[infrt] unify the infrt dialect. test=develop (#40451)

cmake/external/llvm.cmake

@@ -99,7 +99,8 @@ endfunction()
 
 function(mlir_add_rewriter td_base)
   set(LLVM_TARGET_DEFINITIONS ${td_base}.td)
-  mlir_tablegen(${td_base}.cpp.inc -gen-rewriters "-I${CMAKE_SOURCE_DIR}/infrt/dialect/pass")
+  set(LLVM_TARGET_DEPENDS  ${LLVM_TARGET_DEPENDS} ${CMAKE_SOURCE_DIR}/paddle/infrt/dialect/infrt/ir/infrt_base.td)
+  mlir_tablegen(${td_base}.cpp.inc -gen-rewriters)
   add_public_tablegen_target(MLIR${td_base}IncGen)
   add_dependencies(mlir-headers MLIR${td_base}IncGen)
 endfunction()

paddle/infrt/CMakeLists.txt

@@ -90,7 +90,6 @@ add_subdirectory(tests)
 set(infrt_mlir_incs
         basic_kernels_inc
         test_kernels_inc
-        infrt_base_inc
         tensor_shape_inc
         dense_tensor_inc
         pd_ops_inc

paddle/infrt/api/infrt_api.cc

@@ -24,7 +24,7 @@
 
 #include "paddle/infrt/common/global.h"
 #include "paddle/infrt/dialect/dense_tensor.h"
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 #include "paddle/infrt/dialect/mlir_loader.h"
 #include "paddle/infrt/host_context/core_runtime.h"
 #include "paddle/infrt/host_context/kernel_registry.h"
@@ -144,7 +144,7 @@ class PredictExecutor : public MlirToRuntimeTranslator {
 
     // process results
     auto& last_op = predict_func.front().back();
-    if (last_op.getName().getStringRef() == "Infrt.return") {
+    if (last_op.getName().getStringRef() == "infrt.return") {
       for (size_t i = 0; i < last_op.getNumOperands(); ++i) {
         auto* value = AddValue(mlir::Value(last_op.getOperand(i)));
         results_.push_back(ValueRef(value));

paddle/infrt/dialect/CMakeLists.txt

@@ -2,26 +2,20 @@ core_gather_headers()
 
 gather_srcs(infrt_src SRCS
     dialect.cc
-    basic_kernels.cc
-    test_kernels.cc
-    infrt_base.cc
-    init_infrt_dialects.cc
+    init_dialects.cc
     tensor_shape.cc
     dense_tensor.cc
     mlir_loader.cc
     diagnostic_utils.cc
-    pd_types.cc
     pd_ops.cc
     )
 
-mlir_tablegen_on(basic_kernels)
-mlir_tablegen_on(test_kernels)
-mlir_tablegen_on(infrt_base DIALECT Infrt)
 mlir_tablegen_on(tensor_shape DIALECT ts)
 mlir_tablegen_on(dense_tensor DIALECT dt)
 mlir_tablegen_on(pd_op_base DIALECT pd)
 mlir_tablegen_on(pd_ops)
 mlir_tablegen_on(pd_extra_ops)
+
 mlir_add_rewriter(rewrite)
 
 # TODO(Superjomn) add a cmake function cc_executable to ecapsulate the following code

paddle/infrt/dialect/dense_tensor.h

@@ -19,7 +19,7 @@
 
 #include <string>
 
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 
 #include "paddle/infrt/dialect/dense_tensor_dialect.hpp.inc"
 

paddle/infrt/dialect/dense_tensor.td

@@ -2,7 +2,7 @@
 #else
 #define DT_OPS
 
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "paddle/infrt/dialect/tensor_shape_base.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 

paddle/infrt/dialect/infrt/CMakeLists.txt

-core_gather_headers()
-
-gather_srcs(infrt_src SRCS
-    common_type.cc
-    infrt_dialect.cc
-    )
-
-
-add_mlir_dialect(infrt_ops infrt)
-
-set(LLVM_TARGET_DEFINITIONS infrt_ops.td)
-mlir_tablegen(infrt_opsAttributes.h.inc -gen-attrdef-decls -dialect=infrt)
-mlir_tablegen(infrt_opsAttributes.cpp.inc -gen-attrdef-defs -dialect=infrt)
-add_public_tablegen_target(MLIRinfrt_opsAttributesIncGen)
-add_dependencies(mlir-headers MLIRinfrt_opsAttributesIncGen)
-
+add_subdirectory(common)
+add_subdirectory(ir)
 add_subdirectory(pass)

paddle/infrt/dialect/infrt/common/CMakeLists.txt

+core_gather_headers()
+
+gather_srcs(infrt_src SRCS
+    types.cc
+    utils.cc
+    )

paddle/infrt/dialect/infrt/common_type.cc → paddle/infrt/dialect/infrt/common/types.cc

@@ -12,7 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 
 namespace infrt {
 

paddle/infrt/dialect/infrt/common/utils.cc

+// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/infrt/dialect/infrt/common/utils.h"
+
+mlir::SmallVector<mlir::Value, 4> infrt::cvtValueToValueRange(
+    const mlir::Value &operand) {
+  return mlir::SmallVector<mlir::Value, 4>(1, operand);
+}
+
+mlir::SmallVector<mlir::Value, 4> infrt::concatTwoValueRange(
+    mlir::ValueRange operand_0, mlir::ValueRange operand_1) {
+  mlir::SmallVector<mlir::Value, 4> operands;
+  operands.append(operand_0.begin(), operand_0.end());
+  operands.append(operand_1.begin(), operand_1.end());
+  return operands;
+}

paddle/infrt/dialect/pd_types.cc → paddle/infrt/dialect/infrt/common/utils.h

@@ -12,4 +12,20 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/infrt/dialect/pd_types.h"
+#pragma once
+
+#include <mlir/IR/Builders.h>
+#include <mlir/IR/Dialect.h>
+#include <mlir/IR/DialectImplementation.h>
+#include <mlir/IR/MLIRContext.h>
+#include <mlir/IR/TypeUtilities.h>
+#include <mlir/IR/Types.h>
+
+namespace infrt {
+
+mlir::SmallVector<mlir::Value, 4> cvtValueToValueRange(
+    const mlir::Value &operand);
+
+mlir::SmallVector<mlir::Value, 4> concatTwoValueRange(
+    mlir::ValueRange operand_0, mlir::ValueRange operand_1);
+}  // namespace infrt

paddle/infrt/dialect/infrt/ir/CMakeLists.txt

+core_gather_headers()
+
+gather_srcs(infrt_src SRCS
+    infrt_dialect.cc
+    basic_kernels.cc
+    test_kernels.cc
+    )
+
+add_mlir_dialect(infrt_ops infrt)
+
+set(LLVM_TARGET_DEFINITIONS infrt_ops.td)
+mlir_tablegen(infrt_opsAttributes.h.inc -gen-attrdef-decls -dialect=infrt)
+mlir_tablegen(infrt_opsAttributes.cpp.inc -gen-attrdef-defs -dialect=infrt)
+add_public_tablegen_target(MLIRinfrt_opsAttributesIncGen)
+add_dependencies(mlir-headers MLIRinfrt_opsAttributesIncGen)
+
+mlir_tablegen_on(basic_kernels)
+mlir_tablegen_on(test_kernels)

paddle/infrt/dialect/basic_kernels.cc → paddle/infrt/dialect/infrt/ir/basic_kernels.cc

@@ -12,7 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/infrt/dialect/basic_kernels.h"
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.h"
 
 #include <llvm/ADT/STLExtras.h>
 #include <mlir/IR/Attributes.h>
@@ -30,23 +30,6 @@ namespace infrt {
 namespace dialect {
 using namespace mlir;  // NOLINT
 
-static ParseResult parseCallOp(OpAsmParser &parser,       // NOLINT
-                               OperationState &result) {  // NOLINT
-  SymbolRefAttr callee_attr;
-  FunctionType callee_type;
-  SmallVector<OpAsmParser::OperandType, 4> operands;
-  auto callee_loc = parser.getNameLoc();
-  if (parser.parseAttribute(callee_attr, "callee", result.attributes) ||
-      parser.parseOperandList(operands, OpAsmParser::Delimiter::Paren) ||
-      parser.parseOptionalAttrDict(result.attributes) ||
-      parser.parseColonType(callee_type) ||
-      parser.addTypesToList(callee_type.getResults(), result.types) ||
-      parser.resolveOperands(
-          operands, callee_type.getInputs(), callee_loc, result.operands))
-    return failure();
-  return success();
-}
-
 static ParseResult parseConstantOp(Type attrType,
                                    OpAsmParser &parser,       // NOLINT
                                    OperationState &result) {  // NOLINT
@@ -79,24 +62,6 @@ static ParseResult parseConstantI64Op(OpAsmParser &parser,       // NOLINT
       IntegerType::get(result.getContext(), 64), parser, result);
 }
 
-static ParseResult parseReturnOp(OpAsmParser &parser,       // NOLINT
-                                 OperationState &result) {  // NOLINT
-  SmallVector<OpAsmParser::OperandType, 2> opInfo;
-  SmallVector<Type, 2> types;
-  llvm::SMLoc loc = parser.getCurrentLocation();
-  return failure(parser.parseOperandList(opInfo) ||
-                 (!opInfo.empty() && parser.parseColonTypeList(types)) ||
-                 parser.resolveOperands(opInfo, types, loc, result.operands));
-}
-
-static void print(OpAsmPrinter &p, CallOp op) {  // NOLINT
-  p << op->getAttr("callee") << "(";
-  p.printOperands(op.getOperands());
-  p << ")";
-  p.printOptionalAttrDict(op->getAttrs(), {"callee"});
-  p << " : ";
-}
-
 static void printConstant(OpAsmPrinter &p, mlir::Operation *op) {  // NOLINT
   p << " ";
   p.printOptionalAttrDict(op->getAttrs(), /*elidedAttrs=*/{"value"});
@@ -127,37 +92,13 @@ static void print(OpAsmPrinter &p, ConstantI64Op op) {  // NOLINT
   printConstant(p, op);
 }
 
-static void print(OpAsmPrinter &p, ReturnOp op) {  // NOLINT
-  if (op.getNumOperands() > 0) {
-    p << ' ';
-    p.printOperands(op.getOperands());
-    p << " : ";
-    llvm::interleaveComma(op.getOperands(), p);
-  }
-}
-
-static LogicalResult verify(CallOp op) { return success(); }
-
 static LogicalResult verify(ConstantF32Op op) { return success(); }
 static LogicalResult verify(ConstantI32Op op) { return success(); }
 static LogicalResult verify(ConstantF64Op op) { return success(); }
 static LogicalResult verify(ConstantI64Op op) { return success(); }
 
-static LogicalResult verify(ReturnOp op) {
-  auto function = dyn_cast<FuncOp>(op->getParentOp());
-
-  if (!function) return success();
-
-  auto results = function.getType().getResults();
-  if (op.getNumOperands() != results.size())
-    return op.emitOpError("has ")
-           << op.getNumOperands()
-           << " operands, but enclosing function returns " << results.size();
-
-  return success();
-}
 }  // namespace dialect
 }  // namespace infrt
 
 #define GET_OP_CLASSES
-#include "paddle/infrt/dialect/basic_kernels.cpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.cpp.inc"

paddle/infrt/dialect/basic_kernels.h → paddle/infrt/dialect/infrt/ir/basic_kernels.h

@@ -18,4 +18,4 @@
 #include <mlir/Interfaces/SideEffectInterfaces.h>
 
 #define GET_OP_CLASSES
-#include "paddle/infrt/dialect/basic_kernels.hpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.hpp.inc"

paddle/infrt/dialect/basic_kernels.td → paddle/infrt/dialect/infrt/ir/basic_kernels.td

