diff --git a/src/Accelerators/NNPA/Compiler/NNPACompilerUtils.cpp b/src/Accelerators/NNPA/Compiler/NNPACompilerUtils.cpp
index b078640e82..e4145407de 100644
--- a/src/Accelerators/NNPA/Compiler/NNPACompilerUtils.cpp
+++ b/src/Accelerators/NNPA/Compiler/NNPACompilerUtils.cpp
@@ -111,15 +111,7 @@ void addONNXToZHighPasses(mlir::PassManager &pm) {
onnx_mlir::zhigh::createZHighConstPropagationPass());
// One more call to ONNX shape inference/canonicalization/... to update shape
// if possible.
- if (enableONNXHybridPass) {
- // For starters only illustrating the new hybrid pass by replacing 3 passes
- // here. The plan is to replace most of the passes in addONNXToMLIRPasses.
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createONNXHybridTransformPass());
- } else {
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- pm.addPass(mlir::createCanonicalizerPass());
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- }
+ pm.addNestedPass<func::FuncOp>(onnx_mlir::createONNXHybridTransformPass());
// Remove common sub-expressions.
pm.addPass(mlir::createCSEPass());
diff --git a/src/Compiler/CompilerOptions.cpp b/src/Compiler/CompilerOptions.cpp
index 4b4b9a5126..cc137bf464 100644
--- a/src/Compiler/CompilerOptions.cpp
+++ b/src/Compiler/CompilerOptions.cpp
@@ -34,7 +34,6 @@ std::string march; // common for both
InstrumentStages instrumentStage; // common for both
int onnxConstPropExpansionBound; // common for both
std::vector<std::string> onnxConstPropDisablePatterns; // common for both
-bool enableONNXHybridPass; // common for both
std::vector<std::string> functionsToDecompose; // common for both
std::string opsForCall; // common for both
EmissionTargetType emissionTarget; // onnx-mlir only
@@ -59,8 +58,6 @@ std::string instrumentOps; // onnx-mlir only
unsigned instrumentControlBits; // onnx-mlir only
bool instrumentONNXSignature; // onnx-mlir only
std::string ONNXOpStats; // onnx-mlir only
-int onnxOpTransformThreshold; // onnx-mlir only
-bool onnxOpTransformReport; // onnx-mlir only
bool enableParallel; // onnx-mlir only
bool disableSimdOption; // onnx-mlir only
bool enableSimdDataLayout; // onnx-mlir only
@@ -173,12 +170,6 @@ static llvm::cl::list<std::string, std::vector<std::string>>
llvm::cl::location(onnxConstPropDisablePatterns),
llvm::cl::cat(OnnxMlirCommonOptions));
-static llvm::cl::opt<bool, true> enableONNXHybridPassOpt("onnx-hybrid-pass",
- llvm::cl::desc("Enable ONNX hybrid pass (default=true)\n"
- "Set to 'false' if you want to disable ONNX hybrid pass."),
- llvm::cl::location(enableONNXHybridPass), llvm::cl::init(true),
- llvm::cl::cat(OnnxMlirCommonOptions));
-
static llvm::cl::list<std::string, std::vector<std::string>>
functionsToDecomposeOpt("functions-to-decompose",
llvm::cl::desc("Specify ONNX functions to decompose"),
@@ -377,22 +368,6 @@ static llvm::cl::opt<std::string, true> ONNXOpStatsOpt("onnx-op-stats",
llvm::cl::location(ONNXOpStats), llvm::cl::init(""),
llvm::cl::cat(OnnxMlirOptions));
-static llvm::cl::opt<int, true> onnxOpTransformThresholdOpt(
- "onnx-op-transform-threshold",
- llvm::cl::desc(
- "Max iteration for dynamic op transform passes (default=3).\n"
- "If set to 0, onnxOpTransformPass will be disabled, and\n"
- "static iteration will be used"),
- llvm::cl::location(onnxOpTransformThreshold), llvm::cl::init(3),
- llvm::cl::cat(OnnxMlirOptions));
-
-static llvm::cl::opt<bool, true> onnxOpTransformReportOpt(
- "onnx-op-transform-report",
- llvm::cl::desc(
- "Report diagnostic info for ONNX op transform/optimization passes."),
- llvm::cl::location(onnxOpTransformReport), llvm::cl::init(false),
- llvm::cl::cat(OnnxMlirOptions));
-
static llvm::cl::opt<bool, true> enableParallelOpt("parallel",
llvm::cl::desc("Enable parallelization (default=false)\n"
