Fix remaining warnings on Windows and turn on warning-as-error (#1706)

This change applies the remaining fixes needed for warnings to be treated as errors on Windows and then turns them on on Windows only. Of particular interest are a couple of changes: * The `check-docs` target needs an update to properly parse the directive even when it contains parenthesis in the path. For example: `C:/Program Files (x86)/Microsoft Visual Studio/Shared/Python39_64/python.exe` * The Windows CI build now builds `onnx` first and then builds all of the targets that are enabled in onnx-mlir. This will make sure that no targets get missed * The remaining warnings (4927) in `ConstProp.cpp` are fixed as well. Signed-off-by: Stella Stamenova <[email protected]>
onnx · Sep 27, 2022 · 9795440 · 9795440
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diff --git a/.azure-pipelines/Windows-CI.yml b/.azure-pipelines/Windows-CI.yml
@@ -125,6 +125,15 @@ jobs:
     displayName: Download mlir artifact
     condition: and(succeeded(), ne(variables['MLIRBuildID'], 'NotFound'))
 
+  - script: |
+      call "%ProgramFiles(x86)%\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
+      cd onnx-mlir\third_party\onnx
+      python setup.py -q install
+    env:
+      CMAKE_ARGS: -DCMAKE_PREFIX_PATH="$(Agent.BuildDirectory)\protobuf_install" -DONNX_USE_PROTOBUF_SHARED_LIBS=OFF -DProtobuf_USE_STATIC_LIBS=ON -DONNX_USE_MSVC_STATIC_RUNTIME=OFF
+    displayName: Install onnx
+    workingDirectory: $(Agent.BuildDirectory)
+
   - script: |
       call "%ProgramFiles(x86)%\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
       call onnx-mlir\utils\build-onnx-mlir.cmd
@@ -147,15 +156,6 @@ jobs:
     env:
       CTEST_PARALLEL_LEVEL: ${{ parameters.CTEST_PARALLEL_LEVEL }}
 
-  - script: |
-      call "%ProgramFiles(x86)%\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
-      cd onnx-mlir\third_party\onnx
-      python setup.py -q install
-    env:
-      CMAKE_ARGS: -DCMAKE_PREFIX_PATH="$(Agent.BuildDirectory)\protobuf_install" -DONNX_USE_PROTOBUF_SHARED_LIBS=OFF -DProtobuf_USE_STATIC_LIBS=ON -DONNX_USE_MSVC_STATIC_RUNTIME=OFF
-    displayName: Install onnx
-    workingDirectory: $(Agent.BuildDirectory)
-
   - script: |
       call "%ProgramFiles(x86)%\Microsoft Visual Studio\2019\Enterprise\VC\Auxiliary\Build\vcvarsall.bat" x64
       call onnx-mlir\utils\check-docs.cmd

diff --git a/docs/BuildOnWindows.md b/docs/BuildOnWindows.md
@@ -99,9 +99,9 @@ call cmake %root_dir%\onnx-mlir -G "Ninja" ^
    -DLLVM_EXTERNAL_LIT=%lit_path% ^
    -DLLVM_LIT_ARGS=-v ^
    -DMLIR_DIR=%root_dir%\llvm-project\build\lib\cmake\mlir ^
-   -DONNX_MLIR_BUILD_TESTS=ON
+   -DONNX_MLIR_ENABLE_WERROR=ON
 