@@ -4,10 +4,10 @@
 #else
 #define BASIC_OPS
 
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 
-class INFRT_Op<string mnemonic, list<OpTrait> traits = []> : Op<INFRT_Dialect, mnemonic, !listconcat(traits, [IsolatedFromAbove])> {
+class INFRT_Op<string mnemonic, list<OpTrait> traits = []> : Op<Infrt_Dialect, mnemonic, !listconcat(traits, [IsolatedFromAbove])> {
 
   // Each registered op needs to provide all of a printer, parser and verifier.
   let printer = [{ return infrt::dialect::print(p, *this); }];
@@ -15,23 +15,6 @@ class INFRT_Op<string mnemonic, list<OpTrait> traits = []> : Op<INFRT_Dialect, m
   let parser = [{ return infrt::dialect::parse$cppClass(parser, result); }];
 }
 
-def CallOp : INFRT_Op<"call"> {
-  let summary = "call a host operation";
-  let description = [{
-      The "infrt.call" operation represents a direct call to a function. The operands and result types of the call must match the specified function type.
-
-          %2 = infrt.call @add(%0, %1) : (f32, f32) -> f32
-    }];
-
-  let arguments = (ins FlatSymbolRefAttr:$callee, Variadic<AnyType>:$operands);
-  let results = (outs Variadic<AnyType>);
-
-  let extraClassDeclaration = [{
-      mlir::StringRef getCallee() { return callee(); }
-      mlir::FunctionType getCalleeType();
-    }];
-}
-
 class ConstantOp<string suffix, Type baseType, Attr attr>
     : INFRT_Op<"constant." # suffix, [NoSideEffect]> {
   let summary = "constant value constructor in host";
@@ -45,22 +28,6 @@ def ConstantI64Op : ConstantOp<"i64", I64, I64Attr>;
 def ConstantF32Op : ConstantOp<"f32", F32, F32Attr>;
 def ConstantF64Op : ConstantOp<"f64", F64, F64Attr>;
 
-def ReturnOp : INFRT_Op<"return", [Terminator]> {
-  let summary = "host executor return operation";
-  let description = [{
-      The "Infrt.return" operation represents a return operation within a function.
-
-        func @foo() : (i32, f8) {
-        Infrt.return %0, %1 : i32, f8
-        }
-    }];
-
-  let arguments = (ins Variadic<AnyType>:$operands);
-
-  let builders = [OpBuilder<(ins),
-                  [{ build($_builder, $_state, llvm::None); }]>];
-}
-
 class AddOp<string suffix, Type type> : INFRT_Op<"add." # suffix, [NoSideEffect]> {
   let summary = "infrt.add operation";
   let description = [{
@@ -112,7 +79,7 @@ def PrintF32Op : PrintOp<"f32", F32>;
 def PrintF64Op : PrintOp<"f64", F64>;
 
 def PrintStringOp : INFRT_Op<"print_string"> {
-  let summary = "Infrt.print_string";
+  let summary = "infrt.print_string";
   let description = [{
       An operation that prints a string.
   }];

paddle/infrt/dialect/infrt/infrt_ops_base.td → paddle/infrt/dialect/infrt/ir/infrt_base.td

@@ -101,4 +101,21 @@ class Infrt_Attr<string name, list<Trait> traits = [],
     : AttrDef<Infrt_Dialect, name, traits, baseCppClass> {
   let mnemonic = ?;
 }
+
+// tools function. used for pattern rewriter
+class INFRT_createI32Attr<string value> : NativeCodeCall<
+    "$_builder.getI32IntegerAttr(" # value # ")">;
+
+class INFRT_createSI32Attr<string value> : NativeCodeCall<
+    "$_builder.getSI32IntegerAttr(" # value # ")">;
+
+class INFRT_createF32Attr<string value> : NativeCodeCall<
+    "$_builder.getF32FloatAttr(" # value # ")">;
+
+def INFRT_cvtValueToValueRange : NativeCodeCall<
+    "infrt::cvtValueToValueRange($0)">;
+
+def INFRT_concatTwoValueRange : NativeCodeCall<
+    "infrt::concatTwoValueRange($0, $1)">;
+
 #endif // INFRT_OPS_BASE

paddle/infrt/dialect/infrt/infrt_dialect.cc → paddle/infrt/dialect/infrt/ir/infrt_dialect.cc

@@ -12,40 +12,52 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 
 #include <llvm/ADT/TypeSwitch.h>
 #include <mlir/IR/Builders.h>
 #include <mlir/IR/BuiltinOps.h>
 #include <mlir/IR/DialectImplementation.h>
 #include "paddle/infrt/dialect/dense_tensor.h"
-#include "paddle/infrt/dialect/infrt/infrt_opsDialect.cpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsDialect.cpp.inc"
 
 #define GET_TYPEDEF_CLASSES
-#include "paddle/infrt/dialect/infrt/infrt_opsTypes.cpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsTypes.cpp.inc"
 
 #define GET_ATTRDEF_CLASSES
-#include "paddle/infrt/dialect/infrt/infrt_opsAttributes.cpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsAttributes.cpp.inc"
 
 #define GET_OP_CLASSES
-#include "paddle/infrt/dialect/infrt/infrt_ops.cpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_ops.cpp.inc"
+
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.h"
+
+#include "paddle/infrt/dialect/infrt/ir/test_kernels.h"
 
 namespace infrt {
 
 void InfrtDialect::initialize() {
   addTypes<
 #define GET_TYPEDEF_LIST
-#include "paddle/infrt/dialect/infrt/infrt_opsTypes.cpp.inc"  // NOLINT
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsTypes.cpp.inc"  // NOLINT
       >();
 
   addAttributes<
 #define GET_ATTRDEF_LIST
-#include "paddle/infrt/dialect/infrt/infrt_opsAttributes.cpp.inc"  // NOLINT
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsAttributes.cpp.inc"  // NOLINT
       >();
 
   addOperations<
 #define GET_OP_LIST
-#include "paddle/infrt/dialect/infrt/infrt_ops.cpp.inc"  // NOLINT
+#include "paddle/infrt/dialect/infrt/ir/infrt_ops.cpp.inc"  // NOLINT
+      >();
+  addOperations<
+#define GET_OP_LIST
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.cpp.inc"
+      >();
+  addOperations<
+#define GET_OP_LIST
+#include "paddle/infrt/dialect/infrt/ir/test_kernels.cpp.inc"
       >();
 }
 
@@ -128,7 +140,7 @@ mlir::Type InfrtDialect::parseType(::mlir::DialectAsmParser &parser) const {
 
 void InfrtDialect::printType(::mlir::Type type,
                              ::mlir::DialectAsmPrinter &os) const {
-  // print LoDTensorType, for example: !Infrt.lod_tensor<3x64x3x3xf32,5>
+  // print LoDTensorType, for example: !infrt.lod_tensor<3x64x3x3xf32,5>
   if (type.isa<infrt::LoDTensorType>()) {
     auto lod_tensor_type = type.cast<infrt::LoDTensorType>();
     os << "lod_tensor<";

paddle/infrt/dialect/infrt/infrt_dialect.h → paddle/infrt/dialect/infrt/ir/infrt_dialect.h

@@ -22,14 +22,14 @@
 #include <mlir/IR/Dialect.h>
 #include <mlir/IR/OpDefinition.h>
 #include <mlir/Interfaces/SideEffectInterfaces.h>
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 
-#include "paddle/infrt/dialect/infrt/infrt_opsDialect.h.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsDialect.h.inc"
 #define GET_TYPEDEF_CLASSES
-#include "paddle/infrt/dialect/infrt/infrt_opsTypes.h.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsTypes.h.inc"
 
 #define GET_ATTRDEF_CLASSES
-#include "paddle/infrt/dialect/infrt/infrt_opsAttributes.h.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_opsAttributes.h.inc"
 
 #define GET_OP_CLASSES
-#include "paddle/infrt/dialect/infrt/infrt_ops.h.inc"
+#include "paddle/infrt/dialect/infrt/ir/infrt_ops.h.inc"

paddle/infrt/dialect/infrt/infrt_ops.td → paddle/infrt/dialect/infrt/ir/infrt_ops.td

-include "paddle/infrt/dialect/infrt/infrt_ops_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 
 // Op definition
 class Infrt_Op<string mnemonic, list<OpTrait> traits = []> : Op<Infrt_Dialect, mnemonic, traits> {
@@ -33,6 +33,26 @@ def Infrt_ReturnOp : Infrt_Op<"return", [Terminator]> {
   let assemblyFormat = "attr-dict ($operands^ `:` type($operands))?";
 }
 
+def Infrt_CallOp : Infrt_Op<"call"> {
+  let summary = "call a host operation";
+  let description = [{
+      The "infrt.call" operation represents a direct call to a function. The operands and result types of the call must match the specified function type.
+
+          %2 = infrt.call @add(%0, %1) : (f32, f32) -> f32
+    }];
+
+  let arguments = (ins FlatSymbolRefAttr:$callee, Variadic<AnyType>:$operands);
+  let results = (outs Variadic<AnyType>);
+
+  //let extraClassDeclaration = [{
+  //    mlir::StringRef getCallee() { return callee(); }
+  //    mlir::FunctionType getCalleeType();
+  //  }];
+  let assemblyFormat = [{
+    $callee `(` $operands `)` attr-dict `:` functional-type($operands, results)
+  }];
+}
+
 def Infrt_CvtTensorOp : Infrt_Op<"cvt_tensor", [NoSideEffect]> {
   let summary = "convert tensor type op";
   let description = [{convert tensor type op!}];

paddle/infrt/dialect/test_kernels.cc → paddle/infrt/dialect/infrt/ir/test_kernels.cc

@@ -12,7 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/infrt/dialect/test_kernels.h"
+#include "paddle/infrt/dialect/infrt/ir/test_kernels.h"
 
 #include <mlir/IR/Builders.h>
 #include <mlir/IR/OpDefinition.h>
@@ -147,7 +147,7 @@ static mlir::LogicalResult verify(BenchmarkOp op) {
   // Verify that the target benchmark region has exactly one return value.
   auto &region = op.region();
   auto &last_op = region.front().back();
-  if (last_op.getName().getStringRef() != "Infrt.return") {
+  if (last_op.getName().getStringRef() != "infrt.return") {
     return op.emitOpError("missing return statement");
   }
   if (last_op.getNumOperands() != 1) {
@@ -161,4 +161,4 @@ static mlir::LogicalResult verify(BenchmarkOp op) {
 }  // namespace infrt
 
 #define GET_OP_CLASSES
-#include "paddle/infrt/dialect/test_kernels.cpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/test_kernels.cpp.inc"

paddle/infrt/dialect/test_kernels.h → paddle/infrt/dialect/infrt/ir/test_kernels.h

@@ -17,4 +17,4 @@
 #include <mlir/Interfaces/SideEffectInterfaces.h>
 
 #define GET_OP_CLASSES
-#include "paddle/infrt/dialect/test_kernels.hpp.inc"
+#include "paddle/infrt/dialect/infrt/ir/test_kernels.hpp.inc"

paddle/infrt/dialect/test_kernels.td → paddle/infrt/dialect/infrt/ir/test_kernels.td

@@ -4,12 +4,12 @@
 #else
 #define TEST_OPS
 
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 
 // Base class for Test dialect ops.
 class Test_Op<string mnemonic, list<OpTrait> traits = []> :
-    Op<INFRT_Dialect, mnemonic, !listconcat(traits, [IsolatedFromAbove])> {
+    Op<Infrt_Dialect, mnemonic, !listconcat(traits, [IsolatedFromAbove])> {
 