"Set to 'true' if you want to enable parallelization."),
diff --git a/src/Compiler/CompilerOptions.hpp b/src/Compiler/CompilerOptions.hpp
index f781e03424..0da570532b 100644
--- a/src/Compiler/CompilerOptions.hpp
+++ b/src/Compiler/CompilerOptions.hpp
@@ -76,7 +76,6 @@ extern std::string march; // common for both
extern InstrumentStages instrumentStage; // common for both
extern int onnxConstPropExpansionBound; // common for both
extern std::vector<std::string> onnxConstPropDisablePatterns; // common for both
-extern bool enableONNXHybridPass; // common for both
extern std::vector<std::string> functionsToDecompose; // common for both
extern std::string opsForCall; // common for both
extern EmissionTargetType emissionTarget; // onnx-mlir only
@@ -101,8 +100,6 @@ extern std::string instrumentOps; // onnx-mlir only
extern unsigned instrumentControlBits; // onnx-mlir only
extern bool instrumentONNXSignature; // onnx-mlir only
extern std::string ONNXOpStats; // onnx-mlir only
-extern int onnxOpTransformThreshold; // onnx-mlir only
-extern bool onnxOpTransformReport; // onnx-mlir only
extern bool enableParallel; // onnx-mlir only
extern bool disableSimdOption; // onnx-mlir only
extern bool enableSimdDataLayout; // onnx-mlir only
diff --git a/src/Compiler/CompilerPasses.cpp b/src/Compiler/CompilerPasses.cpp
index 706df8eccf..b0f035309b 100644
--- a/src/Compiler/CompilerPasses.cpp
+++ b/src/Compiler/CompilerPasses.cpp
@@ -68,40 +68,12 @@ void addONNXToMLIRPasses(mlir::PassManager &pm, bool targetCPU) {
// Decompose first. Eliminates some unsupported ops without shape inference.
pm.addNestedPass<func::FuncOp>(onnx_mlir::createDecomposeONNXToONNXPass());
- if (enableONNXHybridPass) {
+ pm.addNestedPass<func::FuncOp>(onnx_mlir::createONNXHybridTransformPass());
+ // Convolution Optimization for CPU: enable when there are no accelerators.
+ if (targetCPU && enableConvOptPass) {
+ pm.addNestedPass<func::FuncOp>(onnx_mlir::createConvOptONNXToONNXPass(
+ enableSimdDataLayout && !disableSimdOption));
pm.addNestedPass<func::FuncOp>(onnx_mlir::createONNXHybridTransformPass());
- // Convolution Optimization for CPU: enable when there are no accelerators.
- if (targetCPU && enableConvOptPass) {
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createConvOptONNXToONNXPass(
- enableSimdDataLayout && !disableSimdOption));
- pm.addNestedPass<func::FuncOp>(
- onnx_mlir::createONNXHybridTransformPass());
- }
- } else {
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- pm.addPass(mlir::createCanonicalizerPass());
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- // Convolution Optimization for CPU: enable when there are no accelerators.
- if (targetCPU && enableConvOptPass) {
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createConvOptONNXToONNXPass(
- enableSimdDataLayout && !disableSimdOption));
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- }
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createConstPropONNXToONNXPass());
- if (onnxOpTransformThreshold > 0) {
- // Dynamic iterate in ONNXOpTransformPass
- pm.addPass(onnx_mlir::createONNXOpTransformPass(onnxOpTransformThreshold,
- onnxOpTransformReport, targetCPU,
- enableSimdDataLayout && !disableSimdOption, enableConvOptPass));
- } else {
- // Statically add extra passes
- for (int i = 0; i < repeatOnnxTransform; i++) {
- pm.addPass(mlir::createCanonicalizerPass());
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- pm.addNestedPass<func::FuncOp>(
- onnx_mlir::createConstPropONNXToONNXPass());
- }
- }
}
// Simplify shape-related ops.
@@ -109,13 +81,7 @@ void addONNXToMLIRPasses(mlir::PassManager &pm, bool targetCPU) {
// One more call to ONNX shape inference/canonicalization/... to update
// shape if possible.