-call cmake --build . --config Release --target onnx-mlir
+call cmake --build . --config Release
 ```
 After the above commands succeed, an `onnx-mlir` executable should appear in the `Debug/bin` or `Release/bin` directory.
 

diff --git a/docs/doc_check/directive_impl/file_same_as_stdout.py b/docs/doc_check/directive_impl/file_same_as_stdout.py
@@ -50,4 +50,4 @@ def handle(config, ctx):
         raise ValueError("Check file-same-as-stdout failed")
 
 
-ext_to_patterns = {'.dc': 'file-same-as-stdout\\(([^)]*)\\)'}
+ext_to_patterns = {'.dc': 'file-same-as-stdout\\((.*)\\)'}
diff --git a/src/Transform/ONNX/ConstProp.cpp b/src/Transform/ONNX/ConstProp.cpp
@@ -351,7 +351,7 @@ void IterateConstPropElementwiseBinary(char *lhs, char *rhs,
 /// Do element-wise binary calculation of 'lhs' and 'rhs' values and create an
 /// ONNXConstantOp for the result.
 template <typename ElementwiseBinaryOp>
-ONNXConstantOp ConstPropElementwiseBinary(
+Value ConstPropElementwiseBinary(
     PatternRewriter &rewriter, Value replacingValue, Value lhs, Value rhs) {
   Type elementType =
       replacingValue.getType().cast<ShapedType>().getElementType();
@@ -383,7 +383,7 @@ ONNXConstantOp ConstPropElementwiseBinary(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
@@ -436,7 +436,7 @@ void IterateConstPropElementwiseUnary(
 /// Do element-wise unary calculation of 'input' value and create an
 /// ONNXConstantOp for the result.
 template <typename ElementwiseUnaryOp>
-ONNXConstantOp ConstPropElementwiseUnary(
+Value ConstPropElementwiseUnary(
     PatternRewriter &rewriter, Value replacingValue, Value constValue) {
   ShapedType replacingType = replacingValue.getType().cast<ShapedType>();
   ArrayRef<int64_t> replacingShape = replacingType.getShape();
@@ -465,14 +465,14 @@ ONNXConstantOp ConstPropElementwiseUnary(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
 // Code to perform constant propagation for transpose.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropTranspose(
+Value ConstPropTranspose(
     PatternRewriter &rewriter, Value replacingValue, Value constValue) {
   ArrayRef<int64_t> replacingShape =
       replacingValue.getType().cast<ShapedType>().getShape();
@@ -504,14 +504,14 @@ ONNXConstantOp ConstPropTranspose(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
 // Code to perform constant propagation for unsqueeze.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropUnsqueeze(
+Value ConstPropUnsqueeze(
     PatternRewriter &rewriter, Value replacingValue, Value input) {
   Operation *inputOp = input.getDefiningOp();
 
@@ -521,14 +521,14 @@ ONNXConstantOp ConstPropUnsqueeze(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
 // Code to perform constant propagation for Squeeze.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropSqueeze(
+Value ConstPropSqueeze(
     PatternRewriter &rewriter, Value replacingValue, Value input) {
   Operation *inputOp = input.getDefiningOp();
 
@@ -538,7 +538,7 @@ ONNXConstantOp ConstPropSqueeze(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
@@ -761,7 +761,7 @@ class ConstPropScatterNDPattern : public OpRewritePattern<ONNXScatterNDOp> {
 // Code to perform constant propagation for CastOp.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropCast(
+Value ConstPropCast(
     PatternRewriter &rewriter, Value replacingValue, Value constValue) {
   // Get the const value using the maximum precision e.g. double, int64_t.
   char *constArray =
@@ -796,14 +796,14 @@ ONNXConstantOp ConstPropCast(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
 // Code to perform constant propagation for SliceOp.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropSlice(
+Value ConstPropSlice(
     PatternRewriter &rewriter, Value replacingValue, Value constValue) {
   Operation *op = replacingValue.getDefiningOp();
