message Metadata {
    //  Bit number of fixed-point data the target kernel supports.
    int32 num_bits = 1;
    //  The quantized axis index if it is per-axis quantization.
    int32 quantize_axis = 2;
    // The minimum allowed value of the fixed-point data range.
    // This can also be used to derive the sign of storage type.
    int32 range_min = 3;
    // The minimum allowed value of the fixed-point data range.

    axis_stats = DenseFPElementsAttr::get(
        RankedTensorType::get(axis_stats_shape, b.getF32Type()), min_maxs);
    axis = b.getI64IntegerAttr(info.meta().quantize_axis());
  }

  b.setInsertionPointAfter(op);
  if (IsQuantizableResult(op, index)) {
    InsertStatsOpAtResult(b, op->getResult(index), layer_stats, axis_stats,
                          axis);
  } else {

                            tensor_shape_pb2.TensorShapeProto.Dim(
                                size=filter_shape[quantized_axis]
                            )
                        ]
                    )
                ]
            )
        )
      else:
        quantized_axis = -1
        # Empty dimension. Per-tensor quantization has singular channel.