   // Each registered op in the Test namespace needs to provide all of a printer,
   // parser and verifier.
@@ -45,7 +45,7 @@ def BenchmarkOp : Test_Op<"benchmark"> {
          // The following code benchmarks the infrt.add.i32 kernel.
          %x = infrt.add.i32 %c, %c
          // The benchmarked function needs to return exactly one value.
-         Infrt.return %x : i32
+         infrt.return %x : i32
        }
   }];
 

paddle/infrt/dialect/infrt/pass/infrt_op_fuse.td

@@ -2,7 +2,7 @@
 #define INFRT_OP_FUSE
 
 include "mlir/Interfaces/SideEffectInterfaces.td"
-include "paddle/infrt/dialect/infrt/infrt_ops.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_ops.td"
 include "paddle/infrt/dialect/pd_ops.td"
 
 def FuseCvtTensorPattern : Pat<

paddle/infrt/dialect/infrt/pass/infrt_op_fuse_pass.cc

@@ -15,7 +15,7 @@
 #include "paddle/infrt/dialect/infrt/pass/infrt_op_fuse_pass.h"
 
 #include <mlir/Transforms/GreedyPatternRewriteDriver.h>
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 #include "paddle/infrt/dialect/pd_ops.h"
 namespace {
 #include "paddle/infrt/dialect/infrt/pass/infrt_op_fuse.cpp.inc"  // NOLINT

paddle/infrt/dialect/infrt_base.cc

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#include "paddle/infrt/dialect/infrt_base.h"
-
-#include "paddle/infrt/dialect/basic_kernels.h"
-#include "paddle/infrt/dialect/dense_tensor.h"
-#include "paddle/infrt/dialect/test_kernels.h"
-
-namespace infrt {
-namespace dialect {
-
-// ----INFRTDialect definition begin----
-void INFRTDialect::initialize() {
-  allowUnknownTypes();
-  allowUnknownOperations();
-  addOperations<
-#define GET_OP_LIST
-#include "paddle/infrt/dialect/basic_kernels.cpp.inc"
-      >();
-  addOperations<
-#define GET_OP_LIST
-#include "paddle/infrt/dialect/test_kernels.cpp.inc"
-      >();
-}
-
-mlir::Type INFRTDialect::parseType(mlir::DialectAsmParser &parser) const {
-  llvm::StringRef keyword;
-  if (parser.parseKeyword(&keyword)) return mlir::Type();
-  // parse TensorMapType, for example: !infrt.tensor_map
-  parser.emitError(parser.getCurrentLocation(), "unknown infrt type: ")
-      << keyword;
-  return mlir::Type();
-}
-
-void INFRTDialect::printType(mlir::Type type,
-                             mlir::DialectAsmPrinter &printer) const {
-  // print TensorMapType, for example: !infrt.tensor_map
-  llvm_unreachable("unknown infrt type.");
-}
-
-// ----INFRTDialect definition end----
-
-}  // namespace dialect
-}  // namespace infrt

paddle/infrt/dialect/infrt_base.h

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-#pragma once
-
-#include <mlir/IR/Builders.h>
-#include <mlir/IR/Dialect.h>
-#include <mlir/IR/DialectImplementation.h>
-#include <mlir/IR/MLIRContext.h>
-#include <mlir/IR/TypeUtilities.h>
-#include <mlir/IR/Types.h>
-
-#include "paddle/infrt/dialect/infrt_base.hpp.inc"
-
-namespace infrt {
-namespace dialect {
-
-class INFRTDialect : public mlir::Dialect {
-  explicit INFRTDialect(mlir::MLIRContext *context)
-      : mlir::Dialect(
-            getDialectNamespace(), context, mlir::TypeID::get<INFRTDialect>()) {
-    initialize();
-  }
-
-  // parse types registered to the dialect.
-  mlir::Type parseType(mlir::DialectAsmParser &parser) const override;
-  // print types registered to the dialect.
-  void printType(mlir::Type type,
-                 mlir::DialectAsmPrinter &printer) const override;
-
-  void initialize();
-  friend class mlir::MLIRContext;
-
- public:
-  static ::llvm::StringRef getDialectNamespace() { return "Infrt"; }
-};
-}  // namespace dialect
-
-template <typename T>
-static mlir::IntegerAttr createI32Attr(mlir::OpBuilder &b,  // NOLINT
-                                       mlir::Location loc,
-                                       T constant) {
-  return b.getIntegerAttr(b.getI32Type(), constant);
-}
-
-template <typename T>
-static mlir::IntegerAttr createSI32Attr(mlir::OpBuilder &b,  // NOLINT
-                                        mlir::Location loc,
-                                        T constant) {
-  return b.getSI32IntegerAttr(constant);
-}
-
-template <typename T>
-static mlir::FloatAttr createF32Attr(mlir::OpBuilder &b,  // NOLINT
-                                     mlir::Location loc,
-                                     T constant) {
-  return b.getF32FloatAttr(constant);
-}
-
-static mlir::SmallVector<mlir::Value, 4> cvtValueToValueRange(
-    const mlir::Value &operand) {
-  return mlir::SmallVector<mlir::Value, 4>(1, operand);
-}
-
-static mlir::SmallVector<mlir::Value, 4> concatTwoValueRange(
-    mlir::ValueRange operand_0, mlir::ValueRange operand_1) {
-  mlir::SmallVector<mlir::Value, 4> operands;
-  operands.append(operand_0.begin(), operand_0.end());
-  operands.append(operand_1.begin(), operand_1.end());
-  return operands;
-}
-}  // namespace infrt

paddle/infrt/dialect/infrt_base.td

-#ifndef INFRT_BASE
-#define INFRT_BASE
-
-include "mlir/IR/OpBase.td"
-include "paddle/infrt/dialect/infrt/infrt_ops_base.td"
-
-def INFRT_Dialect : Dialect {
-  let name = "Infrt";
-
-  let description = [{
-    The INFRT host dialect.
-  }];
-
-  let cppNamespace = "::infrt::dialect";
-}
-
-def BufferType : OpaqueType<"b", "buffer", "buffer">;
-
-class INFRT_createI32Attr<string value> : NativeCodeCall<
-    "infrt::createI32Attr($_builder, $_loc, " # value # ")">;
-
-class INFRT_createSI32Attr<string value> : NativeCodeCall<
-    "infrt::createSI32Attr($_builder, $_loc, " # value # ")">;
-
-class INFRT_createF32Attr<string value> : NativeCodeCall<
-    "infrt::createF32Attr($_builder, $_loc, " # value # ")">;
-
-def INFRT_cvtValueToValueRange : NativeCodeCall<
-    "infrt::cvtValueToValueRange($0)">;
-
-def INFRT_concatTwoValueRange : NativeCodeCall<
-    "infrt::concatTwoValueRange($0, $1)">;
-#endif  // INFRT_BASE

paddle/infrt/dialect/init_infrt_dialects.cc → paddle/infrt/dialect/init_dialects.cc

@@ -12,14 +12,14 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/infrt/dialect/init_infrt_dialects.h"
+#include "paddle/infrt/dialect/init_dialects.h"
 
 #include <glog/logging.h>
 
-#include "paddle/infrt/dialect/basic_kernels.h"
 #include "paddle/infrt/dialect/dense_tensor.h"
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
-#include "paddle/infrt/dialect/infrt_base.h"
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
+
 #include "paddle/infrt/dialect/pd_ops.h"
 #include "paddle/infrt/dialect/phi/ir/infrt_phi_tensor.h"
 #include "paddle/infrt/dialect/phi/ir/phi_base.h"
@@ -30,8 +30,7 @@
 namespace infrt {
 void registerCinnDialects(mlir::DialectRegistry &registry) {  // NOLINT
   registry.insert<ts::TensorShapeDialect,
-                  dialect::INFRTDialect,
-                  infrt::InfrtDialect,
+                  InfrtDialect,
                   dt::DTDialect,
                   mlir::pd::PaddleDialect,
 #ifdef INFRT_WITH_PHI

paddle/infrt/dialect/mlir_loader.cc

@@ -28,7 +28,7 @@
 #include <vector>
 
 #include "paddle/infrt/dialect/diagnostic_utils.h"
-#include "paddle/infrt/dialect/init_infrt_dialects.h"
+#include "paddle/infrt/dialect/init_dialects.h"
 
 namespace infrt {
 namespace dialect {

paddle/infrt/dialect/mlir_loader_test.cc

@@ -22,7 +22,7 @@
 
 #include <string>
 
-#include "paddle/infrt/dialect/init_infrt_dialects.h"
+#include "paddle/infrt/dialect/init_dialects.h"
 
 namespace infrt {
 namespace dialect {
@@ -32,13 +32,13 @@ TEST(MlirLoader, basic) {
 
   auto source = R"ROC(
 func @main() -> f32 {
-  %v0 = Infrt.constant.f32 1.0
-  %v1 = Infrt.constant.f32 2.0
-  %value = "Infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
+  %v0 = infrt.constant.f32 1.0
+  %v1 = infrt.constant.f32 2.0
+  %value = "infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
 
-  "Infrt.print.f32"(%v0) : (f32) -> ()
+  "infrt.print.f32"(%v0) : (f32) -> ()
 
-  Infrt.return %value : f32
+  infrt.return %value : f32
 }
 )ROC";
 

paddle/infrt/dialect/opt.cc

@@ -14,7 +14,7 @@
 
 #include <mlir/Support/MlirOptMain.h>
 #include <mlir/Transforms/Passes.h>
-#include "paddle/infrt/dialect/init_infrt_dialects.h"
+#include "paddle/infrt/dialect/init_dialects.h"
 
 int main(int argc, char **argv) {
   mlir::DialectRegistry registry;

paddle/infrt/dialect/pd_op_base.td

@@ -6,7 +6,7 @@
 
 include "mlir/IR/OpBase.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
-include "paddle/infrt/dialect/infrt/infrt_ops_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 
 def PD_Dialect : Dialect {
   let name = "pd";

paddle/infrt/dialect/pd_ops.cc

@@ -16,7 +16,6 @@
 
 #include <mlir/IR/Matchers.h>
 #include <mlir/IR/PatternMatch.h>
-#include "paddle/infrt/dialect/infrt_base.h"
 
