto& handler_reduce_prod_op =
+    [](::pir::Operation* op,
+       ::pir::IrMapping& ir_mapping,                    // NOLINT
+       ::pir::Builder& builder) -> ::pir::Operation* {  // NOLINT
+  VLOG(6) << "transform " << op->name() << " from cinn_op to pd_op";
+  auto attrs = op->attributes();
+
+  pir::Attribute attr_axis = ArrayAttributeToIntArrayAttribute(
+      attrs.at("dim").dyn_cast<::pir::ArrayAttribute>());
+  attrs.insert({"dims", attr_axis});
+  attrs.erase("dim");
+
+  auto pd_op = builder.Build<paddle::dialect::ProdOp>(
+      ir_mapping.Lookup(op->operand_source(0)), attrs);
+  for (uint32_t i = 0; i < op->num_results(); ++i) {
+    ir_mapping.Add(op->result(i), pd_op->result(i));
+  }
   return pd_op;
 };
 
+::pir::Operation* ConvertSliceOp(::pir::Operation* op,
+                                 ::pir::IrMapping& ir_mapping,  // NOLINT
+                                 ::pir::Builder& builder) {     // NOLINT
+  VLOG(6) << "transform " << op->name() << " from cinn_op to pd_op";
+  auto attrs = op->attributes();
+  pir::Attribute starts = ArrayAttributeToIntArrayAttribute(
+      attrs.at("starts").dyn_cast<::pir::ArrayAttribute>());
+  pir::Attribute ends = ArrayAttributeToIntArrayAttribute(
+      attrs.at("ends").dyn_cast<::pir::ArrayAttribute>());
+  attrs["starts"] = starts;
+  attrs["ends"] = ends;
+  auto pd_op = builder.Build<paddle::dialect::SliceOp>(
+      ir_mapping.Lookup(op->operand_source(0)), attrs);
+  for (uint32_t i = 0; i < op->num_results(); ++i) {
+    ir_mapping.Add(op->result(i), pd_op->result(i));
+  }
+  return pd_op;
+}
+
+::pir::Operation* ConvertConcatOp(::pir::Operation* op,
+                                  ::pir::IrMapping& ir_mapping,  // NOLINT
+                                  ::pir::Builder& builder) {     // NOLINT
+  VLOG(6) << "transform " << op->name() << " from cinn_op to pd_op";
+  auto attrs = op->attributes();
+  for (auto item : attrs) {
+    VLOG(0) << item.first;
+  }
+  std::vector<pir::Value> vec_inputs;
+  for (uint32_t i = 0; i < op->num_operands(); ++i) {
+    vec_inputs.push_back(ir_mapping.Lookup(op->operand_source(i)));
+  }
+  auto op_input = builder.Build<pir::CombineOp>(vec_inputs).result(0);
+
+  int axis = attrs.at("axis").dyn_cast<::pir::Int32Attribute>().data();
+
+  auto pd_op = builder.Build<paddle::dialect::ConcatOp>(op_input, axis);
+  for (uint32_t i = 0; i < op->num_results(); ++i) {
+    ir_mapping.Add(op->result(i), pd_op->result(i));
+  }
+  return pd_op;
+}
+
 bool CanApplyOn(::pir::Operation* op) {
   return op->dialect()->name() == "cinn_op";
 }
 
 ::pir::Operation* RewriteCinnOpToPdOp(::pir::Operation* op,
-                                      const ::pir::Builder& builder) {
+                                      ::pir::IrMapping& ir_mapping,  // NOLINT
+                                      ::pir::Builder& builder) {     // NOLINT
   VLOG(8) << "Rewrite CinnOp to PdOp for op: " << op->name();
   auto& op_transformers = TransformContext::Instance();
-  return op_transformers[op->name()](op, builder);
+  return op_transformers[op->name()](op, ir_mapping, builder);
 }
 
 void RewriteCinnOpToPdOp(const ::pir::Block& src_block,
@@ -91,20 +202,37 @@ void RewriteCinnOpToPdOp(const ::pir::Block& src_block,
     }
     ::pir::Operation* new_op;
     if (CanApplyOn(&op)) {
-      new_op = RewriteCinnOpToPdOp(&op, builder);
+      new_op = RewriteCinnOpToPdOp(&op, ir_mapping, builder);
       new_op->MoveTo(target_block, target_block->end());
     } else {
       new_op = op.Clone(ir_mapping, clone_options);
       new_op->MoveTo(target_block, target_block->end());
     }
-    for (uint32_t i = 0; i < op.num_results(); ++i) {
-      ir_mapping.Add(op.result(i), new_op->result(i));
-    }
   }
 }
 
