diff --git a/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp b/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
index bf606b22d30a..960ba274e6dd 100644
--- a/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
+++ b/lib/Dialect/Torch/Transforms/DecomposeComplexOps.cpp
@@ -834,6 +834,68 @@ class DecomposeAtenRepeatOp : public OpRewritePattern<AtenRepeatOp> {
 };
 } // namespace
 
+// Decompose aten.flatten.using_ints into aten.view op.
+namespace {
+class DecomposeAtenFlattenUsingIntsOp
+    : public OpRewritePattern<AtenFlattenUsingIntsOp> {
+public:
+  using OpRewritePattern::OpRewritePattern;
+  LogicalResult matchAndRewrite(AtenFlattenUsingIntsOp op,
+                                PatternRewriter &rewriter) const override {
+    Location loc = op.getLoc();
+    Value self = op.self();
+    MLIRContext *context = op.getContext();
+    int64_t rank = getTensorRank(self);
+    if (rank < 0)
+      return rewriter.notifyMatchFailure(op, "unimplemented: unranked tensor");
+
+    int64_t start, end;
+    if (!matchPattern(op.start_dim(), m_TorchConstantInt(&start)) ||
+        !matchPattern(op.end_dim(), m_TorchConstantInt(&end))) {
+      return rewriter.notifyMatchFailure(
+          op, "unimplemented: requires start and end dims to be constants");
+    }
+
+    SmallVector<Value, 4> newSizes;
+    if (rank == 0) {
+      Value one =
+          rewriter.create<ConstantIntOp>(loc, rewriter.getI64IntegerAttr(1));
+      newSizes.push_back(one);
+    } else {
+      start = toPositiveDim(start, rank);
+      end = toPositiveDim(end, rank);
+
+      if (start > end) {
+        return rewriter.notifyMatchFailure(
+            op, "expected end dim larger than start dim");
+      }
+
+      newSizes.reserve(rank - end + start);
+      for (size_t k = 0; k < start; ++k) {
+        Value dim =
+            rewriter.create<ConstantIntOp>(loc, rewriter.getI64IntegerAttr(k));
+        newSizes.push_back(
+            rewriter.create<AtenSizeIntOp>(loc, self, /*dim=*/dim));
+      }
+      Value flattenDimSize =
+          rewriter.create<ConstantIntOp>(loc, rewriter.getI64IntegerAttr(-1));
+      newSizes.push_back(flattenDimSize);
+      for (size_t k = end + 1; k < rank; ++k) {
+        Value dim =
+            rewriter.create<ConstantIntOp>(loc, rewriter.getI64IntegerAttr(k));
+        newSizes.push_back(
+            rewriter.create<AtenSizeIntOp>(loc, self, /*dim=*/dim));
+      }
+    }
+    Value newSizeList = rewriter.create<PrimListConstructOp>(
+        loc, ListType::get(IntType::get(context)), newSizes);
+    rewriter.replaceOpWithNewOp<AtenViewOp>(op, op.getType(), op.self(),
+                                            newSizeList);
+    return success();
+  }
+};
+} // namespace
+
 // Decompose aten.expand into aten.broadcast_to op.
 namespace {
 class DecomposeAtenExpandOp : public OpRewritePattern<AtenExpandOp> {
@@ -2497,6 +2559,8 @@ class DecomposeComplexOpsPass
     target.addIllegalOp<AtenRepeatOp>();
     patterns.add<DecomposeAtenExpandOp>(context);
     target.addIllegalOp<AtenExpandOp>();
+    patterns.add<DecomposeAtenFlattenUsingIntsOp>(context);
+    target.addIllegalOp<AtenFlattenUsingIntsOp>();
     patterns.add<DecomposeAtenWhereScalarOp>(context);
     target.addIllegalOp<AtenWhereScalarOp>();
     patterns.add<DecomposeAtenWhereScalarOtherOp>(context);
diff --git a/python/torch_mlir/__init__.py b/python/torch_mlir/__init__.py
index e6bbd7e0b4fd..2a716d3927ce 100644
--- a/python/torch_mlir/__init__.py
+++ b/python/torch_mlir/__init__.py
@@ -126,8 +126,8 @@ def like(tensor: torch.Tensor, dynamic_axes: List[int] = None):
