diff --git a/lib/Dialect/mhlo/IR/hlo_ops.cc b/lib/Dialect/mhlo/IR/hlo_ops.cc
index 20a255f..a0f63c9 100644
--- a/lib/Dialect/mhlo/IR/hlo_ops.cc
+++ b/lib/Dialect/mhlo/IR/hlo_ops.cc
@@ -898,6 +898,7 @@ static LogicalResult Verify(DynamicBroadcastInDimOp op) {
   return success();
 }
 
+namespace {
 // If a DynamicBroadCastInDimOp is not actually dynamic, use an ordinary
 // BroadcastInDimOp.
 class DynamicBroadcastInDimOpNotActuallyDynamic
@@ -915,9 +916,40 @@ class DynamicBroadcastInDimOpNotActuallyDynamic
   }
 };
 
+class ChainedDynamicBroadcastInDimCanonicalization
+    : public OpRewritePattern<DynamicBroadcastInDimOp> {
+  using OpRewritePattern::OpRewritePattern;
+  LogicalResult matchAndRewrite(DynamicBroadcastInDimOp bcast,
+                                PatternRewriter& rewriter) const override {
+    auto preceding_bcast =
+        bcast.operand().getDefiningOp<DynamicBroadcastInDimOp>();
+    if (!preceding_bcast) return failure();
+
+    // Compose broadcast dimensions.
+    DenseIntElementsAttr preceding_bcast_dims =
+        preceding_bcast.broadcast_dimensions();
+    DenseIntElementsAttr bcast_dims = bcast.broadcast_dimensions();
+    SmallVector<APInt, 4> composition;
+    for (APInt preceding_dim : preceding_bcast_dims) {
+      auto composed_dim = bcast_dims.getValue({preceding_dim.getZExtValue()})
+                              .cast<IntegerAttr>();
+      composition.push_back(composed_dim.getValue());
+    }
+    auto composed_bcast_dims =
+        DenseIntElementsAttr::get(preceding_bcast_dims.getType(), composition);
+
+    rewriter.replaceOpWithNewOp<DynamicBroadcastInDimOp>(
+        bcast, bcast.getType(), preceding_bcast.operand(),
+        bcast.output_dimensions(), composed_bcast_dims);
+    return success();
+  }
+};
+}  // namespace
+
 void DynamicBroadcastInDimOp::getCanonicalizationPatterns(
     OwningRewritePatternList& results, MLIRContext* context) {
-  results.insert<DynamicBroadcastInDimOpNotActuallyDynamic,
+  results.insert<ChainedDynamicBroadcastInDimCanonicalization,
+                 DynamicBroadcastInDimOpNotActuallyDynamic,
                  DynamicBroadcastToOwnShape_1, DynamicBroadcastToOwnShape_2,
                  DynamicBroadcastToOwnShape_3, DynamicBroadcastToOwnShape_4>(
       context);
diff --git a/tests/move_up_dynamic_broadcasts_for_fusion.mlir b/tests/move_up_dynamic_broadcasts_for_fusion.mlir
index 86e73b9..8f0401d 100644
--- a/tests/move_up_dynamic_broadcasts_for_fusion.mlir
+++ b/tests/move_up_dynamic_broadcasts_for_fusion.mlir
@@ -300,12 +300,10 @@ func @sub_sub(%arg0: tensor<?x32xf16>, %arg1 : tensor<?x32xf16>,
   // CHECK:      %[[ASSUMING_RESULTS:.*]]:4 = shape.assuming %[[WITNESS]]
   // CHECK-SAME: {
   // CHECK:        %[[BCASTED_SHAPE01:.*]] = shape.broadcast %[[SHAPE0]], %[[SHAPE1]]
-  // CHECK:        %[[PARTIALLY_BCASTED_ARG0:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG0]], %[[BCASTED_SHAPE01]]) {broadcast_dimensions = dense<[0, 1]>
-  // CHECK:        %[[PARTIALLY_BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG1]], %[[BCASTED_SHAPE01]]) {broadcast_dimensions = dense<[0, 1]>
   // CHECK:        %[[BCASTED_SHAPE012:.*]] = shape.broadcast %[[SHAPE2]], %[[BCASTED_SHAPE01]]
   // CHECK:        %[[BCASTED_ARG2:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG2]], %[[BCASTED_SHAPE012]]) {broadcast_dimensions = dense<[0, 1, 2]>
-  // CHECK:        %[[BCASTED_ARG0:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[PARTIALLY_BCASTED_ARG0]], %[[BCASTED_SHAPE012]]) {broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>}
-  // CHECK:        %[[BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[PARTIALLY_BCASTED_ARG1]], %[[BCASTED_SHAPE012]]) {broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>}
+  // CHECK:        %[[BCASTED_ARG0:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG0]], %[[BCASTED_SHAPE012]]) {broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>}
+  // CHECK:        %[[BCASTED_ARG1:.*]] = "mhlo.dynamic_broadcast_in_dim"(%[[ARG1]], %[[BCASTED_SHAPE012]]) {broadcast_dimensions = dense<[1, 2]> : tensor<2xi64>}
   // CHECK:        %[[TMP:.*]] = mhlo.subtract %[[BCASTED_ARG0]], %[[BCASTED_ARG1]]
   // CHECK:        %[[RESULT:.*]] = mhlo.subtract %[[BCASTED_ARG2]], %[[TMP]]
   // CHECK:        shape.assuming_yield %{{.*}}, %{{.*}}, %{{.*}}, %[[RESULT]]