 #define GET_OP_CLASSES
 #include "paddle/infrt/dialect/pd_ops.cpp.inc"  // NOLINT

paddle/infrt/dialect/pd_ops.h

@@ -28,7 +28,7 @@
 #include <mlir/Interfaces/InferTypeOpInterface.h>
 #include <mlir/Interfaces/LoopLikeInterface.h>
 #include <mlir/Interfaces/SideEffectInterfaces.h>
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 
 namespace mlir {
 namespace pd {

paddle/infrt/dialect/pd_types.h

-// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
-//
-// Licensed under the Apache License, Version 2.0 (the "License");
-// you may not use this file except in compliance with the License.
-// You may obtain a copy of the License at
-//
-//     http://www.apache.org/licenses/LICENSE-2.0
-//
-// Unless required by applicable law or agreed to in writing, software
-// distributed under the License is distributed on an "AS IS" BASIS,
-// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-// See the License for the specific language governing permissions and
-// limitations under the License.
-
-// This file defines the types used in PaddlePaddle MLIR dialect.
-// We borrowed much ideas from tensorflow mlir dialect (tf_types.h in
-// tensorflow).
-
-#pragma once
-
-#include <mlir/IR/Diagnostics.h>
-#include <mlir/IR/Location.h>
-#include <mlir/IR/Operation.h>
-#include <mlir/IR/TypeUtilities.h>
-#include <mlir/IR/Types.h>
-
-namespace mlir {
-namespace PD {
-
-class PaddleType : public Type {
- public:
-  using Type::Type;
-
-  static bool classof(Type type);
-};
-
-namespace detail {
-
-template <typename Derived>
-class PaddleTypeImpl : public Type::TypeBase<Derived, PaddleType, TypeStorage> {
- public:
-  using Base = typename Type::TypeBase<Derived, PaddleType, TypeStorage>;
-  using PDBase = PaddleTypeImpl<Derived>;
-  using Base::Base;
-};
-
-}  // namespace detail
-
-#define HANDLE_PD_TYPE(pdtype, enumerant, name)                      \
-  class pdtype##Type : public detail::PaddleTypeImpl<pdtype##Type> { \
-   public:                                                           \
-    using PDBase::PDBase;                                            \
-  };
-
-}  // namespace PD
-}  // namespace mlir

paddle/infrt/dialect/phi/data_type.h

@@ -14,7 +14,7 @@
 
 #pragma once
 
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 #include "paddle/phi/common/backend.h"
 #include "paddle/phi/common/data_type.h"
 #include "paddle/phi/common/layout.h"

paddle/infrt/dialect/phi/ir/infrt_phi_base.td

@@ -2,7 +2,7 @@
 #define PHI_BASE
 
 include "mlir/IR/OpBase.td"
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "mlir/Interfaces/InferTypeOpInterface.td"
 
 def PHI_Dialect : Dialect {

paddle/infrt/dialect/phi/ir/infrt_phi_kernel.td

@@ -3,7 +3,7 @@
 
 include "mlir/Interfaces/SideEffectInterfaces.td"
 include "mlir/IR/OpBase.td"
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "paddle/infrt/dialect/phi/ir/infrt_phi_base.td"
 
 def PHI_CPUKernelDialect : Dialect {

paddle/infrt/dialect/phi/ir/infrt_phi_tensor.td

@@ -5,7 +5,7 @@
 include "paddle/infrt/dialect/phi/ir/infrt_phi_base.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 include "mlir/IR/OpBase.td"
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 
 def PHI_DenseTensorDialect : Dialect {
   let name = "phi_dt";

paddle/infrt/dialect/phi/ir/phi_base.h

@@ -18,7 +18,7 @@
 #include <mlir/Interfaces/SideEffectInterfaces.h>
 
 #include <string>
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 
 #include "paddle/infrt/dialect/phi/ir/infrt_phi_baseDialect.h.inc"
 

paddle/infrt/dialect/phi/ir/phi_kernels.h

@@ -30,7 +30,7 @@
 #include <mlir/Interfaces/SideEffectInterfaces.h>
 
 #include "paddle/infrt/dialect/dense_tensor.h"
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 #include "paddle/infrt/dialect/phi/ir/phi_base.h"
 
 #include "paddle/infrt/dialect/phi/ir/phi_cpu_kernelsDialect.h.inc"

paddle/infrt/dialect/phi/pass/kernel_op_desc.h

@@ -16,7 +16,7 @@
 
 #include <string>
 #include <vector>
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 
 namespace infrt {
 

paddle/infrt/dialect/phi/pass/phi_op_cvt_pass.cc

@@ -24,13 +24,29 @@
 #include <unordered_set>
 #include <vector>
 
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 #include "paddle/infrt/dialect/phi/ir/infrt_phi_tensor.h"
 #include "paddle/infrt/dialect/phi/pass/kernel_op_desc.h"
 #include "paddle/infrt/dialect/phi/pass/proto_arg_map_context.h"
 #include "paddle/phi/core/compat/op_utils.h"
 #include "paddle/phi/ops/compat/signatures.h"
-namespace infrt {
+
+namespace {
+class phiOpCvtPass
+    : public mlir::PassWrapper<phiOpCvtPass, mlir::FunctionPass> {
+ public:
+  ::llvm::StringRef getName() const override { return "phiOpCvtPass"; }
+  void runOnFunction() override;
+  explicit phiOpCvtPass(
+      std::vector<infrt::Place> valid_places = std::vector<infrt::Place>())
+      : valid_places_(valid_places) {}
+
+ private:
+  void convertStage();
+  void diapatchStage();
+  std::vector<infrt::Place> valid_places_;
+};
+
 // Implementation of the phiOpCvtPass.
 void phiOpCvtPass::runOnFunction() {
   convertStage();
@@ -63,7 +79,7 @@ void phiOpCvtPass::convertStage() {
 
     ::phi::KernelSignature kernel_sign =
         ::phi::OpUtilsMap::Instance().GetArgumentMappingFn(op_name)(
-            ProtoArgumentMappingContext(op));
+            infrt::ProtoArgumentMappingContext(op));
     // resort input&output according to kernel_sign
     ::llvm::SmallVector<mlir::Value, 4> inputs, ori_output;
     ::llvm::SmallVector<mlir::Type, 4> output_types;
@@ -109,10 +125,10 @@ void phiOpCvtPass::diapatchStage() {
   }
 
   mlir::OpBuilder builder(&block, block.begin());
-  std::map<TargetType, mlir::Value> phi_context;
+  std::map<infrt::TargetType, mlir::Value> phi_context;
   for (infrt::KernelOp kernel_op : worklist) {
     std::string kernel_name = kernel_op.name().str();
-    std::vector<PhiKernelDesc> candidates =
+    std::vector<infrt::PhiKernelDesc> candidates =
         getCandidateKernels(kernel_name, valid_places_);
     if (candidates.empty()) {
       LOG(FATAL) << "No candidate kernels for op:" << kernel_name;
@@ -121,12 +137,13 @@ void phiOpCvtPass::diapatchStage() {
     builder.setInsertionPoint(kernel_op);
 
     // Todo: Implimentation the concrete pass pick strategy
-    const PhiKernelDesc &phi_kernel_desc = candidates.front();
+    const infrt::PhiKernelDesc &phi_kernel_desc = candidates.front();
 
-    kernel_name = getPhiTargetPrefix(phi_kernel_desc.kernelType.target) +
-                  kernel_name +
-                  getPhiPrecisionSuffix(phi_kernel_desc.kernelType.precision) +
-                  getPhiLayoutSuffix(phi_kernel_desc.kernelType.layout);
+    kernel_name =
+        infrt::getPhiTargetPrefix(phi_kernel_desc.kernelType.target) +
+        kernel_name +
+        infrt::getPhiPrecisionSuffix(phi_kernel_desc.kernelType.precision) +
+        infrt::getPhiLayoutSuffix(phi_kernel_desc.kernelType.layout);
 
     mlir::OperationName operation_name(kernel_name, kernel_op.getContext());
     mlir::OperationState operation_state(kernel_op.getLoc(), operation_name);
@@ -134,18 +151,18 @@ void phiOpCvtPass::diapatchStage() {
     if (phi_context.find(phi_kernel_desc.kernelType.target) ==
         phi_context.end()) {
       switch (phi_kernel_desc.kernelType.target) {
-        case TargetType::CPU: {
+        case infrt::TargetType::CPU: {
           auto context_value =
               builder
                   .create<infrt::phi::CreateCPUContextOp>(
                       kernel_op.getLoc(),
-                      phi::ContextType::get(kernel_op.getContext(),
-                                            TargetType::CPU))
+                      infrt::phi::ContextType::get(kernel_op.getContext(),
+                                                   infrt::TargetType::CPU))
                   .output();
-          phi_context[TargetType::CPU] = context_value;
+          phi_context[infrt::TargetType::CPU] = context_value;
         } break;
-        case TargetType::GPU:
-        case TargetType::UNK:
+        case infrt::TargetType::GPU:
+        case infrt::TargetType::UNK:
         default:
           LOG(FATAL) << "Unsupported TargetType";
           break;
@@ -155,29 +172,30 @@ void phiOpCvtPass::diapatchStage() {
         phi_context.at(phi_kernel_desc.kernelType.target));
     for (size_t index = 0; index < phi_kernel_desc.inputsType.size(); ++index) {
       mlir::Value input = kernel_op.getOperand(index);
-      auto cvt_tensor_type_op = builder.create<CvtTensorOp>(
+      auto cvt_tensor_type_op = builder.create<infrt::CvtTensorOp>(
           kernel_op.getLoc(),
-          DenseTensorType::get(kernel_op.getContext(),
-                               phi_kernel_desc.inputsType[index].target,
-                               phi_kernel_desc.inputsType[index].precision,
-                               phi_kernel_desc.inputsType[index].layout),
+          infrt::DenseTensorType::get(
+              kernel_op.getContext(),
+              phi_kernel_desc.inputsType[index].target,
+              phi_kernel_desc.inputsType[index].precision,
+              phi_kernel_desc.inputsType[index].layout),
           input);
       operation_state.addOperands(cvt_tensor_type_op.output());
     }
     for (size_t index = 0; index < phi_kernel_desc.outputsType.size();
          ++index) {
-      operation_state.addTypes(
-          DenseTensorType::get(kernel_op.getContext(),
-                               phi_kernel_desc.outputsType[index].target,
-                               phi_kernel_desc.outputsType[index].precision,
-                               phi_kernel_desc.outputsType[index].layout));
+      operation_state.addTypes(infrt::DenseTensorType::get(
+          kernel_op.getContext(),
+          phi_kernel_desc.outputsType[index].target,
+          phi_kernel_desc.outputsType[index].precision,
+          phi_kernel_desc.outputsType[index].layout));
     }
     operation_state.addAttributes(kernel_op.attrsAttr().getValue());
     mlir::Operation *phi_operation = builder.createOperation(operation_state);
     for (size_t index = 0; index < phi_kernel_desc.outputsType.size();
          ++index) {
       mlir::Value input = phi_operation->getResult(index);
-      auto cvt_tensor_type_op = builder.create<CvtTensorOp>(
+      auto cvt_tensor_type_op = builder.create<infrt::CvtTensorOp>(
           kernel_op.getLoc(), kernel_op.getResultTypes()[index], input);
       kernel_op.getResult(index).replaceAllUsesWith(
           cvt_tensor_type_op.output());
@@ -185,4 +203,10 @@ void phiOpCvtPass::diapatchStage() {
     kernel_op.erase();
   }
 }
-}  // namespace infrt
+
+}  // namespace
+
+std::unique_ptr<mlir::Pass> infrt::createPhiOpCvtPass(
+    std::vector<Place> valid_places) {
+  return std::make_unique<phiOpCvtPass>(valid_places);
+}

paddle/infrt/dialect/phi/pass/phi_op_cvt_pass.h

@@ -14,44 +14,14 @@
 
 #pragma once
 #include <mlir/Pass/Pass.h>
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 
 namespace infrt {
 /*
  * phiOpCvtPass.
- *
- * Convert the general operators in pd Dialect to a infrt.kernelOp.
- *
- * source func:
- *
- * func @main() -> tensor<?xf32> {
- *  %a = "pd.feed"()...
- *  %c = "pd.conv2d"(%a) ...
- *  %d = "pd.conv3d"(%c) ...
- *  %f = "pd.conv2d"(%a) ...
- *  "pd.fetch" (%d, %f)
- * }
- *
- * destination func:
- * func @main() -> tensor<?xf32> {
- *  %a = "pd.feed"()...
- *  %c = "infrt.kernel"(%a){name = "conv2d"} ...
- *  %d = "infrt.kernel"(%c){name = "conv3d"}...
- *  %f = "infrt.kernel"(%a){name = "conv2d"}...
- *  "pd.fetch" (%d, %f)
- * }
+ * Convert the general operators from pd Dialect to phi dialect.
  */
-class phiOpCvtPass
-    : public mlir::PassWrapper<phiOpCvtPass, mlir::FunctionPass> {
- public:
-  ::llvm::StringRef getName() const override { return "phiOpCvtPass"; }
-  void runOnFunction() override;
-  explicit phiOpCvtPass(std::vector<Place> valid_places = std::vector<Place>())
-      : valid_places_(valid_places) {}
+std::unique_ptr<mlir::Pass> createPhiOpCvtPass(
+    std::vector<Place> valid_places = std::vector<Place>());
 
