[ONNX] Add averagepool dilations support (#3490)

- To fix dilations issue: https://github.com/llvm/torch-mlir/issues/3428
- Test by: https://github.com/nod-ai/SHARK-TestSuite/pull/268

lib/Conversion/TorchOnnxToTorch/DefaultDomainAtoF.cpp

@@ -379,7 +379,7 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
       "AveragePool", 11,
       [](OpBinder binder, ConversionPatternRewriter &rewriter) {
         std::string autoPad;
-        SmallVector<int64_t> dilation;
+        SmallVector<int64_t> dilations;
         if (binder.customOpNameStringAttr(autoPad, "auto_pad", "NOTSET"))
           return failure();
         if (autoPad != "NOTSET") {
@@ -387,13 +387,6 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
           return rewriter.notifyMatchFailure(
               binder.op, "unsupported conversion: auto_pad != NOTSET");
         }
-        if (binder.s64IntegerArrayAttr(dilation, "dilations", {})) {
-          return failure();
-        }
-        if (dilation.size() > 0) {
-          return rewriter.notifyMatchFailure(
-              binder.op, "dilation is not supported by torch.aten.avgpool op");
-        }
 
         Torch::ValueTensorType resultType;
         Value operand;
@@ -436,7 +429,7 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
               binder.op, "strides list size does not match the number of axes");
         }
 
-        SmallVector<Value> cstKernel, cstPadding, cstStrides;
+        SmallVector<Value> cstKernel, cstPadding, cstStridesDilations;
         for (int64_t i : kernel) {
           cstKernel.push_back(rewriter.create<Torch::ConstantIntOp>(
               binder.getLoc(), rewriter.getI64IntegerAttr(i)));
@@ -454,9 +447,24 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
               binder.getLoc(), rewriter.getI64IntegerAttr(padding[i])));
         }
         for (int64_t i : strides) {
-          cstStrides.push_back(rewriter.create<Torch::ConstantIntOp>(
+          cstStridesDilations.push_back(rewriter.create<Torch::ConstantIntOp>(
               binder.getLoc(), rewriter.getI64IntegerAttr(i)));
         }
+
+        // No dilations attribute in pytorch avgpool op, so use this trick to
+        // encode dilation into strides. Then in the following torchtolinalg
+        // lowering, decode strides into strides + dilation.
+        // [strideDim1,strideDim2,...,dilationDim1,dilationDim2,...]
+        if (binder.s64IntegerArrayAttr(
+                dilations, "dilations",
+                llvm::SmallVector<int64_t>(rank - 2, 1))) {
+          return failure();
+        }
+        for (auto dilation : dilations) {
+          cstStridesDilations.push_back(rewriter.create<Torch::ConstantIntOp>(
+              binder.getLoc(), rewriter.getI64IntegerAttr(dilation)));
+        }
+
         Value kernelSizeList = rewriter.create<Torch::PrimListConstructOp>(
             binder.getLoc(),
             Torch::ListType::get(Torch::IntType::get(binder.op->getContext())),
@@ -465,10 +473,12 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
             binder.getLoc(),
             Torch::ListType::get(Torch::IntType::get(binder.op->getContext())),
             cstPadding);
-        Value stridesList = rewriter.create<Torch::PrimListConstructOp>(
-            binder.getLoc(),
-            Torch::ListType::get(Torch::IntType::get(binder.op->getContext())),
-            cstStrides);
+        Value stridesDilationsList =
+            rewriter.create<Torch::PrimListConstructOp>(
+                binder.getLoc(),
+                Torch::ListType::get(
+                    Torch::IntType::get(binder.op->getContext())),
+                cstStridesDilations);
         Value cstCeilMode =
             rewriter.create<Torch::ConstantBoolOp>(binder.getLoc(), ceilMode);
         Value cstCountIncludePad = rewriter.create<Torch::ConstantBoolOp>(
@@ -477,19 +487,22 @@ void mlir::torch::onnx_c::populateDefaultDomainAtoF(
 
         if (rank == 3) {
           rewriter.replaceOpWithNewOp<Torch::AtenAvgPool1dOp>(
-              binder.op, resultType, operand, kernelSizeList, stridesList,
-              paddingList, cstCeilMode, cstCountIncludePad);
+              binder.op, resultType, operand, kernelSizeList,
+              stridesDilationsList, paddingList, cstCeilMode,
+              cstCountIncludePad);
           return success();
         } else if (rank == 4) {
           rewriter.replaceOpWithNewOp<Torch::AtenAvgPool2dOp>(
-              binder.op, resultType, operand, kernelSizeList, stridesList,
-              paddingList, cstCeilMode, cstCountIncludePad,
+              binder.op, resultType, operand, kernelSizeList,
+              stridesDilationsList, paddingList, cstCeilMode,
+              cstCountIncludePad,
               /*divisor_override=*/cstNone);
           return success();
         } else if (rank == 5) {
           rewriter.replaceOpWithNewOp<Torch::AtenAvgPool3dOp>(
-              binder.op, resultType, operand, kernelSizeList, stridesList,
-              paddingList, cstCeilMode, cstCountIncludePad,
+              binder.op, resultType, operand, kernelSizeList,
+              stridesDilationsList, paddingList, cstCeilMode,
+              cstCountIncludePad,
               /*divisor_override=*/cstNone);
           return success();
         }

lib/Conversion/TorchToLinalg/Pooling.cpp

@@ -612,6 +612,16 @@ public:
                                                   strideInts, paddingInts)))
       return rewriter.notifyMatchFailure(op, "invalid pooling parameters");
 
+    // Decode strideInts into strideInts and dilation
+    if (strideInts.size() == 2 * Dim) {
+      for (int i = 0; i < Dim; i++) {
+        dilationInts[i] = strideInts[Dim + i];
+      }
+      for (int i = 0; i < Dim; i++) {
+        strideInts.pop_back();
+      }
+    }
+
     // TODO: Add support for count_include_pad equal to `False`.
     bool countIncludePad;
     if (!matchPattern(op.getCountIncludePad(),