descriptor.coordinates.organisation.set('org-ぴ₦ガき∆ç√∫')
        descriptor.coordinates.module.set('module-<tag attrib="value"/>-markup')
        descriptor.coordinates.revision.set('version-&"')

        then:
        with (ivyXml) {
            info.@organisation == 'org-ぴ₦ガき∆ç√∫'
            info.@module == 'module-<tag attrib="value"/>-markup'
            info.@revision == 'version-&"'
        }
    }

    return func_.emitWarning()
           << "Invalid number of results from " << kMaxUnpooling << ": "
           << func_.getFunctionType().getNumResults();
  }

  auto attrs = attr_.getAttrs();

  if (failed(HasIntegerArrayWithSize(&func_, attrs, "pool_size", 2))) {
    return failure();
  }

  if (failed(HasIntegerArrayWithSize(&func_, attrs, "strides", 2))) {
    return failure();

                 StringAttr::get(func_.getContext(), kCustomSSDPostprocessing));

  OpBuilder builder(func_.getBody());
  std::string custom_option_buffer;
  if (failed(CreateNMSCustomOptions(func_, attr_.getAttrs(),
                                    custom_option_buffer))) {
    return failure();
  }
  auto op = builder.create<CustomOp>(
      func_.getLoc(), func_.getFunctionType().getResults(),

                       .getLeafReference()
                       .getValue());
    // Remove the attribute from the instruction as it is already converted to
    // op_name.
    auto attr_id = mlir::StringAttr::get(inst->getContext(), "f");
    inst->removeAttr(attr_id);
  } else {
    // Some control flow ops in TensorFlow Graph have their respective "Ref" ops
    // as well. For example there is Enter and RefEnter op. RefEnter forwards

LogicalResult ConvertToI32Attr(IntegerAttr attr, IntegerAttr* attr_i32) {
  if (attr.getType().isInteger(/*width=*/32)) {
    *attr_i32 = attr;
    return success();
  }

  int64_t value = attr.getInt();
  if (value > std::numeric_limits<int>::max() ||
      value < std::numeric_limits<int>::min()) {
    return failure();
  }

  *attr_i32 = IntegerAttr::get(

        string_attr.getValue() == kNullAttributeValue) {
      continue;
    }

    if (std::find_if(
            attr_to_op_map.begin(), attr_to_op_map.end(), [&](auto attr_op) {
              return std::get<0>(attr_op).getName() == attribute.getName();
            }) == attr_to_op_map.end()) {
      emitError(UnknownLoc::get(&context),
                "Could not find attribute: " + attribute.getName().str());

      tensorflow::Tensor tensor(list->element_dtype,
                                tensorflow::TensorShape(result_shape));
      auto attr_or = tensorflow::ConvertTensor(tensor, &rewriter);
      if (!attr_or.ok()) return failure();
      rewriter.replaceOpWithNewOp<TF::ConstOp>(op, attr_or.value());
      return success();
    }

    // Extract individual tensor list element and combine them using the tf.Pack
    // op.

LogicalResult ConvertToI32Attr(IntegerAttr attr, IntegerAttr* attr_i32) {
  if (attr.getType().isInteger(/*width=*/32)) {
    *attr_i32 = attr;
    return success();
  }

  int64_t value = attr.getInt();
  if (value > std::numeric_limits<int>::max() ||
      value < std::numeric_limits<int>::min()) {
    return failure();
  }

  *attr_i32 = IntegerAttr::get(

	claims[ldapUser] = ldapUserDN
	claims[ldapActualUser] = ldapActualUserDN
	claims[ldapUserN] = ldapUsername
	// Add lookup up LDAP attributes as claims.
	for attrib, value := range lookupResult.Attributes {
		claims[ldapAttribPrefix+attrib] = value
	}

	secret, err := getTokenSigningKey()
	if err != nil {
		writeSTSErrorResponse(ctx, w, ErrSTSInternalError, err)
		return
	}

		$2 ~ /^GENL_/ ||
		$2 ~ /^STATX_/ ||
		$2 ~ /^RENAME/ ||
		$2 ~ /^UBI_IOC[A-Z]/ ||
		$2 ~ /^UTIME_/ ||
		$2 ~ /^XATTR_(CREATE|REPLACE|NO(DEFAULT|FOLLOW|SECURITY)|SHOWCOMPRESSION)/ ||
		$2 ~ /^ATTR_(BIT_MAP_COUNT|(CMN|VOL|FILE)_)/ ||
		$2 ~ /^FSOPT_/ ||
		$2 ~ /^WDIO[CFS]_/ ||
		$2 ~ /^NFN/ ||
		$2 !~ /^NFT_META_IIFTYPE/ &&
		$2 ~ /^NFT_/ ||
		$2 ~ /^NF_NAT_/ ||
		$2 ~ /^XDP_/ ||
		$2 ~ /^RWF_/ ||