- private:
-  void convertStage();
-  void diapatchStage();
-  std::vector<Place> valid_places_;
-};
 }  // namespace infrt

paddle/infrt/dialect/phi/phi_ir_exec.cc

@@ -38,7 +38,7 @@ int main(int argc, char** argv) {
   std::vector<infrt::Place> valid_places = {{infrt::TargetType::CPU,
                                              infrt::PrecisionType::FLOAT32,
                                              infrt::LayoutType::NCHW}};
-  phi_pass_manager.addPass(std::make_unique<infrt::phiOpCvtPass>(valid_places));
+  phi_pass_manager.addPass(infrt::createPhiOpCvtPass(valid_places));
   phi_pass_manager.addPass(infrt::createInfrtOpFusePass());
   if (mlir::failed(pm.run(*module))) {
     std::cout << "\npass failed!\n" << std::endl;

paddle/infrt/dialect/print_ir.cc

@@ -31,7 +31,7 @@
 #include <iostream>
 
 #include "paddle/infrt/common/global.h"
-#include "paddle/infrt/dialect/init_infrt_dialects.h"
+#include "paddle/infrt/dialect/init_dialects.h"
 
 namespace cl = llvm::cl;
 

paddle/infrt/dialect/rewrite.td

 #ifndef INFRT_REWRITE
 #define INFRT_REWRITE
 
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 include "paddle/infrt/dialect/pd_ops.td"
 include "paddle/infrt/dialect/pd_extra_ops.td"

paddle/infrt/dialect/tensor_shape.td

@@ -2,7 +2,7 @@
 #else
 #define INFRT_OPS
 
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "paddle/infrt/dialect/tensor_shape_base.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 

paddle/infrt/dialect/tensorrt/pd_lower_to_trt.td

@@ -2,7 +2,7 @@
 #define PD_LOWER_TO_TRT
 
 include "mlir/Interfaces/SideEffectInterfaces.td"
-include "paddle/infrt/dialect/infrt_base.td"
+include "paddle/infrt/dialect/infrt/ir/infrt_base.td"
 include "paddle/infrt/dialect/pd_ops.td"
 include "paddle/infrt/dialect/tensorrt/trt_ops.td"
 

paddle/infrt/dialect/tensorrt/trt_graph_fuse_pass.h

@@ -14,7 +14,6 @@
 
 #pragma once
 #include <mlir/Pass/Pass.h>
-#include "paddle/infrt/dialect/infrt_base.h"
 
 namespace infrt {
 namespace trt {
@@ -28,17 +27,17 @@ namespace trt {
  * func @main(%a : tensor<?xf32>) -> tensor<?xf32> {
  *  %c = "pd.graph"(%a) {
  *     %m = "pd.conv2d"(%a)...
- *     "infrt.return" (%m)
+ *     infrt.return %m...
  *  } ...
  *  %d = "pd.graph"(%c) {
  *      %m = "pd.conv3d"(%c)...
- *      "infrt.return" (%m)
+ *      infrt.return %m...
  *  } ...
  *  %f = "pd.graph"(%a) {
  *      %m = "pd.conv2d"(%a)...
- *      "infrt.return" (%m)
+ *      infrt.return %m...
  *  } ...
- *  "infrt.return" (%d, %f)..
+ *  infrt.return %d, %f :...
  * }
  *
  * destination func:
@@ -47,9 +46,9 @@ namespace trt {
  *     %m = "pd.conv2d"(%a)...
  *     %n = "pd.conv3d"(%m)...
  *     %s = "pd.conv2d"(%a)...
- *     "infrt.return" (%n, %s)
+ *     infrt.return %n, %s:...
  *  } ...
- *  "infrt.return" (%d, %f)
+ *  infrt.return %d, %f:...
  * }
  */
 class TRTGraphFusePass

paddle/infrt/dialect/tensorrt/trt_graph_split_pass.h

@@ -14,7 +14,6 @@
 
 #pragma once
 #include <mlir/Pass/Pass.h>
-#include "paddle/infrt/dialect/infrt_base.h"
 
 namespace infrt {
 namespace trt {
@@ -31,9 +30,9 @@ namespace trt {
  *     %m = "pd.conv2d"(%a)...
  *     %n = "pd.conv3d"(%m)...
  *     %s = "pd.conv2d"(%a)...
- *     "infrt.return" (%n, %s)...
+ *     infrt.return %n, %s : ...
  *  } ...
- *  "infrt.return" (%d, %f)...
+ *  infrt.return %d, %f : ...
  * }
  *
  * destination func:
@@ -41,7 +40,7 @@ namespace trt {
  *  %c = "pd.conv2d"(%a) ...
  *  %d = "pd.conv3d"(%c) ...
  *  %f = "pd.conv2d"(%a) ...
- *  "infrt.return" (%d, %f)...
+ *  infrt.return %d, %f:...
  * }
  */
 class TRTGraphSplitPass

paddle/infrt/dialect/tensorrt/trt_op_converter_pass.cc

@@ -14,7 +14,6 @@
 #include "paddle/infrt/dialect/tensorrt/trt_op_converter_pass.h"
 #include <mlir/IR/Builders.h>
 #include <mlir/Transforms/DialectConversion.h>
-#include "paddle/infrt/dialect/infrt_base.h"
 #include "paddle/infrt/dialect/pd_ops.h"
 #include "paddle/infrt/dialect/tensorrt/trt_dialect_types.h"
 
@@ -24,7 +23,7 @@ namespace trt {
 #include "paddle/infrt/dialect/tensorrt/pd_lower_to_trt.cpp.inc"  // NOLINT
 
 struct PD2TRT_GraphLower : public ::mlir::RewritePattern {
-  PD2TRT_GraphLower(::mlir::MLIRContext *context)
+  explicit PD2TRT_GraphLower(::mlir::MLIRContext *context)
       : ::mlir::RewritePattern("pd.graph", 1, context, {"trt.create_engine"}) {}
   ::mlir::LogicalResult matchAndRewrite(
       ::mlir::Operation *op, ::mlir::PatternRewriter &rewriter) const override {

paddle/infrt/dialect/tensorrt/trt_op_converter_pass.h

@@ -15,7 +15,7 @@
 #pragma once
 #include "mlir/IR/Dialect.h"
 #include "mlir/Pass/Pass.h"
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 #include "paddle/infrt/dialect/tensorrt/trt_ops.h"
 
 namespace infrt {
@@ -29,9 +29,9 @@ namespace trt {
  *     %m = "pd.conv2d"(%a)...
  *     %n = "pd.conv3d"(%m)...
  *     %s = "pd.conv2d"(%a)...
- *     "infrt.return" (%n, %s)...
+ *     infrt.return %n, %s:...
  *   } ...
- *   "infrt.return" (%d, %f)...
+ *   infrt.return %d, %f:...
  * }
  *
  * destination ir:
@@ -40,10 +40,10 @@ namespace trt {
  *     %m = "trt.Convolution"(%a)...
  *     %n = "trt.Convolution"(%m)...
  *     %s = "trt.Convolution"(%a)...
- *     "infrt.return" (%n, %s)...
+ *     infrt.return %n, %s :...
  *   }){run_once = true} ...
  *   %d, %f = "trt.execute"(%engine, %a)...
- *   "infrt.return" (%d, %f)...
+ *   infrt.return %d, %f :...
  * }
  */
 struct TRTOpConverterPass

paddle/infrt/dialect/tensorrt/trt_op_teller_pass.cc

@@ -15,8 +15,8 @@
 #include "paddle/infrt/dialect/tensorrt/trt_op_teller_pass.h"
 
 #include <mlir/IR/Builders.h>
-#include "paddle/infrt/dialect/basic_kernels.h"
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 #include "paddle/infrt/dialect/pd_ops.h"
 
 namespace infrt {

paddle/infrt/dialect/tensorrt/trt_op_teller_pass.h

@@ -14,7 +14,6 @@
 
 #pragma once
 #include <mlir/Pass/Pass.h>
-#include "paddle/infrt/dialect/infrt_base.h"
 
 namespace infrt {
 namespace trt {
@@ -29,24 +28,24 @@ namespace trt {
  *  %c = "pd.conv2d"(%a) ...
  *  %d = "pd.conv3d"(%c) ...
  *  %f = "pd.conv2d"(%a) ...
- *  "infrt.return"(%d, %f) ...
+ *  infrt.return %d, %f: ...
  * }
  *
  * destination func:
  * func @main(%a : tensor<?xf32>) -> tensor<?xf32> {
  *  %c = "pd.graph"(%a) {
  *     %m = "pd.conv2d"(%a)...
- *     "infrt.return" (%m)
+ *     infrt.return %m:...
  *  } ...
  *  %d = "pd.graph"(%c) {
  *      %m = "pd.conv3d"(%c)...
- *      "infrt.return" (%m)
+ *      infrt.return %m:...
  *  } ...
  *  %f = "pd.graph"(%a) {
  *      %m = "pd.conv2d"(%a)...
- *      "infrt.return" (%m)
+ *      infrt.return %m:...
  *  } ...
- *  "infrt.return" (%d, %f)
+ *  infrt.return %d, %f:...
  * }
  * TODO(winter-wang): Supplementary how to judge the operators can be supported
  * by tensorrt.

paddle/infrt/dialect/tensorrt/trt_ops.h

@@ -28,8 +28,8 @@
 #include <mlir/Interfaces/InferTypeOpInterface.h>
 #include <mlir/Interfaces/LoopLikeInterface.h>
 #include <mlir/Interfaces/SideEffectInterfaces.h>
-#include "paddle/infrt/dialect/basic_kernels.h"
-#include "paddle/infrt/dialect/infrt/infrt_dialect.h"
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.h"
+#include "paddle/infrt/dialect/infrt/ir/infrt_dialect.h"
 #include "paddle/infrt/dialect/pd_ops.h"
 
 namespace infrt {

paddle/infrt/external_kernels/basic.mlir

 // CHECK: basic
 func @basic() -> f32 {
-  %v0 = Infrt.constant.f32 1.0
-  %v1 = Infrt.constant.f32 2.0
+  %v0 = infrt.constant.f32 1.0
+  %v1 = infrt.constant.f32 2.0
   %v2 = "external.add.f32"(%v0, %v1) : (f32, f32) -> f32
 
   // CHECK: 1
@@ -17,5 +17,5 @@ func @basic() -> f32 {
   // CHECK: 6
   "external.print.f32"(%v3) : (f32) -> ()
 
-  Infrt.return %v3 : f32
+  infrt.return %v3 : f32
 }

paddle/infrt/external_kernels/fc.mlir

 // CHECK-LABEL: @fc
-func @fc(%input : !Infrt.tensor<X86, NCHW, F32>,
-         %w : !Infrt.tensor<X86, NCHW, F32>,
-         %bias : !Infrt.tensor<X86, NCHW, F32>) -> !Infrt.tensor<X86, NCHW, F32>
+func @fc(%input : !infrt.dense_tensor<CPU, FP32, NCHW>,
+         %w : !infrt.dense_tensor<CPU, FP32, NCHW>,
+         %bias : !infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
 {
-  %out = dt.create_uninit_tensor.f32 [30, 50] -> !Infrt.tensor<X86, NCHW, F32>
-  // dt.fill_tensor_with_constant.f32 (%out : !Infrt.tensor<X86, NCHW, F32>) {value=0.0:f32}
+  %out = dt.create_uninit_tensor.f32 [30, 50] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  // dt.fill_tensor_with_constant.f32 (%out : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=0.0:f32}
 
   // fc1
-  "external.matmul"(%input, %w, %out) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  "external.elementwise_add"(%out, %bias, %out) {axis = -1}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  "external.sigmoid"(%out, %out) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
+  "external.matmul"(%input, %w, %out) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  "external.elementwise_add"(%out, %bias, %out) {axis = -1}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  "external.sigmoid"(%out, %out) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
 
