# This workflow should touch no issues, so times are set to -1
          # (see actions/stale documentation for the behavior)
          days-before-issue-stale: -1
          stale-issue-label: stale
          stale-issue-message: >
            **BUG!** This issue should not be marked stale by the "stale" workflow.
            Please report it to @gradle/bt-support team
          days-before-issue-close: -1

          days-before-issue-stale: 14
          stale-issue-label: to-triage
          stale-issue-message: ""
          days-before-issue-close: -1

          only-pr-labels: 'from:contributor'
          exempt-all-pr-milestones: true
          days-before-pr-stale: 14
          stale-pr-label: to-triage
          stale-pr-message: ""

				// Following check is for situations
				// when Writes() scale higher than Reads()
				// - practically speaking this never happens
				// and should never happen - however it has
				// been seen recently due to hardware issues
				// causes Reads() to go slower than Writes().
				//
				// Send such results anyways as this shall
				// expose a problem underneath.
				if totalPut > throughputHighestPut {

                       absl::Span<AbstractTensorHandle*> outputs) {
  PartialTensorShape shape;
  TF_RETURN_IF_ERROR(inputs[0]->Shape(&shape));
  if (shape.dims() != 0) {
    return errors::InvalidArgument(
        "Tensor expected to have scalar shape found rank: ", shape.dims());
  }
  return absl::OkStatus();
}

TEST_P(UnifiedAPI, TestTensorShapeScalar) {
  if (UseFunction() && UseMlir()) {

namespace tensorflow {

std::string AbstractTensorHandle::DebugString() const {
  PartialTensorShape shape;
  Status s = Shape(&shape);
  std::string shape_string;
  if (!s.ok()) {
    shape_string = "<error computing shape>";
  } else {
    shape_string = shape.DebugString();
  }
  return absl::StrCat("TensorHandle(shape=", shape_string,
                      ", dtype=", DataType_Name(DataType()),

proxy1     cluster1     STALE        SYNCED      SYNCED      NOT SENT     SYNCED       istiod1     1.20
proxy2     cluster2     STALE        SYNCED      STALE       SYNCED       STALE        istiod2     1.19
proxy3     cluster3     NOT SENT     ERROR       STALE       NOT SENT     NOT SENT     istiod3     1.20

						clusterID:      "cluster2",
						version:        "1.19",
						cdsSyncStatus:  status.ConfigStatus_STALE,
						ldsSyncStatus:  status.ConfigStatus_SYNCED,
						rdsSyncStatus:  status.ConfigStatus_SYNCED,
						edsSyncStatus:  status.ConfigStatus_STALE,
						ecdsSyncStatus: status.ConfigStatus_STALE,
					},
				}),
				"istiod3": xdsResponseInput("istiod3", []clientConfigInput{
					{
						proxyID:        "proxy3",

namespace tensorflow {

std::string ImmediateExecutionTensorHandle::DebugString() const {
  PartialTensorShape shape;
  std::string shape_string;
  if (Shape(&shape).ok()) {
    shape_string = shape.DebugString();
  } else {
    shape_string = "<error computing shape>";
  }
  std::string value_string;
  if (!SummarizeValue(value_string).ok()) {
    value_string = "<error computing value>";
  }

    return nullptr;
  }
  tensorflow::PartialTensorShape partial_shape;
  if (shape.num_dims != -1) {
    DCHECK(shape.dim_sizes != nullptr);
    Status status = tensorflow::PartialTensorShape::MakePartialShape(
        reinterpret_cast<int64_t*>(shape.dim_sizes), shape.num_dims,
        &partial_shape);
    if (!status.ok()) {
      tsl::Set_TF_Status_from_Status(s, status);
      return nullptr;

**NOTE:**

- All the nodes running distributed MinIO should share a common root credentials, for the nodes to connect and trust each other. To achieve this, it is **recommended** to export root user and root password as environment variables, `MINIO_ROOT_USER` and `MINIO_ROOT_PASSWORD`, on all the nodes before executing MinIO server command. If not exported, default `minioadmin/minioadmin` credentials shall be used.