 # ops in the backend contract, and move these lists somewhere deeper in the
 # compiler where each backend can "own" its set of legal ops.
 BACKEND_LEGAL_OPS = {
-    OutputType.TOSA: [],
-    OutputType.LINALG_ON_TENSORS: [],
+    OutputType.TOSA: ['torch.aten.flatten.using_ints',],
+    OutputType.LINALG_ON_TENSORS: ['torch.aten.flatten.using_ints',],
     OutputType.MHLO: [],
 }
 
diff --git a/test/Dialect/Torch/decompose-complex-ops.mlir b/test/Dialect/Torch/decompose-complex-ops.mlir
index 8c37005db913..60d5589ec24d 100644
--- a/test/Dialect/Torch/decompose-complex-ops.mlir
+++ b/test/Dialect/Torch/decompose-complex-ops.mlir
@@ -202,8 +202,10 @@ func.func @torch.aten.argmax(%arg0: !torch.vtensor<[?,?],f32>) -> !torch.vtensor
 // CHECK:           %[[FALSE:.*]] = torch.constant.bool false
 // CHECK:           %[[CST0:.*]] = torch.constant.int 0
 // CHECK:           %[[CST1:.*]] = torch.constant.int 1
-// CHECK:           %[[FLATTEN:.*]] = torch.aten.flatten.using_ints %[[INP]], %[[CST0]], %[[CST1]] :
-// CHECK-SAME:         !torch.vtensor<[?,?],f32>, !torch.int, !torch.int -> !torch.vtensor<[?],f32>
+// CHECK:           %[[CST:.*]]-1 = torch.constant.int -1
+// CHECK:           %[[T0:.*]] = torch.prim.ListConstruct %[[CST]]-1 : (!torch.int) -> !torch.list<int>
+// CHECK:           %[[FLATTEN:.*]] = torch.aten.view %[[INP]], %[[T0]] :
+// CHECK-SAME:         !torch.vtensor<[?,?],f32>, !torch.list<int> -> !torch.vtensor<[?],f32>
 // CHECK:           %[[VAL:.*]], %[[IND:.*]] = torch.aten.max.dim %[[FLATTEN]], %[[CST0]], %[[FALSE]] :
 // CHECK-SAME:         !torch.vtensor<[?],f32>, !torch.int, !torch.bool -> !torch.vtensor<[],f32>, !torch.vtensor<[],si64>
 // CHECK:           return %[[IND]] : !torch.vtensor<[],si64>
@@ -1332,3 +1334,19 @@ func.func @torch.aten.std.dim(%arg0: !torch.vtensor<[3,4,5],f32>) -> !torch.vten
   %0 = torch.aten.std.dim %arg0, %dims, %unbiased, %keepdim: !torch.vtensor<[3,4,5],f32>, !torch.list<int>, !torch.bool, !torch.bool -> !torch.vtensor<[3,4,1],f32>
   return %0 : !torch.vtensor<[3,4,1],f32>
 }
+
+// -----
+// CHECK-LABEL:  func.func @torch.aten.flatten.using_ints(
+// CHECK-SAME:                                            %[[ARG0:.*]]: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?],f32> {
+// CHECK:         %[[INT0:.*]] = torch.constant.int 0
+// CHECK:         %[[INT3:.*]] = torch.constant.int 3
+// CHECK:         %[[INT:.*]]-1 = torch.constant.int -1
+// CHECK:         %[[T0:.*]] = torch.prim.ListConstruct %[[INT]]-1 : (!torch.int) -> !torch.list<int>
+// CHECK:         %[[T1:.*]] = torch.aten.view %[[ARG0]], %[[T0]] : !torch.vtensor<[?,?,?,?],f32>, !torch.list<int> -> !torch.vtensor<[?],f32>
+// CHECK:         return %[[T1]] : !torch.vtensor<[?],f32>
+func.func @torch.aten.flatten.using_ints(%arg0: !torch.vtensor<[?,?,?,?],f32>) -> !torch.vtensor<[?],f32> {
+  %int0 = torch.constant.int 0
+  %int3 = torch.constant.int 3
+  %1 = torch.aten.flatten.using_ints %arg0, %int0, %int3: !torch.vtensor<[?,?,?,?],f32>, !torch.int, !torch.int -> !torch.vtensor<[?],f32>
+  return %1 : !torch.vtensor<[?],f32>
+}