   // fc2
-  "external.matmul"(%out, %w, %out) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  "external.elementwise_add"(%out, %bias, %out) {axis = -1}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  "external.sigmoid"(%out, %out) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
+  "external.matmul"(%out, %w, %out) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  "external.elementwise_add"(%out, %bias, %out) {axis = -1}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  "external.sigmoid"(%out, %out) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
 
-  Infrt.return %out : !Infrt.tensor<X86, NCHW, F32>
+  infrt.return %out : !infrt.dense_tensor<CPU, FP32, NCHW>
 }
 
 // CHECK-LABEL: @benchmark
 func @benchmark() {
-  %input = dt.create_uninit_tensor.f32 [30, 50] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%input : !Infrt.tensor<X86, NCHW, F32>) {value=1.0:f32}
+  %input = dt.create_uninit_tensor.f32 [30, 50] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%input : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=1.0:f32}
 
-  %w = dt.create_uninit_tensor.f32 [50, 50] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%w : !Infrt.tensor<X86, NCHW, F32>) {value=2.0:f32}
+  %w = dt.create_uninit_tensor.f32 [50, 50] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%w : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=2.0:f32}
 
-  %bias = dt.create_uninit_tensor.f32 [30, 50] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%bias : !Infrt.tensor<X86, NCHW, F32>) {value=3.0:f32}
+  %bias = dt.create_uninit_tensor.f32 [30, 50] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%bias : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=3.0:f32}
 
-  Infrt.benchmark "add.f32"(
-          %input:!Infrt.tensor<X86, NCHW, F32>,
-          %w:!Infrt.tensor<X86, NCHW, F32>,
-          %bias:!Infrt.tensor<X86, NCHW, F32>)
+  infrt.benchmark "add.f32"(
+          %input:!infrt.dense_tensor<CPU, FP32, NCHW>,
+          %w:!infrt.dense_tensor<CPU, FP32, NCHW>,
+          %bias:!infrt.dense_tensor<CPU, FP32, NCHW>)
           duration_secs = 100, max_count = 300000, num_warmup_runs = 3
   {
-    %res = Infrt.call @fc(%input, %w, %bias) : (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> (!Infrt.tensor<X86, NCHW, F32>)
-    Infrt.return %res : !Infrt.tensor<X86, NCHW, F32>
+    %res = infrt.call @fc(%input, %w, %bias) : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+    infrt.return %res : !infrt.dense_tensor<CPU, FP32, NCHW>
   }
-  Infrt.return
+  infrt.return
 }

paddle/infrt/external_kernels/paddle.mlir

 // CHECK: paddle_func
 func @paddle_func() -> () {
-  %input = dt.create_uninit_tensor.f32 [3, 5] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%input : !Infrt.tensor<X86, NCHW, F32>) {value=1.0:f32}
+  %input = dt.create_uninit_tensor.f32 [3, 5] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%input : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=1.0:f32}
 
-  %w = dt.create_uninit_tensor.f32 [5, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%w : !Infrt.tensor<X86, NCHW, F32>) {value=2.0:f32}
+  %w = dt.create_uninit_tensor.f32 [5, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%w : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=2.0:f32}
 
-  %bias = dt.create_uninit_tensor.f32 [4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%bias : !Infrt.tensor<X86, NCHW, F32>) {value=3.0:f32}
+  %bias = dt.create_uninit_tensor.f32 [4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%bias : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=3.0:f32}
 
-  %out = dt.create_uninit_tensor.f32 [3, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%out : !Infrt.tensor<X86, NCHW, F32>) {value=0.0:f32}
+  %out = dt.create_uninit_tensor.f32 [3, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%out : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=0.0:f32}
 
-  "external.fc2"(%input, %w, %bias, %out) {in_num_col_dims=3:i32, test_attr=5:i32}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
+  "external.fc2"(%input, %w, %bias, %out) {in_num_col_dims=3:i32, test_attr=5:i32}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
   // CHECK-LABEL: tensor: shape=shape[3,5], values=[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
-  dt.print_tensor (%input : !Infrt.tensor<X86, NCHW, F32>)
+  dt.print_tensor (%input : !infrt.dense_tensor<CPU, FP32, NCHW>)
   // CHECK-LABEL: tensor: shape=shape[5,4], values=[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]
-  dt.print_tensor (%w : !Infrt.tensor<X86, NCHW, F32>)
-  dt.print_tensor (%bias : !Infrt.tensor<X86, NCHW, F32>)
-  dt.print_tensor (%out : !Infrt.tensor<X86, NCHW, F32>)
+  dt.print_tensor (%w : !infrt.dense_tensor<CPU, FP32, NCHW>)
+  dt.print_tensor (%bias : !infrt.dense_tensor<CPU, FP32, NCHW>)
+  dt.print_tensor (%out : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
   // test external.matmul
-  %out1 = dt.create_uninit_tensor.f32 [3, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%out1 : !Infrt.tensor<X86, NCHW, F32>) {value=0.0:f32}
-  "external.matmul"(%input, %w, %out1) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  dt.print_tensor (%out1 : !Infrt.tensor<X86, NCHW, F32>)
+  %out1 = dt.create_uninit_tensor.f32 [3, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%out1 : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=0.0:f32}
+  "external.matmul"(%input, %w, %out1) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  dt.print_tensor (%out1 : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
   // test external.elementwise_add
-  %out2 = dt.create_uninit_tensor.f32 [3, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%out2 : !Infrt.tensor<X86, NCHW, F32>) {value=0.0:f32}
-  %bias1 = dt.create_uninit_tensor.f32 [3, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%bias1 : !Infrt.tensor<X86, NCHW, F32>) {value=3.0:f32}
-  "external.elementwise_add"(%out1, %bias1, %out2) {axis=-1}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  dt.print_tensor (%out2 : !Infrt.tensor<X86, NCHW, F32>)
+  %out2 = dt.create_uninit_tensor.f32 [3, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%out2 : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=0.0:f32}
+  %bias1 = dt.create_uninit_tensor.f32 [3, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%bias1 : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=3.0:f32}
+  "external.elementwise_add"(%out1, %bias1, %out2) {axis=-1}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  dt.print_tensor (%out2 : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
   // test external.relu
-  %out3 = dt.create_uninit_tensor.f32 [3, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%out3 : !Infrt.tensor<X86, NCHW, F32>) {value=0.0:f32}
-  "external.relu"(%out1, %out3) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  dt.print_tensor (%out3 : !Infrt.tensor<X86, NCHW, F32>)
+  %out3 = dt.create_uninit_tensor.f32 [3, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%out3 : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=0.0:f32}
+  "external.relu"(%out1, %out3) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  dt.print_tensor (%out3 : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
   // test external.sigmoid
-  %out4 = dt.create_uninit_tensor.f32 [3, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%out4 : !Infrt.tensor<X86, NCHW, F32>) {value=0.0:f32}
-  "external.sigmoid"(%out1, %out4) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  dt.print_tensor (%out4 : !Infrt.tensor<X86, NCHW, F32>)
+  %out4 = dt.create_uninit_tensor.f32 [3, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%out4 : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=0.0:f32}
+  "external.sigmoid"(%out1, %out4) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  dt.print_tensor (%out4 : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }

paddle/infrt/host_context/mlir_exec.cc

@@ -92,7 +92,7 @@ int main(int argc, char** argv) {
   std::vector<infrt::Place> valid_places = {{infrt::TargetType::CPU,
                                              infrt::PrecisionType::FLOAT32,
                                              infrt::LayoutType::NCHW}};
-  phi_pass_manager.addPass(std::make_unique<infrt::phiOpCvtPass>(valid_places));
+  phi_pass_manager.addPass(infrt::createPhiOpCvtPass(valid_places));
   phi_pass_manager.addPass(infrt::createInfrtOpFusePass());
 #endif
 

paddle/infrt/host_context/mlir_tests/basic.mlir

 // CHECK-LABEL: basic
 func @basic() -> f32 {
-  %v0 = Infrt.constant.f32 1.0
-  %v1 = Infrt.constant.f32 2.0
-  %v2 = "Infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
+  %v0 = infrt.constant.f32 1.0
+  %v1 = infrt.constant.f32 2.0
+  %v2 = "infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
 
   // CHECK: 1
-  "Infrt.print.f32"(%v0) : (f32) -> ()
+  "infrt.print.f32"(%v0) : (f32) -> ()
   // CHECK: 2
-  "Infrt.print.f32"(%v1) : (f32) -> ()
+  "infrt.print.f32"(%v1) : (f32) -> ()
 
   // CHECK: 3
-  "Infrt.print.f32"(%v2) : (f32) -> ()
+  "infrt.print.f32"(%v2) : (f32) -> ()
 
-  %v3 = "Infrt.mul.f32"(%v2, %v1) : (f32, f32) -> f32
+  %v3 = "infrt.mul.f32"(%v2, %v1) : (f32, f32) -> f32
 
   // CHECK: 6
-  "Infrt.print.f32"(%v3) : (f32) -> ()
+  "infrt.print.f32"(%v3) : (f32) -> ()
 
-  Infrt.return %v3 : f32
+  infrt.return %v3 : f32
 }
 
 // CHECK-LABEL: basic1
 // Check the mlir executor can work with more than one function in a file.
 func @basic1() -> () {
-  %v0 = Infrt.constant.f32 1.0
-  "Infrt.print.f32"(%v0) : (f32) -> ()
+  %v0 = infrt.constant.f32 1.0
+  "infrt.print.f32"(%v0) : (f32) -> ()
   // CHECK: 1
-  Infrt.return
+  infrt.return
 }
\ No newline at end of file

paddle/infrt/host_context/mlir_tests/dense_tensor.mlir

 // CHECK-LABEL: build_tensor1
 func @build_tensor1() {
-  %a = dt.create_uninit_tensor.f32 [3, 4] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%a : !Infrt.tensor<X86, NCHW, F32>) {value=1.0:f32}
+  %a = dt.create_uninit_tensor.f32 [3, 4] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%a : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=1.0:f32}
   // CHECK: tensor: shape=shape[3,4], values=[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
-  dt.print_tensor (%a : !Infrt.tensor<X86, NCHW, F32>)
+  dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }

paddle/infrt/host_context/mlir_tests/shape.mlir

@@ -3,5 +3,5 @@ func @build_tensor1() {
   %a = ts.build_shape [1:i64, 57:i64, 92:i64]
   // CHECK: shape[1,57,92]
   ts.print_shape %a
-  Infrt.return
-}
+  infrt.return
+}
\ No newline at end of file

paddle/infrt/host_context/mlir_to_runtime_translate.cc

@@ -75,7 +75,7 @@ struct MlirToRuntimeTranslator::Impl {
 };
 
 bool MlirToRuntimeTranslator::EmitConstantOp(mlir::Operation* op) {
-  if (!infrt::Startswith(op->getName().getStringRef().str(), "Infrt.constant"))
+  if (!infrt::Startswith(op->getName().getStringRef().str(), "infrt.constant"))
     return false;
   VLOG(3) << "Emitting constant op [" << op->getName().getStringRef().str()
           << "]";
@@ -267,7 +267,7 @@ boost::optional<std::vector<double>> MlirToRuntimeTranslator::EmitAttribute(
 }
 
 static bool IsReturn(mlir::Operation* op) {
-  return op->getName().getStringRef() == "Infrt.return";
+  return op->getName().getStringRef() == "infrt.return";
 }
 
 bool MlirToRuntimeTranslator::EmitGeneralOp(mlir::Operation* op) {
@@ -405,7 +405,7 @@ bool MlirToRuntimeTranslator::EmitGeneralOp(mlir::Operation* op) {
 bool MlirToRuntimeTranslator::EmitReturnOp(
     mlir::Operation* op, llvm::SmallVectorImpl<mlir::Value>* results) {
   CHECK(results);
-  if (op->getName().getStringRef() == "Infrt.return") {
+  if (op->getName().getStringRef() == "infrt.return") {
     for (size_t i = 0; i < op->getNumOperands(); i++) {
       results->push_back(op->getOperand(i));
     }
@@ -478,7 +478,7 @@ bool MlirToRuntimeTranslator::EmitCallOp(mlir::Operation* op,
                                          function_defs_t* function_table) {
   CHECK(op);
   CHECK(function_table);
-  if (op->getName().getStringRef() != "Infrt.call") return false;
+  if (op->getName().getStringRef() != "infrt.call") return false;
 
   impl_->cur_op =
       impl_->runtime->NewOpExecutable(op->getName().getStringRef().str());

paddle/infrt/host_context/mlir_to_runtime_translate.h

@@ -57,7 +57,7 @@ class MlirToRuntimeTranslator {
  protected:
   //! Emit a "infrt.constant.*" operation, return true if succeed.
   bool EmitConstantOp(mlir::Operation* op);
-  //! Emit a "Infrt.return" operation.
+  //! Emit a "infrt.return" operation.
   bool EmitReturnOp(mlir::Operation* op,
                     llvm::SmallVectorImpl<mlir::Value>* results);
   //! Emit a "ts.build_shape" operation.

