Revert "Support attribute promotion."

This reverts commit 955968b750.

src/CMakeLists.txt

@@ -12,10 +12,7 @@ add_library(compiler
         pass/onnx_combine.cpp
         pass/onnx_rewrite.cpp
         pass/onnx_decompose.cpp
-        pass/passes.hpp
+        pass/passes.hpp)
-        dialect/onnx/const_operands_interface.hpp
-        dialect/onnx/attribute_promotion.cpp
-        )
 
 # Include root src directory.
 target_include_directories(compiler PRIVATE ${ONNF_SRC_ROOT})
@@ -50,18 +47,12 @@ onnf_tablegen(onnx_rewrite.inc -gen-rewriters)
 add_public_tablegen_target(gen_onnx_rewrite)
 add_dependencies(compiler gen_onnx_rewrite)
 
-add_subdirectory(dialect/onnx)
-
 set(LLVM_TARGET_DEFINITIONS dialect/onnx/onnx.td)
 onnf_tablegen(onnx.hpp.inc -gen-op-decls "-I${CMAKE_SOURCE_DIR}/compiler/pass")
 onnf_tablegen(onnx.cpp.inc -gen-op-defs "-I${CMAKE_SOURCE_DIR}/compiler/pass")
 set(GEN_DOC_FILE ${CMAKE_BINARY_DIR}/docs/Dialects/onnx.md)
 add_public_tablegen_target(gen_onnx)
-
-add_dependencies(gen_onnx gen_shape_inference)
-add_dependencies(gen_onnx gen_const_operands_interface)
 add_dependencies(compiler gen_onnx)
-
 add_onnf_dialect_doc(onnx dialect/onnx/onnx.td)
 
 set(LLVM_TARGET_DEFINITIONS dialect/krnl/krnl_ops.td)
@@ -75,7 +66,7 @@ target_include_directories(onnf_onnx_decompose
         PRIVATE ${ONNF_SRC_ROOT} ${ONNF_BIN_ROOT}
         ${ONNF_SRC_ROOT})
 target_link_libraries(onnf_onnx_decompose ${MLIRLibs})
-add_dependencies(onnf_onnx_decompose gen_onnx)
+add_dependencies(onnf_onnx_decompose gen_krnl_ops)
 
 add_library(onnf_shape_inference pass/shape_inference_pass.cpp)
 target_include_directories(onnf_shape_inference

src/dialect/onnx/CMakeLists.txt

@@ -1,11 +0,0 @@
-#add_library(onnf_fold_const_operand_to_attribute fold_const_operand_to_attribute.hpp)
-#target_include_directories(onnf_fold_const_operand_to_attribute
-#        PRIVATE ${ONNF_SRC_ROOT} ${ONNF_BIN_ROOT})
-#target_link_libraries(onnf_fold_const_operand_to_attribute ${MLIRLibs})
-
-set(LLVM_TARGET_DEFINITIONS const_operands_interface.td)
-onnf_tablegen(const_operands_interface.hpp.inc -gen-op-interface-decls)
-onnf_tablegen(const_operands_interface.cpp.inc -gen-op-interface-defs)
-message("TBLGENOUT" ${TABLEGEN_OUTPUT})
-add_public_tablegen_target(gen_const_operands_interface)
-add_dependencies(compiler gen_const_operands_interface)