- if (enableONNXHybridPass) {
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createONNXHybridTransformPass());
- } else {
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- pm.addPass(mlir::createCanonicalizerPass());
- pm.addNestedPass<func::FuncOp>(onnx_mlir::createShapeInferencePass());
- }
+ pm.addNestedPass<func::FuncOp>(onnx_mlir::createONNXHybridTransformPass());
// Replace ONNXReturnOp with func::ReturnOp.
pm.addPass(onnx_mlir::createStandardFuncReturnPass());
diff --git a/src/Pass/Passes.hpp b/src/Pass/Passes.hpp
index d228d1bde7..076fd8e2b5 100644
--- a/src/Pass/Passes.hpp
+++ b/src/Pass/Passes.hpp
@@ -29,12 +29,6 @@ namespace onnx_mlir {
/// Pass for removing DisposableElementsAttr attributes.
std::unique_ptr<mlir::Pass> createScrubDisposablePass(bool closeAfter = true);
-/// Pass for ONNX graph level optimization
-std::unique_ptr<mlir::Pass> createONNXOpTransformPass();
-std::unique_ptr<mlir::Pass> createONNXOpTransformPass(int threshold,
- bool report, bool targetCPU, bool enableSimdDataLayoutOpt,
- bool enableConvOptPass);
-
/// Pass for rewriting inside frontend dialect.
std::unique_ptr<mlir::Pass> createDecomposeONNXToONNXPass(
const std::string &target = "");
diff --git a/src/Tools/onnx-mlir-opt/RegisterPasses.cpp b/src/Tools/onnx-mlir-opt/RegisterPasses.cpp
index c31875b14f..25025c91a0 100644
--- a/src/Tools/onnx-mlir-opt/RegisterPasses.cpp
+++ b/src/Tools/onnx-mlir-opt/RegisterPasses.cpp
@@ -39,10 +39,6 @@ void registerOMPasses(int optLevel) {
return createScrubDisposablePass();
});
- mlir::registerPass([]() -> std::unique_ptr<mlir::Pass> {
- return createONNXOpTransformPass();
- });
-
mlir::registerPass([]() -> std::unique_ptr<mlir::Pass> {
return createDecomposeONNXToONNXPass();
});
diff --git a/src/Transform/ONNX/CMakeLists.txt b/src/Transform/ONNX/CMakeLists.txt
index 8a551687bd..126ace32a8 100644
--- a/src/Transform/ONNX/CMakeLists.txt
+++ b/src/Transform/ONNX/CMakeLists.txt
@@ -55,17 +55,6 @@ add_onnx_mlir_library(OMInstrumentONNX
MLIRPass
)
-add_onnx_mlir_library(OMOpTransform
- ONNXOpTransformPass.cpp
-
- LINK_LIBS PUBLIC
- OMONNXOps
- MLIRPass
- OMONNXRewrite
- OMShapeInferencePass
- MLIRTransforms
- )
-
add_onnx_mlir_library(OMHybridTransform
ONNXHybridTransformPass.cpp
diff --git a/src/Transform/ONNX/ONNXOpTransformPass.cpp b/src/Transform/ONNX/ONNXOpTransformPass.cpp
deleted file mode 100644
index f371e65e25..0000000000
--- a/src/Transform/ONNX/ONNXOpTransformPass.cpp
+++ /dev/null
@@ -1,127 +0,0 @@
-/*
- * SPDX-License-Identifier: Apache-2.0
- */
-
-//===------- ONNXOpTransformPass.cpp - ONNX Op Transform ------------------===//
-//
-// Copyright 2019-2020 The IBM Research Authors.
-//
-// =============================================================================
-//
-// This file implements a combined pass that dynamically invoke several
-// transformation on ONNX ops.