paddle/infrt/host_context/mlir_to_runtime_translate_test.cc

@@ -37,14 +37,14 @@ TEST(MlirToRuntimeTranslate, basic) {
 
   auto source = R"ROC(
 func @main() -> () {
-  %v0 = Infrt.constant.f32 1.0
-  %v1 = Infrt.constant.f32 2.0
-  %v2 = "Infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
-  %v3 = "Infrt.mul.f32"(%v2, %v1) : (f32, f32) -> f32
+  %v0 = infrt.constant.f32 1.0
+  %v1 = infrt.constant.f32 2.0
+  %v2 = "infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
+  %v3 = "infrt.mul.f32"(%v2, %v1) : (f32, f32) -> f32
 
-  "Infrt.print.f32"(%v1) : (f32) -> ()
+  "infrt.print.f32"(%v1) : (f32) -> ()
 
-  Infrt.return
+  infrt.return
 }
 )ROC";
 
@@ -63,14 +63,14 @@ TEST(TestMlir, basic) {
 
   auto source = R"ROC(
 func @main() -> () {
-  %v0 = Infrt.constant.f32 1.0
-  %v1 = Infrt.constant.f32 2.0
-  %v2 = "Infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
-  %v3 = "Infrt.mul.f32"(%v2, %v1) : (f32, f32) -> f32
+  %v0 = infrt.constant.f32 1.0
+  %v1 = infrt.constant.f32 2.0
+  %v2 = "infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
+  %v3 = "infrt.mul.f32"(%v2, %v1) : (f32, f32) -> f32
 
-  "Infrt.print.f32"(%v1) : (f32) -> ()
+  "infrt.print.f32"(%v1) : (f32) -> ()
 
-  Infrt.return
+  infrt.return
 }
 )ROC";
 
@@ -101,7 +101,7 @@ func @predict(%a: !infrt.dense_tensor<CPU, FP32, NCHW>, %b: !infrt.dense_tensor<
       "!infrt.dense_tensor<CPU, FP32, NCHW>";
 
   auto end = R"ROC(
-Infrt.return %a0, %b0: !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>
+infrt.return %a0, %b0: !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>
 }
   )ROC";
 

paddle/infrt/host_context/paddle_mlir.cc

@@ -19,7 +19,6 @@ MLIRModelGenImpl::MLIRModelGenImpl()
     : context_(infrt::Global::getMLIRContext()), builder_(context_) {
   context_->allowUnregisteredDialects();
   context_->getOrLoadDialect<mlir::StandardOpsDialect>();
-  context_->getOrLoadDialect<infrt::dialect::INFRTDialect>();
   context_->getOrLoadDialect<infrt::ts::TensorShapeDialect>();
   context_->getOrLoadDialect<infrt::dt::DTDialect>();
   context_->getOrLoadDialect<mlir::pd::PaddleDialect>();

paddle/infrt/host_context/paddle_mlir.h

@@ -25,10 +25,10 @@
 #include "mlir/IR/MLIRContext.h"
 #include "paddle/infrt/common/global.h"
 #include "paddle/infrt/common/string.h"
-#include "paddle/infrt/dialect/basic_kernels.h"
 #include "paddle/infrt/dialect/dense_tensor.h"
-#include "paddle/infrt/dialect/infrt_base.h"
-#include "paddle/infrt/dialect/init_infrt_dialects.h"
+#include "paddle/infrt/dialect/infrt/ir/basic_kernels.h"
+
+#include "paddle/infrt/dialect/init_dialects.h"
 #include "paddle/infrt/dialect/pd_ops.h"
 #include "paddle/infrt/dialect/tensor_shape.h"
 #include "paddle/infrt/paddle/model_parser.h"

paddle/infrt/host_context/value.h

@@ -22,7 +22,7 @@
 
 #include "paddle/infrt/common/object.h"
 #include "paddle/infrt/common/shared.h"
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 #include "paddle/infrt/host_context/function.h"
 #include "paddle/infrt/support/variant.h"
 #include "paddle/infrt/tensor/dense_host_tensor.h"

paddle/infrt/kernel/basic_kernels.cc

@@ -63,24 +63,24 @@ static void PrintString(const std::string &str) {
 void RegisterBasicKernels(host_context::KernelRegistry *registry) {
   RegisterIntBasicKernels(registry);
   RegisterFloatBasicKernels(registry);
-  registry->AddKernel("Infrt.get_string", INFRT_KERNEL(GetString));
-  registry->AddKernel("Infrt.print_string", INFRT_KERNEL(PrintString));
+  registry->AddKernel("infrt.get_string", INFRT_KERNEL(GetString));
+  registry->AddKernel("infrt.print_string", INFRT_KERNEL(PrintString));
 }
 
 void RegisterIntBasicKernels(host_context::KernelRegistry *registry) {
-  registry->AddKernel("Infrt.add.i32", INFRT_KERNEL(add<int32_t>));
-  registry->AddKernel("Infrt.sub.i32", INFRT_KERNEL(sub<int32_t>));
-  registry->AddKernel("Infrt.mul.i32", INFRT_KERNEL(mul<int32_t>));
-  registry->AddKernel("Infrt.div.i32", INFRT_KERNEL(div<int32_t>));
-  registry->AddKernel("Infrt.print.i32", INFRT_KERNEL(print<int32_t>));
+  registry->AddKernel("infrt.add.i32", INFRT_KERNEL(add<int32_t>));
+  registry->AddKernel("infrt.sub.i32", INFRT_KERNEL(sub<int32_t>));
+  registry->AddKernel("infrt.mul.i32", INFRT_KERNEL(mul<int32_t>));
+  registry->AddKernel("infrt.div.i32", INFRT_KERNEL(div<int32_t>));
+  registry->AddKernel("infrt.print.i32", INFRT_KERNEL(print<int32_t>));
 }
 
 void RegisterFloatBasicKernels(host_context::KernelRegistry *registry) {
-  registry->AddKernel("Infrt.add.f32", INFRT_KERNEL(add<float>));
-  registry->AddKernel("Infrt.sub.f32", INFRT_KERNEL(sub<float>));
-  registry->AddKernel("Infrt.mul.f32", INFRT_KERNEL(mul<float>));
-  registry->AddKernel("Infrt.div.f32", INFRT_KERNEL(div<float>));
-  registry->AddKernel("Infrt.print.f32", INFRT_KERNEL(print<float>));
+  registry->AddKernel("infrt.add.f32", INFRT_KERNEL(add<float>));
+  registry->AddKernel("infrt.sub.f32", INFRT_KERNEL(sub<float>));
+  registry->AddKernel("infrt.mul.f32", INFRT_KERNEL(mul<float>));
+  registry->AddKernel("infrt.div.f32", INFRT_KERNEL(div<float>));
+  registry->AddKernel("infrt.print.f32", INFRT_KERNEL(print<float>));
 }
 
 }  // namespace kernel

paddle/infrt/kernel/control_flow_kernels.cc

@@ -37,7 +37,7 @@ static void INFRTCall(
 }
 
 void RegisterControlFlowKernels(host_context::KernelRegistry* registry) {
-  registry->AddKernel("Infrt.call", INFRT_KERNEL(INFRTCall));
+  registry->AddKernel("infrt.call", INFRT_KERNEL(INFRTCall));
 }
 
 }  // namespace kernel

paddle/infrt/kernel/phi/dense_tensor_kernels.h

@@ -15,7 +15,7 @@
 #pragma once
 
 #include "paddle/infrt/backends/host/phi_allocator.h"
-#include "paddle/infrt/dialect/infrt/common_type.h"
+#include "paddle/infrt/dialect/infrt/common/types.h"
 #include "paddle/infrt/host_context/kernel_utils.h"
 #include "paddle/phi/core/dense_tensor.h"
 

paddle/infrt/kernel/test_kernels.cc

@@ -193,7 +193,7 @@ tensor::DenseHostTensor ShadowCopyTensor(tensor::DenseHostTensor src) {
 }
 
 void RegisterTestKernels(host_context::KernelRegistry *registry) {
-  registry->AddKernel("Infrt.benchmark", INFRT_KERNEL(benchmark));
+  registry->AddKernel("infrt.benchmark", INFRT_KERNEL(benchmark));
   registry->AddKernel("Infrt.test.shadow_copy_tensor",
                       INFRT_KERNEL(ShadowCopyTensor));
 }

paddle/infrt/tests/dialect/basic.mlir

 // RUN: infrtexec -i %s | FileCheck %s
 // CHECK-LABEL: @basic_f32
 func @basic_f32() -> f32 {
-  %v0 = Infrt.constant.f32 1.0
-  %v1 = Infrt.constant.f32 2.0
-  %value = "Infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
+  %v0 = infrt.constant.f32 1.0
+  %v1 = infrt.constant.f32 2.0
+  %value = "infrt.add.f32"(%v0, %v1) : (f32, f32) -> f32
 
   // CHECK-NEXT: 3
-  "Infrt.print.f32"(%value) : (f32) -> ()
+  "infrt.print.f32"(%value) : (f32) -> ()
 
-  Infrt.return %value : f32
+  infrt.return %value : f32
 }
 
 /// ================================================================
 /// @caller call the other function @callee
 func @callee.add.f32(%x : f32, %y : f32, %y1 : f32) -> f32 {
-  %z = "Infrt.add.f32"(%x, %y) : (f32, f32) -> f32
-  %z1 = "Infrt.add.f32"(%z, %y1) : (f32, f32) -> f32
-  Infrt.return %z1 : f32
+  %z = "infrt.add.f32"(%x, %y) : (f32, f32) -> f32
+  %z1 = "infrt.add.f32"(%z, %y1) : (f32, f32) -> f32
+  infrt.return %z1 : f32
 }
 
 // CHECK-LABEL: @caller.add.f32
 func @caller.add.f32() -> f32 {
-  %x = Infrt.constant.f32 1.0
-  %y = Infrt.constant.f32 2.0
-  %y1 = Infrt.constant.f32 3.0
-  %z = Infrt.call @callee.add.f32(%x, %y, %y1) : (f32, f32, f32) -> f32
+  %x = infrt.constant.f32 1.0
+  %y = infrt.constant.f32 2.0
+  %y1 = infrt.constant.f32 3.0
+  %z = infrt.call @callee.add.f32(%x, %y, %y1) : (f32, f32, f32) -> f32
 