 }  // namespace cinn::dialect::details
 
+REGISTER_TRANSFORM_RULES(reduce_sum_op,
+                         cinn::dialect::ReduceSumOp::name(),
+                         cinn::dialect::details::handler_reduce_sum_op);
+
 REGISTER_TRANSFORM_RULES(reduce_max_op,
                          cinn::dialect::ReduceMaxOp::name(),
                          cinn::dialect::details::handler_reduce_max_op);
+
+REGISTER_TRANSFORM_RULES(reduce_min_op,
+                         cinn::dialect::ReduceMinOp::name(),
+                         cinn::dialect::details::handler_reduce_min_op);
+
+REGISTER_TRANSFORM_RULES(reduce_prod_op,
+                         cinn::dialect::ReduceProdOp::name(),
+                         cinn::dialect::details::handler_reduce_prod_op);
+
+REGISTER_TRANSFORM_RULES(slice_op,
+                         cinn::dialect::SliceOp::name(),
+                         cinn::dialect::details::ConvertSliceOp);
+
+REGISTER_TRANSFORM_RULES(concat_op,
+                         cinn::dialect::ConcatOp::name(),
+                         cinn::dialect::details::ConvertConcatOp);

paddle/cinn/hlir/dialect/operator/transforms/cinn_to_pd_util.h

@@ -20,15 +20,17 @@
 #include "paddle/common/enforce.h"
 
 namespace pir {
+class IrMapping;
 class Block;
 class Operation;
 class Builder;
+class IrMapping;
 }  // namespace pir
 
 namespace cinn::dialect::details {
 
-using TRule =
-    std::function<::pir::Operation*(::pir::Operation*, const ::pir::Builder&)>;
+using TRule = std::function<::pir::Operation*(
+    ::pir::Operation*, ::pir::IrMapping&, ::pir::Builder&)>;
 
 class TransformContext {
  private:
@@ -86,6 +88,8 @@ class TransformRegistrar {
 
 void RewriteCinnOpToPdOp(const ::pir::Block& src_block,
                          ::pir::Block* target_block);
-::pir::Operation* RewriteCinnOpToPdOp(::pir::Operation*, const ::pir::Builder&);
+::pir::Operation* RewriteCinnOpToPdOp(::pir::Operation*,
+                                      ::pir::IrMapping&,  // NOLINT
+                                      ::pir::Builder&);   // NOLINT
 
 }  // namespace cinn::dialect::details

paddle/cinn/hlir/dialect/operator/transforms/pd_to_cinn_pass.cc

@@ -56,6 +56,7 @@ class SumOpPattern : public paddle::drr::DrrPatternBase {
     const auto &cinn_reduce_sum =
         res.Op(cinn::dialect::ReduceSumOp::name(),
                {{"dim", pattern.Attr("axis_info")},
+                {"dtype", pattern.Attr("dtype")},
                 {"keep_dim", pattern.Attr("keep_dim")}});
     res.Tensor("ret") = cinn_reduce_sum(res.Tensor("arg0"));
   }
@@ -128,16 +129,19 @@ class ProdOpPattern : public paddle::drr::DrrPatternBase {
                     {"dtype", pattern.Attr("dtype_2")},
                     {"place", pattern.Attr("place_2")}});
 
-    const auto &pd_max = pattern.Op(paddle::dialect::ProdOp::name(),
-                                    {{"keep_dim", pattern.Attr("keep_dim")}});
+    const auto &pd_max =
+        pattern.Op(paddle::dialect::ProdOp::name(),
+                   {{"keep_dim", pattern.Attr("keep_dim")},
+                    {"reduce_all", pattern.Attr("reduce_all")}});
     pattern.Tensor("ret") = pd_max(pattern.Tensor("arg0"), full_int_array());
 
     // Result patterns
     paddle::drr::ResultPattern res = pattern.ResultPattern();
     const auto &cinn_reduce_max =
         res.Op(cinn::dialect::ReduceProdOp::name(),
                {{"dim", pattern.Attr("axis_info")},
-                {"keep_dim", pattern.Attr("keep_dim")}});
+                {"keep_dim", pattern.Attr("keep_dim")},
+                {"reduce_all", pattern.Attr("reduce_all")}});
     res.Tensor("ret") = cinn_reduce_max(res.Tensor("arg0"));
   }
 };