src/dialect/onnx/attribute_promotion.cpp

@@ -1,79 +0,0 @@
-//===----- shape_inference_pass.cpp - Shape Inference ---------------------===//
-//
-// Copyright 2019 The IBM Research Authors.
-//
-// =============================================================================
-//
-// This file implements a Function level pass performing propagation of array
-// shapes through function specialization.
-//
-//===----------------------------------------------------------------------===//
-
-#include "mlir/Pass/Pass.h"
-#include "llvm/Support/raw_ostream.h"
-
-#include "src/dialect/onnx/const_operands_interface.hpp"
-#include "src/dialect/onnx/onnx_ops.hpp"
-#include "src/pass/passes.hpp"
-
-using namespace mlir;
-
-#include "src/dialect/onnx/const_operands_interface.cpp.inc"
-
-namespace {
-/*!
- *  FunctionPass that performs shape inference by iterating over a list of
- *  candidate operations and propagating the shape information until the list
- *  of operations is empty [credit MLIR authors].
- */
-class AttributePromotionPass
-    : public mlir::FunctionPass<AttributePromotionPass> {
-public:
-  void runOnFunction() override {
-    auto f = getFunction();
-
-    llvm::Optional<mlir::Value> none;
-    f.walk([&](mlir::Operation *op) {
-      if (op->getNumResults() && op->getOpResult(0).getType().isa<NoneType>())
-        none = op->getOpResult(0);
-    });
-
-    if (!none) {
-      OpBuilder builder(f.getContext());
-      builder.setInsertionPointToStart(&f.front());
-      none =
-          builder.create<mlir::ConstantOp>(f.getLoc(), builder.getUnitAttr());
-    }
-
-    // Iterate on the operations that need shape inference i.e the operations
-    // that return a dynamic shape.
-    f.walk([&](mlir::Operation *op) {
-      if (IdentifyConstOperandsOpInterface opWithConstOperand =
-              dyn_cast<IdentifyConstOperandsOpInterface>(op)) {
-        auto promotableOperands = opWithConstOperand.identifyPromotableConstOperands();
-        for (const auto& operandNameToIdx : promotableOperands) {
-          auto name = operandNameToIdx.first;
-          auto idx = operandNameToIdx.second;
-
-          auto operandToPromote = op->getOperand(idx);
-          if (auto constantOp =
-                  dyn_cast_or_null<ConstantOp>(operandToPromote.getDefiningOp())) {
-            op->setAttr(name, constantOp.value());
-            op->setOperand(idx, *none);
-          }
-        }
-      }
-    });
-  }
-};
-} // end anonymous namespace
-
-/*!
- * Create a Shape Inference pass.
- */
-std::unique_ptr<mlir::Pass> mlir::createAttributePromotionPass() {
-  return std::make_unique<AttributePromotionPass>();
-}
-
-static PassRegistration<AttributePromotionPass> pass(
-    "attribute-promotion", "Shape inference for frontend dialects.");

src/dialect/onnx/const_operands_interface.hpp

@@ -1,24 +0,0 @@
-//===- shape_inference_interface.hpp - Definition for ShapeInference --------=//
-//
-// Copyright 2019 The IBM Research Authors.
-//
-// =============================================================================
-//
-// This file contains the declarations of the shape inference interfaces defined
-// in ShapeInferenceInterface.td.
-//
-//===----------------------------------------------------------------------===//
-
-#pragma once
-
-#include <map>
-#include <string>
-
-#include "mlir/IR/OpDefinition.h"
-
-namespace mlir {
-
-/// Include the auto-generated declarations.
-#include "src/dialect/onnx/const_operands_interface.hpp.inc"
-
-}  // end namespace mlir

src/dialect/onnx/const_operands_interface.td

@@ -1,32 +0,0 @@
-//=- shape_inference_interface.td - Shape Inference Interface -*- tablegen -==//
-//
-// Copyright 2019 The IBM Research Authors.
-//
-// =============================================================================
-//
-// Defines the operations of the Shape Inference Op Interface.
-//
-//===----------------------------------------------------------------------===//
-
-#ifdef IDENTIFY_PROMOTABLE_CONST_OPERANDS_OP_INTERFACE
-#else
-#define IDENTIFY_PROMOTABLE_CONST_OPERANDS_OP_INTERFACE
-
-#ifdef OP_BASE
-#else
-include "mlir/IR/OpBase.td"
-#endif // OP_BASE
-
-def IdentifyConstOperandsOpInterface : OpInterface<"IdentifyConstOperandsOpInterface"> {
-  let description = [{
-    Interface to access a registered method to infer the return types for an
-    operation that can be used during type inference.
-  }];
-
-  let methods = [
-    InterfaceMethod<"Infer and set the output shape for the current operation.",
-                    "std::map<std::string, size_t>", "identifyPromotableConstOperands">
-  ];
-}
-
-#endif // IDENTIFY_PROMOTABLE_CONST_OPERANDS_OP_INTERFACE

src/dialect/onnx/onnx.td

@@ -22,11 +22,6 @@ include "mlir/IR/OpBase.td"
 include "pass/shape_inference_interface.td"
 #endif // SHAPE_INFERENCE_INTERFACE
 