   // CHECK-NEXT: 6
-  "Infrt.print.f32"(%z) : (f32) -> ()
-  Infrt.return %z : f32
+  "infrt.print.f32"(%z) : (f32) -> ()
+  infrt.return %z : f32
 }
 /// <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<

paddle/infrt/tests/dialect/benchmark.mlir

@@ -12,13 +12,13 @@ func @benchmark() {
   // CHECK-LABEL: BM:add.f32:CPU 95%(ns)
   // CHECK-LABEL: BM:add.f32:CPU 99%(ns)
   // CHECK-LABEL: BM:add.f32:CPU utilization(percent)
-  Infrt.benchmark "add.f32"() duration_secs = 1, max_count = 3, num_warmup_runs = 3
+  infrt.benchmark "add.f32"() duration_secs = 1, max_count = 3, num_warmup_runs = 3
   {
-    %0 = Infrt.constant.f32 1.0
-    %1 = Infrt.constant.f32 2.0
-    %res = "Infrt.add.f32"(%0, %1) : (f32, f32) -> f32
-    "Infrt.print.f32"(%res) : (f32) -> ()
-    Infrt.return %res : f32
+    %0 = infrt.constant.f32 1.0
+    %1 = infrt.constant.f32 2.0
+    %res = "infrt.add.f32"(%0, %1) : (f32, f32) -> f32
+    "infrt.print.f32"(%res) : (f32) -> ()
+    infrt.return %res : f32
   }
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/dense_tensor.mlir

@@ -4,14 +4,14 @@ func @dense_shape0() {
   %shape = ts.build_shape [1:i64, 57:i64]
   %a = dt.create_uninit_tensor.f32 [12:i64, 23:i64] -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
-  Infrt.return
+  infrt.return
 }
 
 func @predict(%a: !infrt.dense_tensor<CPU, FP32, NCHW>, %b: !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) {
   %a0 = dt.shallow_copy_tensor %a : !infrt.dense_tensor<CPU, FP32, NCHW> -> !infrt.dense_tensor<CPU, FP32, NCHW>
   %b0 = dt.shallow_copy_tensor %b : !infrt.dense_tensor<CPU, FP32, NCHW> -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
-  Infrt.return %a0, %b0: !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>
+  infrt.return %a0, %b0: !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>
 }
 
 
@@ -19,6 +19,6 @@ func @main() {
   %shape = ts.build_shape [1:i64, 57:i64]
   %a = dt.create_uninit_tensor.f32 [12:i64, 23:i64] -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
-  %b, %c = Infrt.call @predict(%a, %a) : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>)
-  Infrt.return
+  %b, %c = infrt.call @predict(%a, %a) : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>)
+  infrt.return
 }

paddle/infrt/tests/dialect/disabled_tensor_map.mlir

 // CHECK-LABEL: @predict
-func @predict(%input:!Infrt.tensor<X86, NCHW, F32>, %map: !Infrt.tensor_map) -> (!Infrt.tensor<X86, NCHW, F32>) {
-  %w = dt.get_param(%map, "create_parameter_0.w_0") -> !Infrt.tensor<X86, NCHW, F32>
-  %bias = dt.get_param(%map, "create_parameter_1.w_0") -> !Infrt.tensor<X86, NCHW, F32>
+func @predict(%input:!infrt.dense_tensor<CPU, FP32, NCHW>, %map: !infrt.dense_tensor_map) -> (!infrt.dense_tensor<CPU, FP32, NCHW>) {
+  %w = dt.get_param(%map, "create_parameter_0.w_0") -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  %bias = dt.get_param(%map, "create_parameter_1.w_0") -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
-  %out = dt.create_uninit_tensor.f32 [3, 3] -> !Infrt.tensor<X86, NCHW, F32>
+  %out = dt.create_uninit_tensor.f32 [3, 3] -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
   // fc
-  "external.matmul"(%input, %w, %out) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  "external.elementwise_add"(%out, %bias, %out) {axis = -1}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  "external.sigmoid"(%out, %out) {}: (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor<X86, NCHW, F32>) -> ()
-  //dt.print_tensor (%out : !Infrt.tensor<X86, NCHW, F32>)
+  "external.matmul"(%input, %w, %out) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  "external.elementwise_add"(%out, %bias, %out) {axis = -1}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  "external.sigmoid"(%out, %out) {}: (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
+  //dt.print_tensor (%out : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return %out : !Infrt.tensor<X86, NCHW, F32>
+  infrt.return %out : !infrt.dense_tensor<CPU, FP32, NCHW>
 }
 
 // CHECK-LABEL: @main
 func @main() {
-  %input = dt.create_uninit_tensor.f32 [3, 3] -> !Infrt.tensor<X86, NCHW, F32>
-  dt.fill_tensor_with_constant.f32 (%input : !Infrt.tensor<X86, NCHW, F32>) {value=1.0:f32}
+  %input = dt.create_uninit_tensor.f32 [3, 3] -> !infrt.dense_tensor<CPU, FP32, NCHW>
+  dt.fill_tensor_with_constant.f32 (%input : !infrt.dense_tensor<CPU, FP32, NCHW>) {value=1.0:f32}
 
   // CHECK-LABEL: loading params
   %map = dt.load_params() {path="/Infrt/build/paddle/paddle_1.8_fc_model"}
 
-  %out = Infrt.call @predict(%input, %map): (!Infrt.tensor<X86, NCHW, F32>, !Infrt.tensor_map) -> (!Infrt.tensor<X86, NCHW, F32>)
-  dt.print_tensor (%out : !Infrt.tensor<X86, NCHW, F32>)
+  %out = infrt.call @predict(%input, %map): (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor_map) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
+  dt.print_tensor (%out : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }
 

paddle/infrt/tests/dialect/paddle_ops.mlir

@@ -5,5 +5,5 @@ func @ops() {
   %b = pd.feed() {name="input1"}: tensor<?xf32>
   %d = pd.feed() {name="input3"}: !infrt.lod_tensor<3x4x9xf32, 0>
   %c = "pd.matmul"(%a, %b) {transpose_x=true, transpose_y=false} : (tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32>
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/phi/dense_tensor.mlir

@@ -11,6 +11,6 @@ func @sign_any_float32_execute() {
 
   // CHECK: dense_tensor: shape=shape[1], values=[1]
   "phi_dt.print_tensor" (%e) : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
-  Infrt.return
+  infrt.return
 }
 

paddle/infrt/tests/dialect/phi/phi_test.mlir

@@ -2,14 +2,14 @@
 module  {
   func @predict(%arg0: !infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW> {
     %2 = "pd.abs"(%arg0) : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
-    Infrt.return %2 : !infrt.dense_tensor<CPU, FP32, NCHW>
+    infrt.return %2 : !infrt.dense_tensor<CPU, FP32, NCHW>
   }
   func @main() {
     %ctx = "phi_dt.create_context.cpu" (): () -> !phi.context<CPU>
     %t = "phi_dt.create_dense_tensor" (%ctx) {precision=#infrt.precision<FP32>, layout=#infrt.layout<NCHW>, lod=[1:i64], dims=[1:i64]}: (!phi.context<CPU>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>)
     "phi_dt.fill_dense_tensor.f32"(%t) {value=[3.8:f32]} : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> ()
-    %2 = Infrt.call@predict(%t) : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
+    %2 = infrt.call@predict(%t) : (!infrt.dense_tensor<CPU, FP32, NCHW>) -> !infrt.dense_tensor<CPU, FP32, NCHW>
     phi_dt.print_tensor(%2 : !infrt.dense_tensor<CPU, FP32, NCHW>)
-    Infrt.return
+    infrt.return
   }
 }

paddle/infrt/tests/dialect/tensor/dense_tensor.mlir

@@ -3,14 +3,14 @@
 func @dense_shape0() {
   %a = dt.create_uninit_tensor.f32 [12:i64, 23:i64] -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
-  Infrt.return
+  infrt.return
 }
 
 func @predict(%a: !infrt.dense_tensor<CPU, FP32, NCHW>, %b: !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) {
   %a0 = dt.shallow_copy_tensor %a : !infrt.dense_tensor<CPU, FP32, NCHW> -> !infrt.dense_tensor<CPU, FP32, NCHW>
   %b0 = dt.shallow_copy_tensor %b : !infrt.dense_tensor<CPU, FP32, NCHW> -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
-  Infrt.return %a0, %b0: !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>
+  infrt.return %a0, %b0: !infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>
 }
 
 
@@ -18,6 +18,6 @@ func @main() {
   %shape = ts.build_shape [1:i64, 57:i64]
   %a = dt.create_uninit_tensor.f32 [12:i64, 23:i64] -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
-  %b, %c = Infrt.call @predict(%a, %a) : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>)
-  Infrt.return
+  %b, %c = infrt.call @predict(%a, %a) : (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>) -> (!infrt.dense_tensor<CPU, FP32, NCHW>, !infrt.dense_tensor<CPU, FP32, NCHW>)
+  infrt.return
 }

paddle/infrt/tests/dialect/tensor/naive_kernels.mlir

@@ -13,7 +13,7 @@ func @naive_elementwise_add() {
   // CHECK: tensor: shape=shape[2,8], values=[3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]
   dt.print_tensor (%c : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }
 
 // RUN: infrtexec -i %s | FileCheck %s
@@ -31,5 +31,5 @@ func @naive_matmul() {
   // CHECK: tensor: shape=shape[2,4], values=[16, 16, 16, 16, 16, 16, 16, 16]
   dt.print_tensor (%c : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/tensor/tensor_map.mlir.in

@@ -3,12 +3,12 @@
 func @load_tensor_map() {
   %map = dt.load_params(){path="@CMAKE_BINARY_DIR@/multi_fc_model"}
   %size = dt.tensor_map_get_size(%map) -> i32
-  Infrt.print.i32 %size
+  infrt.print.i32 %size
 
   %a = dt.tensor_map_get_tensor(%map) {name="fc_bias"} -> !infrt.dense_tensor<CPU, FP32, NCHW>
 
   // CHECK: tensor: shape=shape[2], values=[0, 0]
   dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/tensor/tensor_shape.mlir

@@ -4,5 +4,5 @@ func @build_tensor1() {
   %a = ts.build_shape [1:i64, 57:i64, 92:i64]
   // CHECK: shape[1,57,92]
   ts.print_shape %a
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/tensor/tensor_type.mlir

@@ -6,5 +6,5 @@ func @test_tensor_type() {
   // CHECK: tensor: shape=shape[3,4], values=[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
   dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/tensor_shape.mlir

@@ -4,5 +4,5 @@ func @build_tensor1() {
   %a = ts.build_shape [1:i64, 57:i64, 92:i64]
   // CHECK: shape[1,57,92]
   ts.print_shape %a
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/tensor_type.mlir

@@ -6,5 +6,5 @@ func @test_tensor_type() {
   // CHECK: tensor: shape=shape[3,4], values=[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
   dt.print_tensor (%a : !infrt.dense_tensor<CPU, FP32, NCHW>)
 
-  Infrt.return
+  infrt.return
 }

paddle/infrt/tests/dialect/trt_ops.mlir

@@ -12,5 +12,5 @@ func @main(%bias:tensor<?xf32>, %c:tensor<?xf32>, %b1:tensor<?xf32>, %b2:tensor<
   %d2 = "pd.elementwise_add"(%c2, %bias2) {axis=-1:si32} : (tensor<?xf32>, tensor<?xf32>) -> tensor<?xf32>
   %e2 = "pd.relu"(%d2) {} : (tensor<?xf32>) -> tensor<?xf32>
   
-  "infrt.return"(%e2) : (tensor<?xf32>)->()
+  infrt.return %e2 : tensor<?xf32>
 }