[6]*argField{ap_MMAReg_38_40, ap_VecSReg_61_61_43_47, ap_VecSReg_62_62_48_52, ap_ImmUnsigned_24_27, ap_ImmUnsigned_28_31, ap_ImmUnsigned_16_17}},

    int64_t rank = lhs_type.getRank();
    auto batch_dimensions = llvm::to_vector<4>(llvm::seq<int64_t>(0, rank - 2));
    auto lhs_contracting_dimensions = llvm::to_vector<4>(
        llvm::ArrayRef({op.getAdjX() ? rank - 2 : rank - 1}));
    auto rhs_contracting_dimensions = llvm::to_vector<4>(
        llvm::ArrayRef({op.getAdjY() ? rank - 1 : rank - 2}));

    /** The key of the configuration. e.g. 200 */
    String RANK_FUSION_window_size = "rank.fusion.window_size";

    /** The key of the configuration. e.g. 20 */
    String RANK_FUSION_rank_constant = "rank.fusion.rank_constant";

    /** The key of the configuration. e.g. -1 */
    String RANK_FUSION_THREADS = "rank.fusion.threads";

    /** The key of the configuration. e.g. rf_score */

}

// CHECK-LABEL: @FuseReshapeAroundBMMNagativeTest2
// Checks that the pattern matcher FuseReshapesAroundBatchMatMulLHS does not get
// applied for this case that does not pass the constraint around input rank.
func.func @FuseReshapeAroundBMMNagativeTest2(%arg0: tensor<2x1536xf32>) -> tensor<2x768xf32> {
  %cst = arith.constant dense_resource<__elided__> : tensor<3xi32>
  %cst_0 = arith.constant dense_resource<__elided__> : tensor<2xi32>