Fix output size computation for MaxPool2D for ceil_model = true.

lib/Conversion/TorchToLinalg/Utils.cpp

@@ -13,6 +13,7 @@
 #include "mlir/Dialect/Arith/IR/Arith.h"
 #include "mlir/Dialect/ControlFlow/IR/ControlFlowOps.h"
 #include "mlir/Dialect/Linalg/IR/Linalg.h"
+#include "mlir/Dialect/SCF/IR/SCF.h"
 #include "torch-mlir/Conversion/TorchToLinalg/Utils.h"
 #include "torch-mlir/Conversion/Utils/Utils.h"
 #include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
@@ -116,6 +117,34 @@ Value torch_to_linalg::getOutputDimForConvOps(OpBuilder &b, Location loc,
   else
     division = b.createOrFold<arith::FloorDivSIOp>(loc, dividend, strideInt);
   Value out = b.createOrFold<arith::AddIOp>(loc, division, c1);
+
+  if (ceilMode) {
+    Value outMinusOneTimesStride =
+        b.createOrFold<arith::MulIOp>(loc, division, strideInt);
+    Value inAddLeftPadding = b.createOrFold<arith::AddIOp>(
+        loc, castIndexToInt64(b, loc, in), paddingInt);
+
+    auto reduceOutputDim =
+        b.createOrFold<arith::CmpIOp>(loc, arith::CmpIPredicate::uge,
+                                      outMinusOneTimesStride, inAddLeftPadding);
+
+    // Emit 'then' region of 'scf.if'
+    auto emitThenRegion = [&](OpBuilder &opBuilder, Location loc) {
+      opBuilder.create<scf::YieldOp>(loc, division);
+    };
+
+    // Emit 'else' region of 'scf.if'
+    auto emitElseRegion = [&](OpBuilder &opBuilder, Location loc) {
+      opBuilder.create<scf::YieldOp>(loc, out);
+    };
+
+    // Emit 'scf.if' op
+    auto ifOp = b.create<scf::IfOp>(loc, reduceOutputDim, emitThenRegion,
+                                    emitElseRegion);
+
+    return castIntToIndex(b, loc, ifOp.getResult(0));
+  }
+
   return castIntToIndex(b, loc, out);
 }
 
@@ -527,8 +556,8 @@ Value torch_to_linalg::convertTensorToElementType(OpBuilder &b, Location loc,
                                                   Type elementType) {
   auto dtypePromoteBody = [&](OpBuilder &builder, Location loc,
                               ValueRange payloadArgs) {
-    Value elem =
-        convertScalarToDtype(builder, loc, payloadArgs[0], elementType);
+    Value elem = mlir::torch::Torch::convertScalarToDtype(
+        builder, loc, payloadArgs[0], elementType);
     builder.create<linalg::YieldOp>(loc, elem);
   };
   return torch_to_linalg::createElementwiseLinalgGeneric(

lib/Conversion/TorchToTosa/TorchToTosa.cpp

@@ -5252,9 +5252,11 @@ public:
     } else {
       int64_t dimSize =
           inputDim + padBefore + padAfter - dilation * (kernelDim - 1) - 1;
-      if (ceilMode && (dimSize % stride != 0))
-        return dimSize / stride + 2;
-      return dimSize / stride + 1;
+      int64_t outputDim = dimSize / stride + 1;
+      if (ceilMode && (dimSize % stride != 0) &&
+          (outputDim * stride < inputDim + padBefore))
+        outputDim++;
+      return outputDim;
     }
   }
 

projects/pt1/e2e_testing/xfail_sets.py

@@ -763,6 +763,7 @@ FX_IMPORTER_STABLEHLO_XFAIL_SET = {
     "LenStrModule_basic",
     "MaxPool2dCeilModeTrueModule_basic",
     "MaxPool2dStaticCeilModeTrueModule_basic",
+    "MaxPool2dStaticCeilModeTrueReduceOutputModule_basic",
     "MaxPool2dWithIndicesBackwardDynamic3DModule_basic",
     "MaxPool2dWithIndicesBackwardDynamic4DModule_basic",
     "MaxPool2dWithIndicesBackwardStatic3DModule_basic",
@@ -2261,6 +2262,7 @@ TOSA_PASS_SET = {
     "MatmulStaticBroadcast_basic",
     "MaxPool2dEmptyStrideStaticModule_basic",
     "MaxPool2dStaticCeilModeTrueModule_basic",
+    "MaxPool2dStaticCeilModeTrueReduceOutputModule_basic",
     "MaxPool2dStaticModule_basic",
     "MeanModule_basic",
     "MmDagModule_basic",
@@ -3000,6 +3002,7 @@ ONNX_XFAIL_SET = {
     "MaxPool1dCeilModeTrueModule_basic",
     "MaxPool1dModule_basic",
     "MaxPool2dCeilModeTrueModule_basic",
+    "MaxPool2dStaticCeilModeTrueReduceOutputModule_basic",
     "MaxPool2dModule_basic",
     "MaxPool2dWithIndicesAllOnesModule_basic",
     "MaxPool2dWithIndicesBackwardDynamic3DModule_basic",
@@ -4516,6 +4519,7 @@ ONNX_TOSA_XFAIL_SET = {
     "MaxPool1dCeilModeTrueModule_basic",
     "MaxPool1dModule_basic",
     "MaxPool2dCeilModeTrueModule_basic",
+    "MaxPool2dStaticCeilModeTrueReduceOutputModule_basic",
     "MaxPool2dModule_basic",
     "MaxPool2dWithIndicesAllNegativeValuesModule_basic",
     "MaxPool2dWithIndicesAllOnesModule_basic",

projects/pt1/python/torch_mlir_e2e_test/test_suite/pooling.py

@@ -420,6 +420,35 @@ def MaxPool2dCeilModeTrueModule_basic(module, tu: TestUtils):
     module.forward(tu.rand(1, 1, 20, 20, low=0.5, high=1.0))
 
 
+class MaxPool2dStaticCeilModeTrueReduceOutputModule(torch.nn.Module):
+    def __init__(self):
+        super().__init__()
+        self.mp2d = torch.nn.MaxPool2d(
+            kernel_size=6,
+            stride=6,
+            padding=3,
+            dilation=1,
+            ceil_mode=True,
+        )
+
+    @export
+    @annotate_args(
+        [
+            None,
+            ([2, 6, 20, 10], torch.float32, True),
+        ]
+    )
+    def forward(self, x):
+        return self.mp2d(x)
+
+
+@register_test_case(
+    module_factory=lambda: MaxPool2dStaticCeilModeTrueReduceOutputModule()
+)
+def MaxPool2dStaticCeilModeTrueReduceOutputModule_basic(module, tu: TestUtils):
+    module.forward(tu.rand(2, 6, 20, 10, low=0.5, high=1.0))
+
+
 # ==============================================================================