   ONNXSliceOp sliceOp = cast<ONNXSliceOp>(op);
@@ -852,14 +852,14 @@ ONNXConstantOp ConstPropSlice(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
 // Code to perform constant propagation for ConcatOp.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropConcat(PatternRewriter &rewriter, Value replacingValue,
+Value ConstPropConcat(PatternRewriter &rewriter, Value replacingValue,
     ValueRange operands, IntegerAttr axisAttr) {
   // Get the const values using the maximum precision e.g. double, int64_t.
   SmallVector<char *, 4> inputArrays;
@@ -910,14 +910,14 @@ ONNXConstantOp ConstPropConcat(PatternRewriter &rewriter, Value replacingValue,
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
 // Code to perform constant propagation for ExpandOp.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropExpand(
+Value ConstPropExpand(
     PatternRewriter &rewriter, Value replacingValue, Value constValue) {
   // Get the const value using the maximum precision e.g. double, int64_t.
   char *inputArray =
@@ -964,14 +964,14 @@ ONNXConstantOp ConstPropExpand(
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//
 // Code to perform constant propagation for GatherOp.
 //===----------------------------------------------------------------------===//
 
-ONNXConstantOp ConstPropGather(PatternRewriter &rewriter, Value replacingValue,
+Value ConstPropGather(PatternRewriter &rewriter, Value replacingValue,
     Value inputValue, Value indicesValue) {
   Operation *op = replacingValue.getDefiningOp();
   ONNXGatherOp gatherOp = cast<ONNXGatherOp>(op);
@@ -1037,7 +1037,7 @@ ONNXConstantOp ConstPropGather(PatternRewriter &rewriter, Value replacingValue,
   ONNXConstantOp res =
       createConstantOpAndStoreBufferPtr(rewriter, replacingValue, resArray);
 
-  return res;
+  return res.getResult();
 }
 
 //===----------------------------------------------------------------------===//

diff --git a/test/numerical/Common.hpp b/test/numerical/Common.hpp
@@ -16,8 +16,8 @@
 #include <rapidcheck.h>
 
 #if defined(_MSC_VER)
-#ifdef _SILENCE_ALL_CXX17_DEPRECATION_WARNINGS &&                              \
-    !defined _SILENCE_WAS_PREDEFINED
+#if defined(_SILENCE_ALL_CXX17_DEPRECATION_WARNINGS) &&                        \
+    !defined(_SILENCE_WAS_PREDEFINED)
 #undef _SILENCE_ALL_CXX17_DEPRECATION_WARNINGS
 #endif
 #else

diff --git a/test/perf/CMakeLists.txt b/test/perf/CMakeLists.txt
@@ -4,13 +4,9 @@ add_onnx_mlir_library(PerfLib
   PerfHelper.cpp
   EXCLUDE_FROM_OM_LIBS
 
-  INCLUDE_DIRS PRIVATE
-  ${ONNX_MLIR_SRC_ROOT}/third_party/benchmark/include
-  ${ONNX_MLIR_BIN_ROOT}/third_party/benchmark/include
-
   LINK_LIBS PUBLIC
   benchmark 
-  CompilerUtils
+  LLVMSupport
   )
 
 add_custom_target(perf)
@@ -48,8 +44,6 @@ function(add_perf_unittest test_name)
   set_tests_properties(${test_name} PROPERTIES LABELS perf)
 endfunction()
 
-# The CompilerUtils ExecutionSession are also included in ModelLib,
-# but it did not compile when I removed these two. TODO, figure out why.
 set(TEST_LINK_LIBS ModelLib PerfLib)
 
 add_perf_unittest(PerfGemm

diff --git a/utils/build-onnx-mlir.cmd b/utils/build-onnx-mlir.cmd
@@ -8,6 +8,6 @@ call cmake %root_dir%\onnx-mlir -G "Ninja" ^
    -DLLVM_EXTERNAL_LIT=%lit_path% ^
    -DLLVM_LIT_ARGS=-v ^
    -DMLIR_DIR=%root_dir%\llvm-project\build\lib\cmake\mlir ^
-   -DONNX_MLIR_BUILD_TESTS=ON
+   -DONNX_MLIR_ENABLE_WERROR=ON
 
-call cmake --build . --config Release --target onnx-mlir
+call cmake --build . --config Release
Original file line number	Diff line number	Diff line change
Expand Up		@@ -50,4 +50,4 @@ def handle(config, ctx):
		raise ValueError("Check file-same-as-stdout failed")


		ext_to_patterns = {'.dc': 'file-same-as-stdout\\(([^)]*)\\)'}
		ext_to_patterns = {'.dc': 'file-same-as-stdout\\((.*)\\)'}