// allocated to size `ninputs`. The caller should build `cond_graph` and
// `body_graph` starting from the inputs, and store the final outputs in
// `cond_output` and `body_outputs`.
//
// If `status` is OK, the caller must call either TF_FinishWhile or
// TF_AbortWhile on the returned TF_WhileParams. If `status` isn't OK, the
// returned TF_WhileParams is not valid, and the caller should not call

#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

// Return a tensor handle containing a float scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value);

// Return a tensor handle containing a int scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, int value);

// Return a tensor handle containing a bool scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, bool value);

#### Optimizations

A naive implementation would simply regenerate all resources, of all subscribed types, for each client, on any configuration change. However, this scales poorly. As a result, we have many levels of optimizations to avoid doing this work.

TF_Operation* ScalarConst(bool v, TF_Graph* graph, TF_Status* s,
                          const char* name = "scalar");

TF_Operation* ScalarConst(int32_t v, TF_Graph* graph, TF_Status* s,
                          const char* name = "scalar");

TF_Operation* ScalarConst(double v, TF_Graph* graph, TF_Status* s,
                          const char* name = "scalar");

TF_Operation* ScalarConst(float v, TF_Graph* graph, TF_Status* s,

1. [Standalone Deployment](#standalone-deployment)
2. [Distributed Deployment](#distributed-deployment)
3. [Cloud Scale Deployment](#cloud-scale-deployment)

## 1. Standalone Deployment

To host multiple tenants on a single machine, run one MinIO Server per tenant with a dedicated HTTPS port, configuration, and data directory.

  int num_dims_out = TF_NumDims(model_out_tensor);
  TF_DeleteTensor(model_out_tensor);

  // If the output is a scalar, then return the scalar output
  if (num_dims_out == 0) {
    outputs[0] = model_out.release();
    return absl::OkStatus();
  }

  // Else, reduce sum the output to get a scalar

  // Will sum all dimensions, so get a Tensor containing [0,...,num_dims_out-1].
  AbstractTensorHandlePtr sum_dims;
  {

	// Approx 49 days.
	MaxDeadline = time.Duration(math.MaxUint32) * time.Millisecond
)

// ContextDialer is a dialer that can be used to dial a remote.
type ContextDialer func(ctx context.Context, network, address string) (net.Conn, error)

// DialContext implements the Dialer interface.
func (c ContextDialer) DialContext(ctx context.Context, network, address string) (net.Conn, error) {
	return c(ctx, network, address)

			case reflect.String:
				vars[idx] = escaper + strings.ReplaceAll(fmt.Sprintf("%v", v), escaper, escaper+escaper) + escaper
			default:
				if v != nil && reflectValue.IsValid() && ((reflectValue.Kind() == reflect.Ptr && !reflectValue.IsNil()) || reflectValue.Kind() != reflect.Ptr) {
					vars[idx] = escaper + strings.ReplaceAll(fmt.Sprintf("%v", v), escaper, escaper+escaper) + escaper
				} else {
					vars[idx] = nullStr
				}
			}

### Creating the Scale-out Backup Repository

- Under the Backup Infrastructure view, click on Scale-out Repositories and click the Add Scale-out Repository button on the ribbon.

- Follow the on screen wizard

   * output.
   *
   * <p>This escaper does not treat surrogate pairs specially and does not perform Unicode
   * validation on its input.
   */
  public static Escaper xmlAttributeEscaper() {
    return XML_ATTRIBUTE_ESCAPER;
  }

  private static final Escaper XML_ESCAPER;
  private static final Escaper XML_CONTENT_ESCAPER;
  private static final Escaper XML_ATTRIBUTE_ESCAPER;

  static {