}

// Wrapper to restClient.CallWithMethod to handle network errors, in case of network error the connection is disconnected
// and a healthcheck routine gets invoked that would reconnect.
func (client *storageRESTClient) callGet(ctx context.Context, rpcMethod string, values url.Values, body io.Reader, length int64) (io.ReadCloser, error) {
	if values == nil {
		values = make(url.Values)
	}
	values.Set(storageRESTDiskID, *client.diskID.Load())

// The returned string is heap-allocated, and caller should call free() on it.
TF_CAPI_EXPORT extern const char* TF_GraphDebugString(TF_Graph* graph,
                                                      size_t* len);

// Returns the function content in a human-readable format, with length set in
// `len`. The format is subject to change in the future.
// The returned string is heap-allocated, and caller should call free() on it.
//

  // before `StartExecute` is called again. Using `StartExecute` with `Join`
  // allows the caller to schedule computation on multiple ParallelDevices
  // without sequencing those operations (first call `StartExecute` on each
  // parallel device, then call `Join` on each; even if some of the `Join`s
  // return a bad status the caller must run all of the `Join`s or any future

  typedef void (*MemoryReleaser)(void* data, size_t len, void* arg);

  // Create a tensor instance from the given data buffer and description.
  // `memory_releaser` will be called on destruction, and it's responsible for
  // cleaning up the underlying buffer.
  virtual AbstractTensorInterface* CreateTensor(
      DataType dtype, const int64_t* dims, int num_dims, void* data, size_t len,

	return jsonFlag
}

// IsQuiet - returns true if quietFlag is true
func IsQuiet() bool {
	return quietFlag
}

// RegisterError registers the specified rendering function. This latter
// will be called for a pretty rendering of fatal errors.
func RegisterError(f func(string, error, bool) string) {
	errorFmtFunc = f
}

// uniq swaps away duplicate elements in data, returning the size of the

// the usual way, and then F returns to its caller. To the caller G, the
// invocation of F then behaves like a call to panic, terminating G's
// execution and running any deferred functions. This continues until all
// functions in the executing goroutine have stopped, in reverse order. At
// that point, the program is terminated with a non-zero exit code. This
// termination sequence is called panicking and can be controlled by the

	}
	return true
}

func (l *localLocker) Lock(ctx context.Context, args dsync.LockArgs) (reply bool, err error) {
	if len(args.Resources) > maxDeleteList {
		return false, fmt.Errorf("internal error: localLocker.Lock called with more than %d resources", maxDeleteList)
	}

	l.mutex.Lock()
	defer l.mutex.Unlock()

	if !l.canTakeLock(args.Resources...) {
		// Not all locks can be taken on resources,
		// reject it completely.

// things like the available devices, resource manager etc.
// TFE_Context must outlive all tensor handles created using it. In other
// words, TFE_DeleteContext() must be called after all tensor handles have
// been deleted (with TFE_DeleteTensorHandle).
//
// TODO(ashankar): Merge with TF_Session?
typedef struct TFE_Context TFE_Context;

TF_CAPI_EXPORT extern TFE_Context* TFE_NewContext(

// Handlers can use this to create a reusable response.
// The response may be reused, so caller should clear any fields.
func (h *SingleHandler[Req, Resp]) NewResponse() Resp {
	return h.newResp()
}

// NewRequest creates a new request.
// Handlers can use this to create a reusable request.
// The request may be reused, so caller should clear any fields.
func (h *SingleHandler[Req, Resp]) NewRequest() Req {
	return h.newReq()

  // scheduled on that same threadpool, causing a deadlock in cases where the
  // caller of event_mgr->ThenExecute() blocks on the completion of the callback
  // (as in the case of ConstOp kernel creation on GPU, which involves copying a
  // CPU tensor to GPU).
  // Setting a larger thread pool does not help with the Swift caller, as we use
  // a different TFE context for each thread of execution (for running graph