// Figure out output shapes.
  SmallVector<int64_t, 4> concat_out_shape;
  SmallVector<int64_t, 4> pack_out_shape;

  const int64_t rank = input_type.getRank();
  int64_t pack_axis = pack_op.getAxis();
  size_t count = pack_inputs.size();
  if (pack_axis < 0) {
    pack_axis += rank;
  }

  // Concat out shape.
  for (int i = 0; i < rank; ++i) {
    int64_t dim_size = input_type.getDimSize(i);

  auto values = tf_concat_op.getValues();
  auto output_type = tf_concat_op.getOutput().getType();
  // Extract axis attribute from constant axis tensor
  ElementsAttr axis;
  if (!matchPattern(tf_concat_op.getAxis(), m_Constant(&axis)))
    return failure();
  IntegerAttr axis_int = ExtractSingleElementAsInteger(axis);

  // "axis" operand could be a i64 tensor. Resolve it here.
  IntegerAttr axis_i32;

        }
        TensorRangeSanityCheck(op, rmin, rmax);
        mins.push_back(rmin);
        maxs.push_back(rmax);
      }
      quant_type = quantfork::fakeQuantAttrsToType(
          op.getLoc(), num_bits, *op.getAxis(), mins, maxs, narrow_range,
          expressed, is_signed);
      if (legacy_float_scale) {
        quant_type = DownCastScale(quant_type, mins, maxs, op->getLoc());
      }
    } else if (auto stats =