options.enable_per_channel_quantized_weight_ = true;
  // For debugging purposes.
  options.mlir_dump_file_name_ = "quantize_composite_functions";
  options.merge_fusion_with_dequantize_ =
      pipeline_config.merge_fusion_with_dequantize();

  AddShapeLegalizationPasses(pm);
  pm.addNestedPass<func::FuncOp>(
      CreateConvertCustomAggregationOpToQuantStatsPass());

    Option<"mlir_dump_file_name_", "mlir-dump-file-name",
        "std::optional<std::string>", /*default=*/"std::nullopt",
        "MLIR dump file name.">,
    Option<"merge_fusion_with_dequantize_",
        "merge-fusion-with-dequantize",
        "bool", /*default=*/"false",
        "Whether to merge quantized conv/dot_general fusion with subsequent dequantize.">,
  ];
  let dependentDialects = [

              ([2, 3, 1, 1024], [2, 3, 1024, 3]),
          ),
          'merge_fusion_with_dequantize': (False, True),
      }])
  )
  @test_util.run_in_graph_and_eager_modes
  def test_matmul_ptq_model(
      self,
      bias_fn: Optional[ops.Operation],
      activation_fn: Optional[ops.Operation],
      dim_sizes: Sequence[int],
      merge_fusion_with_dequantize: bool,
  ):
    lhs_dim_size, rhs_dim_size = dim_sizes

  // subsequent dequantize op if present.
  // Default value: false
  // TODO: b/321729008 - re-consider default value after testing on prod model.
  bool merge_fusion_with_dequantize = 2;
}

// Represents a single quantizable unit, a (nearly) minimum unit of work when
// applying quantization. It may correspond to a single or multiple ops.
// Next ID: 2
message QuantizableUnit {