[MLIR] Fold aten select and fill_ pattern

Author: AmosLewis

lib/Dialect/Torch/Transforms/RecomposeComplexOps.cpp

@@ -12,6 +12,7 @@
 #include "mlir/Transforms/GreedyPatternRewriteDriver.h"
 #include "torch-mlir/Dialect/Torch/IR/TorchOps.h"
 #include "torch-mlir/Dialect/Torch/Transforms/Passes.h"
+#include "torch-mlir/Dialect/Torch/Utils/Utils.h"
 
 using namespace mlir;
 using namespace mlir::torch;
@@ -71,6 +72,53 @@ class RecomposeSliceCopy_ : public OpRewritePattern<AtenCopy_Op> {
     return success();
   }
 };
+
+class RecomposeSelectFill_ : public OpRewritePattern<AtenFill_TensorOp> {
+public:
+  using OpRewritePattern::OpRewritePattern;
+  LogicalResult matchAndRewrite(AtenFill_TensorOp op,
+                                PatternRewriter &rewriter) const override {
+    if (!op.getSelf().getDefiningOp() ||
+        !isa<AtenSelectIntOp>(op.getSelf().getDefiningOp()))
+      return failure();
+    auto selectOp = cast<AtenSelectIntOp>(op.getSelf().getDefiningOp());
+
+    // Get indices
+    int64_t dim;
+    if (!matchPattern(selectOp.getDim(), m_TorchConstantInt(&dim)))
+      return failure();
+
+    Value noneVal = rewriter.create<ConstantNoneOp>(op.getLoc());
+    Value falseVal = rewriter.create<ConstantBoolOp>(op.getLoc(), false);
+
+    // Create IndexPut_Op
+    // Convert indexNum to indexTensor for the selectOp
+    BaseTensorType selectOutTy = selectOp.getType().template cast<BaseTensorType>();
+    SmallVector<int64_t> empty;
+    auto dtype =
+        getTypeForTorchType(selectOp.getContext(), selectOp.getIndex().getType());
+    Type emptyTensorType = selectOutTy.getWithSizesAndDtype(llvm::ArrayRef(empty), dtype);
+    Value indexTensor = rewriter.create<PrimNumToTensorScalarOp>(
+        selectOp.getLoc(), emptyTensorType, selectOp.getIndex());
+
+    // Create indicesVector for IndexPut_Op by TorchNone and indexTensor
+    BaseTensorType tensorType = op->getResultTypes()[0].cast<BaseTensorType>();
+    SmallVector<Value> indicesVector(dim-1, noneVal);
+    indicesVector.push_back(indexTensor);
+
+    Value indices = rewriter.create<PrimListConstructOp>(
+        op.getLoc(),
+        Torch::ListType::get(op->getContext(),
+                             Torch::OptionalType::get(tensorType)),
+        indicesVector);
+
+    rewriter.replaceOpWithNewOp<Aten_IndexPutImpl_Op>(
+        op, op->getResultTypes(), selectOp.getSelf(), indices, op.getValue(),
+        /*accumulate=*/falseVal, /*unsafe=*/falseVal);
+
+    return success();
+  }
+};
 } // namespace
 
 namespace {
@@ -83,6 +131,7 @@ class RecomposeComplexOpsPass
 
     // pattern.add calls go here
     patterns.add<RecomposeSliceCopy_>(context);
+    patterns.add<RecomposeSelectFill_>(context);
 
     GreedyRewriteConfig config;
     config.useTopDownTraversal = true;