-#ifdef IDENTIFY_PROMOTABLE_CONST_OPERANDS_OP_INTERFACE
-#else
-include "dialect/onnx/const_operands_interface.td"
-#endif // IDENTIFY_PROMOTABLE_CONST_OPERANDS_OP_INTERFACE
-
 def ONNX_Dialect : Dialect {
   let name = "onnx";
   let cppNamespace = "";

src/dialect/onnx/onnx_ops.hpp

@@ -10,9 +10,6 @@
 
 #pragma once
 
-#include <map>
-#include <string>
-
 #include "mlir/Dialect/StandardOps/Ops.h"
 #include "mlir/IR/Builders.h"
 #include "mlir/IR/Dialect.h"
@@ -20,7 +17,6 @@
 #include "mlir/IR/StandardTypes.h"
 
 #include "src/pass/shape_inference_interface.hpp"
-#include "src/dialect/onnx/const_operands_interface.hpp"
 
 namespace mlir {
 

src/dialect/onnx/onnxop.inc

@@ -26,7 +26,7 @@ def ONNXAbsOp:ONNX_Op<"Abs",
       outputTypes.emplace_back(UnrankedTensorType::get(elementType));
       build(builder, state, outputTypes, operands, attributes);
     }]>
-  ];
+    ];
 }
 
 def ONNXAcosOp:ONNX_Op<"Acos",
@@ -2501,9 +2501,7 @@ def ONNXReluOp:ONNX_Op<"Relu",
 }
 
 def ONNXReshapeOp:ONNX_Op<"Reshape",
-  [NoSideEffect,
+  [NoSideEffect, DeclareOpInterfaceMethods<ShapeInferenceOpInterface>]> {
-   DeclareOpInterfaceMethods<ShapeInferenceOpInterface>,
-   OpInterface<"IdentifyConstOperandsOpInterface">]> {
   let summary = "ONNX Reshape operation";
   let description = [{
   "Reshape the input tensor similar to numpy.reshape."
@@ -2514,11 +2512,8 @@ def ONNXReshapeOp:ONNX_Op<"Reshape",
   "from the input tensor)."
   }];
   let arguments = (ins AnyTypeOf<[AnyMemRef, AnyTensor]>:$data,
-    AnyTypeOf<[AnyMemRef, AnyTensor, NoneType]>:$shape);
+    AnyTypeOf<[AnyMemRef, AnyTensor]>:$shape);
   let results = (outs AnyTypeOf<[AnyMemRef, AnyTensor]>:$reshaped);
-  let extraClassDeclaration = [{
-    std::map<std::string, size_t> identifyPromotableConstOperands() { return {{"shape", 1}}; }
-  }];
 }
 
 def ONNXResizeOp:ONNX_Op<"Resize",

src/main.cpp

@@ -126,7 +126,6 @@ int main(int argc, char *argv[]) {
   pm.addPass(mlir::createShapeInferencePass());
   pm.addPass(mlir::createCanonicalizerPass());
   pm.addPass(mlir::createShapeInferencePass());
-  pm.addPass(mlir::createAttributePromotionPass());
 
   if (emissionTarget >= EmitMLIR) {
     pm.addPass(mlir::createLowerToKrnlPass());

src/pass/passes.hpp

@@ -20,8 +20,6 @@ std::unique_ptr<Pass> createDecomposeONNXToONNXPass();
 
 std::unique_ptr<Pass> createShapeInferencePass();
 
-std::unique_ptr<Pass> createAttributePromotionPass();
-
 /// Add pass for lowering to Krnl IR.
 std::unique_ptr<Pass> createLowerToKrnlPass();
 

src/pass/shape_inference_pass.cpp

@@ -12,9 +12,9 @@
 #include "mlir/Pass/Pass.h"
 #include "llvm/ADT/SmallPtrSet.h"
 #include "llvm/Support/raw_ostream.h"
-#include "mlir/IR/StandardTypes.h"
 
 #include "shape_inference_interface.hpp"
+#include "src/dialect/onnx/onnx_ops.hpp"
 
 #include "passes.hpp"