// you want the latter, use TFE_TensorHandleBackingDeviceName. This function
// will block till the operation that produces `h` has completed.
TF_CAPI_EXPORT extern const char* TFE_TensorHandleDeviceName(
    TFE_TensorHandle* h, TF_Status* status);

// Returns the name of the device in whose memory `h` resides.
//
// This function will block till the operation that produces `h` has completed.

}

var errNegativeRead = errors.New("bufio: reader returned negative count from Read")

// fill reads a new chunk into the buffer.
func (b *Reader) fill() {
	// Slide existing data to beginning.
	if b.r > 0 {
		copy(b.buf, b.buf[b.r:b.w])
		b.w -= b.r
		b.r = 0
	}

	if b.w >= len(b.buf) {
		panic("bufio: tried to fill full buffer")
	}

	// Read new data: try a limited number of times.

  // Specifies the hostname of the Carp
  // If not specified, the carp's hostname will be set to a system-defined value.
  // +optional
  optional string hostname = 16;

  // If specified, the fully qualified Carp hostname will be "<hostname>.<subdomain>.<carp namespace>.svc.<cluster domain>".
  // If not specified, the carp will not have a domainname at all.
  // +optional
  optional string subdomain = 17;

Consider an application streaming a video over http/2. Perhaps the user pauses the video and the application stops reading bytes from this stream. The buffer will fill up, and flow control prevents the server from sending more data on this stream. When the user unpauses her video the buffer drains, the read is acknowledged, and the server proceeds to stream data.

#### Shared reader thread

        style core_runtime stroke:#1abc9c,fill:#b1f4e7,stroke-width:2px,color:#000;

        core_configuration["core-configuration module"]
        style core_configuration stroke:#1abc9c,fill:#b1f4e7,stroke-width:2px,color:#000;

        core_execution["core-execution module"]
        style core_execution stroke:#1abc9c,fill:#b1f4e7,stroke-width:2px,color:#000;
    end
    style core fill:#c2e0f4,stroke:#3498db,stroke-width:2px,color:#000;

   * multiset itself).
   *
   * <p>Despite the method name, this method attempts to avoid actually copying the data when it is
   * safe to do so. The exact circumstances under which a copy will or will not be performed are
   * undocumented and subject to change.
   *
   * <p>This method is not type-safe, as it may be called on elements that are not mutually
   * comparable.
   *

lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions == 4.8.0
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0

# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version
# Note that we must use nightly here as these are used in nightly jobs
# For release jobs, we will pin these on the release branch

    const val MAX_CONCURRENT_STREAMS = 4

    /** HTTP/2: Size in bytes of the largest frame payload the sender will accept. */
    const val MAX_FRAME_SIZE = 5

    /** HTTP/2: Advisory only. Size in bytes of the largest header list the sender will accept. */
    const val MAX_HEADER_LIST_SIZE = 6

    /** Window size in bytes. */
    const val INITIAL_WINDOW_SIZE = 7

 * acquire(1000)} will result in exactly the same throttling, if any), but it affects the throttling
 * of the <i>next</i> request. I.e., if an expensive task arrives at an idle RateLimiter, it will be
 * granted immediately, but it is the <i>next</i> request that will experience extra throttling,
 * thus paying for the cost of the expensive task.
 *

    trustDomain: "cluster.local"

    # The namespace to treat as the administrative root namespace for Istio configuration.
    # When processing a leaf namespace Istio will search for declarations in that namespace first
    # and if none are found it will search in the root namespace. Any matching declaration found in the root namespace
    # is processed as if it were declared in the leaf namespace.