Remove Level Constraint for Constant Propagation (#2537)

* Remove level constraint --------- Co-authored-by: Megan Hampton <[email protected]>
onnx · Sep 28, 2023 · 1a15f58 · 1a15f58
1 parent 06a10c0
commit 1a15f58
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Showing 14 changed files with 33 additions and 35 deletions.
diff --git a/src/Compiler/CompilerOptions.cpp b/src/Compiler/CompilerOptions.cpp
@@ -69,7 +69,7 @@ std::string reportHeapBefore;                          // onnx-mlir only
 std::string reportHeapAfter;                           // onnx-mlir only
 std::string modelTag;                                  // onnx-mlir only
 bool enableConvOptPass;                                // onnx-mlir only
-bool enableConstantProp;                               // onnx-mlir only
+bool disableConstantProp;                              // onnx-mlir only
 std::vector<std::string> extraLibPaths;                // onnx-mlir only
 std::vector<std::string> extraLibs;                    // onnx-mlir only
 ProfileIRs profileIR;                                  // onnx-mlir only
@@ -126,8 +126,7 @@ static llvm::cl::opt<OptLevel, true> OptimizationLevelOpt(
     llvm::cl::values(clEnumVal(O0, "Optimization level 0 (default):"),
         clEnumVal(O1, "Optimization level 1"),
         clEnumVal(O2, "Optimization level 2"),
-        clEnumVal(O3,
-            "Optimization level 3, constant propagation and SIMD is enabled")),
+        clEnumVal(O3, "Optimization level 3, SIMD is enabled")),
     llvm::cl::location(OptimizationLevel), llvm::cl::init(O0),
     llvm::cl::cat(OnnxMlirCommonOptions));
 
@@ -462,10 +461,10 @@ static llvm::cl::opt<bool, true> enableConvOptPassOpt("enable-conv-opt-pass",
     llvm::cl::location(enableConvOptPass), llvm::cl::init(true),
     llvm::cl::cat(OnnxMlirOptions));
 
-static llvm::cl::opt<bool, true> enableConstantPropOpt("enable-constant-prop",
-    llvm::cl::desc("Enable Constant Propagation (default is false)\n"
-                   "Set to 'true' to enable Constant Propagation at Level O3."),
-    llvm::cl::location(enableConstantProp), llvm::cl::init(false),
+static llvm::cl::opt<bool, true> disableConstantPropOpt("disable-constant-prop",
+    llvm::cl::desc("Disable Constant Propagation (default is false)\n"
+                   "Set to 'true' to disable Constant Propagation."),
+    llvm::cl::location(disableConstantProp), llvm::cl::init(false),
     llvm::cl::cat(OnnxMlirCommonOptions));
 
 static llvm::cl::list<std::string, std::vector<std::string>> extraLibPathsOpt(

diff --git a/src/Compiler/CompilerOptions.hpp b/src/Compiler/CompilerOptions.hpp
@@ -111,7 +111,7 @@ extern std::string reportHeapBefore;                          // onnx-mlir only
 extern std::string reportHeapAfter;                           // onnx-mlir only
 extern std::string modelTag;                                  // onnx-mlir only
 extern bool enableConvOptPass;                                // onnx-mlir only
-extern bool enableConstantProp;                               // onnx-mlir only
+extern bool disableConstantProp;                              // onnx-mlir only
 extern std::vector<std::string> extraLibPaths;                // onnx-mlir only
 extern std::vector<std::string> extraLibs;                    // onnx-mlir only
 extern ProfileIRs profileIR;                                  // onnx-mlir only

diff --git a/src/Compiler/CompilerPasses.cpp b/src/Compiler/CompilerPasses.cpp
@@ -46,8 +46,7 @@ void configurePasses() {
   // Set global vector machine support.
   VectorMachineSupport::setGlobalVectorMachineSupport(march, mcpu, "");
   configureConstPropONNXToONNXPass(onnxConstPropExpansionBound,
-      onnxConstPropDisablePatterns,
-      OptimizationLevel >= 3 || enableConstantProp);
+      onnxConstPropDisablePatterns, disableConstantProp);
   configureOnnxToKrnlLoweringPass(optReport == OptReport::Parallel,
       enableParallel, optReport == OptReport::Simd, !disableSimdOption);
 }

diff --git a/src/Pass/Passes.hpp b/src/Pass/Passes.hpp
@@ -46,7 +46,7 @@ std::unique_ptr<mlir::Pass> createShapeInferencePass();
 
