From d94e3575d8277812021d7988493e2badf6c109dc Mon Sep 17 00:00:00 2001
From: Scott Todd <scott.todd0@gmail.com>
Date: Mon, 27 Jan 2025 09:08:49 -0800
Subject: [PATCH] Fix logical `or`/`and` usage for MSVC compilation.

The `or`/`and` alternate spellings are not supported on all compilers without additinoal flags (https://learn.microsoft.com/en-us/cpp/cpp/logical-or-operator-pipe-pipe?view=msvc-170#operator-keyword-for-).
---
 lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp | 4 ++--
 lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp  | 8 ++++----
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp b/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
index adf9a46f464a..3db33aee1f1c 100644
--- a/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
+++ b/lib/Conversion/TorchOnnxToTorch/DefaultDomainGtoP.cpp
@@ -2346,7 +2346,7 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
         ArrayRef<int64_t> inputShape = inputTensorType.getSizes();
         unsigned inputRank = inputShape.size();
         // only handle 2D, 3D and 5D pooling cases
-        if (inputRank > 5 or inputRank < 3) {
+        if (inputRank > 5 || inputRank < 3) {
           return failure();
         }
         if (!resultType || !resultType.hasSizes()) {
@@ -2454,7 +2454,7 @@ void mlir::torch::onnx_c::populateDefaultDomainGtoP(
                                              "Unimplemented: unranked tensor");
         unsigned rank = *maybeRank;
         // only 1D, 2D and 3D LpPool is supported.
-        if (rank > 5 or rank < 3) {
+        if (rank > 5 || rank < 3) {
           return failure();
         }
 
diff --git a/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp b/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
index 91d6b5eb17fc..b292ce7f4830 100644
--- a/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
+++ b/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
@@ -9780,7 +9780,7 @@ class DecomposeAtenNllLossForwardOp
     auto targetSizes = targetType.getSizes();
     int64_t selfRank = selfSizes.size();
     int64_t targetRank = targetSizes.size();
-    if (selfRank <= 0 or selfRank > 2) {
+    if (selfRank <= 0 || selfRank > 2) {
       return rewriter.notifyMatchFailure(op, "input tensor should be 1D or 2D");
     }
     if (targetRank > 1) {
@@ -9788,8 +9788,8 @@ class DecomposeAtenNllLossForwardOp
                                          "target tensor shoule be 0D or 1D!");
     }
 
-    if (selfRank != 1 or targetRank != 0) {
-      if (!(selfSizes[0] == kUnknownSize and targetSizes[0] == kUnknownSize) and
+    if (selfRank != 1 || targetRank != 0) {
+      if (!(selfSizes[0] == kUnknownSize && targetSizes[0] == kUnknownSize) &&
           selfSizes[0] != targetSizes[0]) {
         return rewriter.notifyMatchFailure(
             op,
@@ -9907,7 +9907,7 @@ class DecomposeAtenNllLossForwardOp
         zeroTensor);
 
     Value totalWeight;
-    if (reduction == 0 and selfRank > 1) {
+    if (reduction == 0 && selfRank > 1) {
       auto zeroFloat =
           rewriter.create<ConstantFloatOp>(loc, rewriter.getF64FloatAttr(0.0));
       Value twSize = rewriter.create<PrimListConstructOp>(