SmallVector<int32_t> initial_permutation;
  DenseElementsAttr perm1_const;

  SmallVector<int32_t> new_permutation;
  if (matchPattern(permutation1, m_Constant(&perm1_const))) {
    for (int32_t idx = 0; idx < perm1_const.getNumElements(); ++idx) {
      initial_permutation.push_back(idx);
    }
    for (auto perm : perm2_const.getValues<APInt>()) {

  // a dilated conv.
  auto stb_paddings = stb_op.getPaddings();
  auto bts_crops = bts_op.getCrops();
  ElementsAttr stb_paddings_attr, bts_crops_attr;
  if (!matchPattern(stb_paddings, m_Constant(&stb_paddings_attr)) ||
      !matchPattern(bts_crops, m_Constant(&bts_crops_attr))) {
    return rewriter.notifyMatchFailure(
        op,
        "either SpaceToBatchND or BatchToSpaceND "
        "doesn't have constant padding/crops value");
  }

  ElementsAttr k;
  if (!matchPattern(tf_matrix_diag_v2_or_v3_op.getK(), m_Constant(&k)))
    return false;
  if (ExtractSingleElementAsInteger(k).getInt() != 0) return false;

  // Extract num_rows constant tensor and check value = -1.
  ElementsAttr num_rows;
  if (!matchPattern(tf_matrix_diag_v2_or_v3_op.getNumRows(),
                    m_Constant(&num_rows)))
    return false;

                                   DenseIntElementsAttr& replica_groups,
                                   Operation* op) {
  DenseIntElementsAttr group_assignment;
  if (!matchPattern(group_assignment_value, m_Constant(&group_assignment))) {
    return op->emitOpError() << "expects constant group_assignment";
  }
  replica_groups = mlir::cast<DenseIntElementsAttr>(

  const bool kIsNarrowRange = true;
  const bool kIsSigned = true;
  const int kBitWidth = 8;

  DenseFPElementsAttr attr;
  if (!matchPattern(op->getResult(0), m_Constant(&attr))) return nullptr;

  QuantizedType quant_type = mlir::dyn_cast<quant::QuantizedType>(
      quant::GetUniformQuantizedTypeForWeight(
          attr, /*symmetric=*/kIsNarrowRange && kIsSigned, kBitWidth, kIsSigned,

    DenseIntElementsAttr value_attr;
    if (!matchPattern(value, m_Constant(&value_attr)) ||
        !value_attr.isSplat()) {
      return false;
    }
    splat_value = value_attr.getSplatValue<T>();
    return true;
  }

  DenseFPElementsAttr value_attr;
  if (!matchPattern(value, m_Constant(&value_attr)) || !value_attr.isSplat()) {
    return false;
  }

  mlir::DenseIntElementsAttr splits_attr;
  if (!splits || !matchPattern(splits, m_Constant(&splits_attr)))
    return failure();

  auto split_dim = splitv_op.getSplitDim().getDefiningOp();
  mlir::ElementsAttr split_dim_attr;
  if (!split_dim || !matchPattern(split_dim, m_Constant(&split_dim_attr)))
    return failure();

  auto input = splitv_op.getValue();

// data so that the iota dimension does not need to be the (inner) z-dimension.
bool MatchIotaConst(DenseIntElementsAttr dimensions, Value iota) {
  DenseIntElementsAttr iota_const_attr;
  if (!matchPattern(iota, m_Constant(&iota_const_attr))) return false;

  auto iota_type = iota_const_attr.getType();
  auto iota_shape = iota_type.getShape();
  auto reduce_dim = (*dimensions.value_begin<APInt>()).getSExtValue();

            op->getOperand(qi).getDefiningOp());
        if (!const_op) {
          continue;
        }

        DenseFPElementsAttr attr;
        if (!matchPattern(const_op->getResult(0), m_Constant(&attr))) {
          continue;
        }

        if (mlir::dyn_cast<DenseFPElementsAttr>(attr).size() >=
            quant_specs_.minimum_elements_for_weights) {
          continue;
        }

  DenseFPElementsAttr scales;
  if (!matchPattern(scales_value, m_Constant(&scales))) {
    return rewriter.notifyMatchFailure(op, "scales must be constant");
  }

  // Check whether the zero_points operand has constant op.
  DenseIntElementsAttr zero_points;
  if (!matchPattern(zero_points_value, m_Constant(&zero_points))) {
    return rewriter.notifyMatchFailure(op, "zero_points must be constant");
  }