[Torch] emit aten.ne.str and add folder (llvm#3242)

archana-ramalingam · May 8, 2024 · 74b9709 · 74b9709
1 parent a763f77
commit 74b9709
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diff --git a/lib/Dialect/Torch/IR/TorchOps.cpp b/lib/Dialect/Torch/IR/TorchOps.cpp
@@ -4715,6 +4715,45 @@ LogicalResult AtenPermuteOp::verify() {
   return success();
 }
 
+//===----------------------------------------------------------------------===//
+// PrimsConvertElementTypeOp
+//===----------------------------------------------------------------------===//
+
+OpFoldResult PrimsConvertElementTypeOp::fold(FoldAdaptor adaptor) {
+  auto inputType = cast<BaseTensorType>(getA().getType());
+  auto outputType = cast<BaseTensorType>(getResult().getType());
+  if (inputType != outputType)
+    return nullptr;
+  if (!inputType.hasDtype() || !outputType.hasDtype())
+    return nullptr;
+  if (inputType.getDtype() != outputType.getDtype())
+    return nullptr;
+  return getA();
+}
+
+//===----------------------------------------------------------------------===//
+// AtenMaxPool2dWithIndicesOp
+//===----------------------------------------------------------------------===//
+
+void AtenMaxPool2dWithIndicesOp::getCanonicalizationPatterns(
+    RewritePatternSet &patterns, MLIRContext *context) {
+  patterns.add(+[](AtenMaxPool2dWithIndicesOp op, PatternRewriter &rewriter) {
+    if (!op.getResult1().use_empty()) {
+      return rewriter.notifyMatchFailure(
+          op, "result1 of MaxPool2dWithIndices should be unused");
+    }
+
+    Value result = rewriter.create<Torch::AtenMaxPool2dOp>(
+        op->getLoc(), op.getResult0().getType(), op.getSelf(),
+        op.getKernelSize(), op.getStride(), op.getPadding(), op.getDilation(),
+        op.getCeilMode());
+
+    op.getResult0().replaceAllUsesWith(result);
+    rewriter.eraseOp(op);
+    return success();
+  });
+}
+
 //===----------------------------------------------------------------------===//
 // AtenLinalgCrossOp
 //===----------------------------------------------------------------------===//
@@ -4967,4 +5006,4 @@ LogicalResult InitializeGlobalSlotsOp::verify() {
   if (getInitialValues().size() != getSlotSymNames().size())
     return emitOpError("expected number of operands to match number of slots");
   return success();
-}
+}
diff --git a/test/Dialect/Torch/canonicalize.mlir b/test/Dialect/Torch/canonicalize.mlir
@@ -2974,3 +2974,44 @@ func.func @aten_log$fold_splat_f32() -> !torch.vtensor<[4], f32> {
   %result = torch.aten.log %cst : !torch.vtensor<[4], f32> -> !torch.vtensor<[4], f32>
   return %result : !torch.vtensor<[4], f32>
 }
+
+// -----
+
+// CHECK-LABEL:   func.func @torch.prims.convert_element_type$fold(
+// CHECK:            %[[ARG:.*]]: !torch.vtensor<[64],f32>) -> !torch.vtensor<[64],f32> {
+// CHECK:      return %[[ARG]] : !torch.vtensor<[64],f32>
+func.func @torch.prims.convert_element_type$fold(%arg0: !torch.vtensor<[64],f32>) -> !torch.vtensor<[64],f32> {
+  %int6 = torch.constant.int 6
+  %0 = torch.prims.convert_element_type %arg0, %int6 : !torch.vtensor<[64],f32>, !torch.int -> !torch.vtensor<[64],f32>
+  return %0 : !torch.vtensor<[64],f32>
+}
+
+// -----
+
+// CHECK-LABEL:   func.func @torch.prims.convert_element_type$no_fold(
+// CHECK:            %[[ARG:.*]]: !torch.vtensor<[64],f32>) -> !torch.vtensor<[64],si32> {
+// CHECK:      %[[RET:.*]] = torch.prims.convert_element_type %[[ARG]], %{{.*}} : !torch.vtensor<[64],f32>, !torch.int -> !torch.vtensor<[64],si32>
+// CHECK:      return %[[RET]] : !torch.vtensor<[64],si32>
+func.func @torch.prims.convert_element_type$no_fold(%arg0: !torch.vtensor<[64],f32>) -> !torch.vtensor<[64],si32> {
+  %int6 = torch.constant.int 6
+  %0 = torch.prims.convert_element_type %arg0, %int6 : !torch.vtensor<[64],f32>, !torch.int -> !torch.vtensor<[64],si32>
+  return %0 : !torch.vtensor<[64],si32>
+}
+
+// -----
+
+// CHECK-LABEL:   @torch.aten.max_pool2d_with_indices$canonicalize(
+// CHECK:            %[[ARG:.*]]: !torch.vtensor<[10,64,112,112],f32>) -> !torch.vtensor<[10,64,56,56],f32> {
+// CHECK:      %[[RET:.*]] = torch.aten.max_pool2d %[[ARG]]
+// CHECK:      return %[[RET]] : !torch.vtensor<[10,64,56,56],f32>
+func.func @torch.aten.max_pool2d_with_indices$canonicalize(%arg0: !torch.vtensor<[10,64,112,112],f32>) -> !torch.vtensor<[10,64,56,56],f32> {
+  %false = torch.constant.bool false
+  %int1 = torch.constant.int 1
+  %int2 = torch.constant.int 2
+  %int3 = torch.constant.int 3
+  %29 = torch.prim.ListConstruct %int3, %int3 : (!torch.int, !torch.int) -> !torch.list<int>
+  %30 = torch.prim.ListConstruct %int2, %int2 : (!torch.int, !torch.int) -> !torch.list<int>
+  %31 = torch.prim.ListConstruct %int1, %int1 : (!torch.int, !torch.int) -> !torch.list<int>
+  %result0, %result1 = torch.aten.max_pool2d_with_indices %arg0, %29, %30, %31, %31, %false : !torch.vtensor<[10,64,112,112],f32>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.list<int>, !torch.bool -> !torch.vtensor<[10,64,56,56],f32>, !torch.vtensor<[10,64,56,56],si64>
+  return %result0 : !torch.vtensor<[10,64,56,56],f32>
+}