 // To configure ConstPropONNXToONNXPass at program start.
 void configureConstPropONNXToONNXPass(int expansionBound,
-    llvm::ArrayRef<std::string> disabledPatterns, bool constantPropIsEnabled);
+    llvm::ArrayRef<std::string> disabledPatterns, bool constantPropIsDisabled);
 
 std::unique_ptr<mlir::Pass> createConstPropONNXToONNXPass();
 

diff --git a/src/Transform/ONNX/ConstProp.cpp b/src/Transform/ONNX/ConstProp.cpp
@@ -65,12 +65,12 @@ namespace {
 struct ConstPropONNXToONNXPassConfiguration {
   static int expansionBound;
   static StringSet<> disabledPatterns;
-  static bool constantPropIsEnabled;
+  static bool constantPropIsDisabled;
 };
 
 int ConstPropONNXToONNXPassConfiguration::expansionBound = -1; // -1 == no bound
 StringSet<> ConstPropONNXToONNXPassConfiguration::disabledPatterns = {};
-bool ConstPropONNXToONNXPassConfiguration::constantPropIsEnabled = false;
+bool ConstPropONNXToONNXPassConfiguration::constantPropIsDisabled = false;
 
 // Precondition: result has ranked tensor type with static shape and int or
 // float element type.
@@ -90,12 +90,12 @@ bool satisfiesExpansionBound(Value result) {
          getSizeInBytes(resultType);
 }
 
-// We want to enable Constant Propagation only for Level O3 or when a user
-// manually specifies the "enable-constant-prop" flag.
-bool isConstantPropagationEnabled() {
-  bool enable = (/*enableConstantProp*/ ConstPropONNXToONNXPassConfiguration::
-          constantPropIsEnabled);
-  return enable;
+// We want to disable Constant Propagation when a user
+// manually specifies the "disable-constant-prop" flag.
+bool isConstantPropagationDisabled() {
+  bool disable = (/*disableConstantProp*/ ConstPropONNXToONNXPassConfiguration::
+          constantPropIsDisabled);
+  return disable;
 }
 
 bool isNotDisabled(StringRef name) {
@@ -1053,20 +1053,20 @@ void ConstPropONNXToONNXPass::runOnOperation() {
 } // end anonymous namespace.
 
 void onnx_mlir::getConstPropONNXToONNXPatterns(RewritePatternSet &patterns) {
-  if (!isConstantPropagationEnabled())
+  if (isConstantPropagationDisabled())
     return;
   populateWithGenerated(patterns);
   if (isNotDisabled("SplitOfConst"))
     patterns.insert<SplitOfConst>(patterns.getContext());
 }
 
 void onnx_mlir::configureConstPropONNXToONNXPass(int expansionBound,
-    ArrayRef<std::string> disabledPatterns, bool constantPropIsEnabled) {
+    ArrayRef<std::string> disabledPatterns, bool constantPropIsDisabled) {
   ConstPropONNXToONNXPassConfiguration::expansionBound = expansionBound;
   ConstPropONNXToONNXPassConfiguration::disabledPatterns.insert(
       disabledPatterns.begin(), disabledPatterns.end());
-  ConstPropONNXToONNXPassConfiguration::constantPropIsEnabled =
-      constantPropIsEnabled;
+  ConstPropONNXToONNXPassConfiguration::constantPropIsDisabled =
+      constantPropIsDisabled;
 }
 
 /*!

diff --git a/test/backend/inference_backend.py b/test/backend/inference_backend.py
@@ -774,10 +774,10 @@ def get_test_models():
         # ==LIM== do_not_keep_dim not supported.
         #"test_reduce_log_sum_desc_axes_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
         #"test_reduce_log_sum_asc_axes_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
-        #"test_reduce_log_sum_default_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
+        "test_reduce_log_sum_default_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
         "test_reduce_log_sum_negative_axes_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
         # Name changed in v13
-        # "test_reduce_log_sum_default_expanded_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
+        "test_reduce_log_sum_default_expanded_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
 
         # ==OP== ReduceL1
         # ==MIN== 13

diff --git a/test/mlir/accelerators/nnpa/conversion/device-placement/emit-onnxir.mlir b/test/mlir/accelerators/nnpa/conversion/device-placement/emit-onnxir.mlir
@@ -1,4 +1,4 @@
-// RUN: onnx-mlir --EmitONNXIR --maccel=NNPA --printIR %s | FileCheck %s
+// RUN: onnx-mlir --EmitONNXIR --maccel=NNPA --disable-constant-prop=true --printIR %s | FileCheck %s
 
 module attributes {llvm.data_layout = "E-m:e-i1:8:16-i8:8:16-i64:64-f128:64-v128:64-a:8:16-n32:64", llvm.target_triple = "s390x-ibm-linux", "onnx-mlir.symbol-postfix" = "model"} {
   func.func @mnist(%arg0: tensor<1x1x28x28xf32>) -> tensor<1x10xf32> attributes {input_names = ["Input3"], output_names = ["Plus214_Output_0"]} {

diff --git a/test/mlir/accelerators/nnpa/conversion/device-placement/emit-zhighir.mlir b/test/mlir/accelerators/nnpa/conversion/device-placement/emit-zhighir.mlir
@@ -1,4 +1,4 @@
-// RUN: onnx-mlir --EmitZHighIR --maccel=NNPA --printIR %s | FileCheck %s
+// RUN: onnx-mlir --EmitZHighIR --maccel=NNPA --disable-constant-prop=true --printIR %s | FileCheck %s
 
