"    signature {"
      "      name: 'AddVariablesFunction'"
      "      input_arg {"
      "        name: 'var'"
      "        type: DT_RESOURCE"
      "      }"
      "      output_arg {"
      "        name: 'sum'"
      "        type: DT_FLOAT"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read0'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"

inline bool IsDtypeTrainable(DataType dtype) {
  switch (dtype) {
    case DT_HALF:
    case DT_BFLOAT16:
    case DT_FLOAT:
    case DT_DOUBLE:
    case DT_COMPLEX64:
    case DT_COMPLEX128:
    case DT_RESOURCE:
    case DT_VARIANT:
      return true;
    case DT_QINT8:
    case DT_QINT16:
    case DT_QINT32:
    case DT_QUINT8:
    case DT_QUINT16:
      return tensorflow::flags::Global()

                                }
                                final Date dt = FessFunctions.parseDate(values[0], dateFormate);
                                if (dt != null) {
                                    dataMap.put(mapping.getValue1(), FessFunctions.formatDate(dt));
                                } else {
                                    logger.warn("Failed to parse {}", mapping);

namespace tensorflow {
namespace {

Status ValidateNonRefOutput(const Node* node, int idx) {
  const DataType& dt = node->output_type(idx);
  return IsRefType(dt)
             ? InvalidArgument("Output ", idx, " of node '", node->name(),
                               "' has a reference type ", DataTypeString(dt))
             : absl::OkStatus();
}

// Converts `ninputs` and `inputs` into `inputs_tensors` and `input_nodes` and

 *
 * <dl>
 *   <dt>The IPv4 loopback address, {@code "127.0.0.1"}.
 *   <dd>{@code 7f 00 00 01}
 *   <dt>The IPv6 loopback address, {@code "::1"}.
 *   <dd>{@code 00 00 00 00 00 00 00 00 00 00 00 00 00 00 00 01}
 *   <dt>From the IPv6 reserved documentation prefix ({@code 2001:db8::/32}), {@code "2001:db8::1"}.
 *   <dd>{@code 20 01 0d b8 00 00 00 00 00 00 00 00 00 00 00 01}

  const tensorflow::Tensor& arg_tensor = cc_ctx->input(index);
  absl::Status cc_status;
  if (arg_tensor.dtype() != tensorflow::DT_RESOURCE) {
    cc_status = absl::InvalidArgumentError(
        absl::StrCat("Trying to obtain resource handle from Input[", index,
                     "], which is not type DT_RESOURCE."));
    status->status = cc_status;
    return nullptr;
  }
  const tensorflow::ResourceHandle& handle =

  }
}

void ParallelDevice::AsyncWait(TFE_Context* context, TF_Status* status) const {
  StatusPtr first_bad_status(nullptr);

  for (const auto& dt : device_threads_) {
    StatusPtr async_wait_status(TF_NewStatus());
    dt->AsyncWait(async_wait_status.get());
    // Prefer non cancelled errors to uncover real failures.
    if (TF_GetCode(async_wait_status.get()) != TF_OK &&

      DataTypeIsInteger(BaseType(dtype))) {
    return tensorflow::ops::Identity(ctx, input, output, name);
  } else if (!DataTypeIsComplex(BaseType(dtype)) &&
             BaseType(dtype) != DT_VARIANT) {
    return errors::InvalidArgument(
        "Expected numeric or variant tensor, got dtype ", dtype);
  }
  return tensorflow::ops::Conj(ctx, input, output, name);
}

			if !ok {
				d = bandwidth.Details{
					LimitInBytesPerSecond: report.BucketStats[opts].LimitInBytesPerSecond,
				}
			}
			dt, ok := report.BucketStats[opts]
			if ok {
				d.CurrentBandwidthInBytesPerSecond += dt.CurrentBandwidthInBytesPerSecond
			}
			consolidatedReport.BucketStats[opts] = d
		}
	}
	return consolidatedReport
}

DEFAULT_KIND_IMAGE="gcr.io/istio-testing/kind-node:v1.28.4"

# COMMON_SCRIPTS contains the directory this file is in.
COMMON_SCRIPTS=$(dirname "${BASH_SOURCE:-$0}")

function log() {
  echo -e "$(date -u '+%Y-%m-%dT%H:%M:%S.%NZ')\t$*"
}

function retry() {
  local n=1
  local max=5
  local delay=5
  while true; do
    "$@" && break
    if [[ $n -lt $max ]]; then
      ((n++))