-//
-//===----------------------------------------------------------------------===//
-
-#include "mlir/IR/OperationSupport.h"
-#include "mlir/Pass/PassManager.h"
-#include "mlir/Transforms/Passes.h"
-
-#include "src/Dialect/ONNX/ONNXOps.hpp"
-#include "src/Pass/Passes.hpp"
-
-using namespace mlir;
-
-namespace {
-
-struct ONNXOpTransformPass : public mlir::PassWrapper<ONNXOpTransformPass,
- OperationPass<mlir::ModuleOp>> {
- MLIR_DEFINE_EXPLICIT_INTERNAL_INLINE_TYPE_ID(ONNXOpTransformPass)
-
- StringRef getArgument() const override { return "onnx-op-transform"; }
-
- StringRef getDescription() const override {
- return "Invoke passes iteratively that transform ONNX operation.";
- }
-
- Option<int> onnxOpTransformThreshold{*this, "onnx-op-transform-threshold",
- llvm::cl::desc("max iteration for op transform passes."),
- llvm::cl::init(10)};
- Option<bool> onnxOpTransformReport{*this, "onnx-op-transform-report",
- llvm::cl::desc("Report diagnostic info for op transform passes."),
- llvm::cl::init(false)};
- Option<bool> onnxOpTransformTargetCPU{*this, "onnx-op-transform-target-cpu",
- llvm::cl::desc("Target CPU op transform passes."), llvm::cl::init(true)};
- Option<bool> onnxOpTransformEnableSimdDataLayout{*this,
- "onnx-op-transform-simd-data-layout",
- llvm::cl::desc("Enable SIMD data layout opt in op transform passes."),
- llvm::cl::init(false)};
- Option<bool> enableConvOptPass{*this, "enable-conv-opt-pass",
- llvm::cl::desc("Enable the ConvOptPass. Default is true."),
- llvm::cl::init(true)};
-
- ONNXOpTransformPass() = default;
- ONNXOpTransformPass(const ONNXOpTransformPass &pass)
- : mlir::PassWrapper<ONNXOpTransformPass,
- OperationPass<mlir::ModuleOp>>() {}
- ONNXOpTransformPass(int threshold, bool report, bool targetCPU,
- bool enableSimdDataLayoutOpt, bool enableConvOptPass) {
- this->onnxOpTransformThreshold = threshold;
- this->onnxOpTransformReport = report;
- this->onnxOpTransformTargetCPU = targetCPU;
- this->onnxOpTransformEnableSimdDataLayout = enableSimdDataLayoutOpt;
- this->enableConvOptPass = enableConvOptPass;
- }
-
- void runOnOperation() final;
-};
-
-void ONNXOpTransformPass::runOnOperation() {
- auto module = getOperation();
-
- assert(onnxOpTransformThreshold > 0);
- int n = onnxOpTransformThreshold;
- OperationFingerPrint before(module);
- do {
- OpPassManager dynamicPM("builtin.module");
- dynamicPM.addNestedPass<func::FuncOp>(
- onnx_mlir::createDecomposeONNXToONNXPass());
- dynamicPM.addNestedPass<func::FuncOp>(
- onnx_mlir::createShapeInferencePass());
- dynamicPM.addPass(mlir::createCanonicalizerPass());
- dynamicPM.addNestedPass<func::FuncOp>(
- onnx_mlir::createShapeInferencePass());
- // Convolution Optimization currently only for CPU.
- if (onnxOpTransformTargetCPU && enableConvOptPass) {
- dynamicPM.addNestedPass<func::FuncOp>(
- onnx_mlir::createConvOptONNXToONNXPass(
- onnxOpTransformEnableSimdDataLayout));
- dynamicPM.addNestedPass<func::FuncOp>(
- onnx_mlir::createShapeInferencePass());
- }
- dynamicPM.addNestedPass<func::FuncOp>(
- onnx_mlir::createConstPropONNXToONNXPass());
- if (failed(runPipeline(dynamicPM, module)))
- return signalPassFailure();
- OperationFingerPrint after(module);
- if (after == before)
- break;
- before = after;
- } while (--n > 0);
- if (n == 0) {
- module->emitWarning()
- << "ONNXOpTransform did not converge after " << onnxOpTransformThreshold
- << "iterations. "
- << "You may set a higher threshold with command option";
- }
- if (onnxOpTransformReport) {
- llvm::outs() << "ONNXOpTransform iterated " << onnxOpTransformThreshold - n
- << " times, converged " << (n > 0 ? "true" : "false") << "\n";
- }
-}
-
-} // end anonymous namespace
-
-/*!
- * Create an instrumentation pass.
- */
-std::unique_ptr<mlir::Pass> onnx_mlir::createONNXOpTransformPass() {
- return std::make_unique<ONNXOpTransformPass>();
-}
-
-std::unique_ptr<mlir::Pass> onnx_mlir::createONNXOpTransformPass(int threshold,
- bool report, bool targetCPU, bool enableSimdDataLayoutOpt,
- bool enableConvOptPass) {
- return std::make_unique<ONNXOpTransformPass>(
- threshold, report, targetCPU, enableSimdDataLayoutOpt, enableConvOptPass);
-}