 // Note that, we intentionally add `device=cpu` into onnx.Gemm to force it run on CPU.
 module { 

diff --git a/test/mlir/accelerators/nnpa/conversion/rewrite-onnx-for-zhigh.mlir b/test/mlir/accelerators/nnpa/conversion/rewrite-onnx-for-zhigh.mlir
@@ -1,5 +1,5 @@
 // RUN: onnx-mlir-opt --maccel=NNPA --shape-inference --rewrite-onnx-for-zhigh %s -split-input-file | FileCheck %s
-// RUN: onnx-mlir-opt --maccel=NNPA --rewrite-onnx-for-zhigh --shape-inference --canonicalize --constprop-onnx --enable-constant-prop=true --shape-inference %s --split-input-file | FileCheck --check-prefix=CONSTPROP %s
+// RUN: onnx-mlir-opt --maccel=NNPA --rewrite-onnx-for-zhigh --shape-inference --canonicalize --constprop-onnx  --shape-inference %s --split-input-file | FileCheck --check-prefix=CONSTPROP %s
 
 // -----
 

diff --git a/test/mlir/onnx/onnx_constprop.mlir b/test/mlir/onnx/onnx_constprop.mlir
@@ -1,4 +1,4 @@
-// RUN: onnx-mlir-opt --shape-inference --constprop-onnx --enable-constant-prop=true %s -split-input-file | FileCheck %s
+// RUN: onnx-mlir-opt --shape-inference --constprop-onnx %s -split-input-file | FileCheck %s
 
 //===----------------------------------------------------------------------===//
 // Common tests. Use ONNXAddOp as example.

diff --git a/test/mlir/onnx/onnx_constprop_expansion_bound.mlir b/test/mlir/onnx/onnx_constprop_expansion_bound.mlir
@@ -1,4 +1,4 @@
-// RUN: onnx-mlir-opt --constprop-onnx --enable-constant-prop=true --onnx-const-prop-expansion-bound=2 %s -split-input-file | FileCheck %s
+// RUN: onnx-mlir-opt --constprop-onnx  --onnx-const-prop-expansion-bound=2 %s -split-input-file | FileCheck %s
 
 //===----------------------------------------------------------------------===//
 // Constant propagate ONNXAddOp only if expansion bound satisfied

diff --git a/test/mlir/onnx/onnx_constprop_no_shape_inference.mlir b/test/mlir/onnx/onnx_constprop_no_shape_inference.mlir
@@ -1,4 +1,4 @@
-// RUN: onnx-mlir-opt --decompose-onnx --constprop-onnx --enable-constant-prop=true %s -split-input-file | FileCheck %s
+// RUN: onnx-mlir-opt --decompose-onnx --constprop-onnx %s -split-input-file | FileCheck %s
 
 //===----------------------------------------------------------------------===//
 /// Split tests

diff --git a/test/mlir/onnx/onnx_hybrid_transform.mlir b/test/mlir/onnx/onnx_hybrid_transform.mlir
@@ -1,6 +1,6 @@
-// RUN: onnx-mlir-opt --enable-constant-prop=true -onnx-hybrid-transform="constant-propagation=false decomposition=false" %s | FileCheck %s
-// RUN: onnx-mlir-opt --enable-constant-prop=true -onnx-hybrid-transform=constant-propagation=false %s | FileCheck --check-prefix=DECOMPOSE %s
-// RUN: onnx-mlir-opt --enable-constant-prop=true -onnx-hybrid-transform=decomposition=false %s | FileCheck --check-prefix=CONSTPROP %s
+// RUN: onnx-mlir-opt  -onnx-hybrid-transform="constant-propagation=false decomposition=false" %s | FileCheck %s
+// RUN: onnx-mlir-opt  -onnx-hybrid-transform=constant-propagation=false %s | FileCheck --check-prefix=DECOMPOSE %s
+// RUN: onnx-mlir-opt  -onnx-hybrid-transform=decomposition=false %s | FileCheck --check-prefix=CONSTPROP %s
 
 // Illustrates the back and forth between shape inference and the
 // BinaryOpBroadcastAxisPattern canonicalization pattern:

diff --git a/test/mlir/onnx/onnx_simplify_shape_related_ops.mlir b/test/mlir/onnx/onnx_simplify_shape_related_ops.mlir
@@ -1,4 +1,4 @@
-// RUN: onnx-mlir-opt --enable-constant-prop=true --simplify-shape-related-ops-onnx %s -split-input-file | FileCheck %s
+// RUN: onnx-mlir-opt  --simplify-shape-related-ops-onnx %s -split-input-file | FileCheck %s
 
 func.func @test_shape_to_dim(%arg0: tensor<?x256xi64>) -> (tensor<2xi64>) {
   %0 = "onnx.Shape"(%arg0) : (tensor<?x256xi64>) -> tensor<2xi64>