diff --git a/third_party/xla/xla/service/gpu/ir_emitter_triton.cc b/third_party/xla/xla/service/gpu/ir_emitter_triton.cc
index c190665f71e4e3..20f290e27ff18a 100644
--- a/third_party/xla/xla/service/gpu/ir_emitter_triton.cc
+++ b/third_party/xla/xla/service/gpu/ir_emitter_triton.cc
@@ -1942,18 +1942,15 @@ absl::Status EmitMatMul(mlir::OpBuilder builder,
   const HloInstruction* root = dot_instr->parent()->root_instruction();
   TF_RET_CHECK(!root->shape().IsTuple());
 
-  auto fusion_adaptor = HloFusionAdaptor::ForComputation(computation);
-  HloInstructionAdaptor instr_adaptor{*instr, fusion_adaptor.get()};
   // TODO(b/320659359) Allow TF32 for 8-bit or less types with F32.
-  bool is_8_bit_or_less_dot_with_F32 = HloAnyOf(
-      instr_adaptor.GetOperands(), *fusion_adaptor,
-      [&](HloInstructionAdaptor node) {
-        if (node.opcode() != HloOpcode::kConvert) {
+  bool is_unsupported_bitwidth =
+      HloAnyOf({dot_instr}, [&](const HloInstruction* node) {
+        if (node->opcode() != HloOpcode::kConvert) {
           return false;
         }
-        Type in_type =
-            TritonType(builder, node.GetOperand(0).shape().element_type());
-        Type out_type = TritonType(builder, node.shape().element_type());
+        auto in_type =
+            TritonType(builder, node->operand(0)->shape().element_type());
+        Type out_type = TritonType(builder, node->shape().element_type());
         return in_type.getIntOrFloatBitWidth() <= 8 && out_type.isF32();
       });
 
@@ -2168,7 +2165,7 @@ absl::Status EmitMatMul(mlir::OpBuilder builder,
       // lower precision than the output type. The change was introduced here:
       // https://github.com/openai/triton/commit/31b0c521427109a8eda609b58d756c380b21599a
       auto input_precision =
-          IsTf32Allowed(dot_instr) && !is_8_bit_or_less_dot_with_F32
+          IsTf32Allowed(dot_instr) && !is_unsupported_bitwidth
               ? mt::InputPrecision::TF32
               : mt::InputPrecision::IEEE;
       accumulator_next =