logger.Fatal(fmt.Errorf("invalid arguments passed to --ftp=%s (%v)", arg, err), "unable to start FTP server")
			}
			if port < 1 || port > 65535 {
				logger.Fatal(fmt.Errorf("invalid arguments passed to --ftp=%s, (port number must be between 1 to 65535)", arg), "unable to start FTP server")
			}
			publicIP = host
		case "passive-port-range":
			portRange = tokens[1]
		case "tls-private-key":
			tlsPrivateKey = tokens[1]

     * down. twiceSignifFloor will contain the top SIGNIFICAND_BITS + 2 bits, and signifFloor the
     * top SIGNIFICAND_BITS + 1.
     *
     * It helps to consider the real number signif = absX * 2^(SIGNIFICAND_BITS - exponent).
     */
    int shift = exponent - SIGNIFICAND_BITS - 1;
    long twiceSignifFloor = absX.shiftRight(shift).longValue();
    long signifFloor = twiceSignifFloor >> 1;

should serve from. ## If left empty, it defaults to the value of {{ .Values.mountPath }} ## If defined, it must be a sub-directory of the path specified in {{ .Values.mountPath }} ## bucketRoot: "" # Number of drives attached to a node drivesPerNode: 1 # Number of MinIO containers running replicas: 16 # Number of expanded MinIO clusters pools: 1 # Deploy if 'mode == gateway' - 4 replicas. gateway: type: "nas" # currently only "nas" is supported. replicas: 4 ## TLS Settings for MinIO tls: enabled: false...

should serve from. ## If left empty, it defaults to the value of {{ .Values.mountPath }} ## If defined, it must be a sub-directory of the path specified in {{ .Values.mountPath }} ## bucketRoot: "" # Number of drives attached to a node drivesPerNode: 1 # Number of MinIO containers running replicas: 16 # Number of expanded MinIO clusters pools: 1 # Deploy if 'mode == gateway' - 4 replicas. gateway: type: "nas" # currently only "nas" is supported. replicas: 4 ## TLS Settings for MinIO tls: enabled: false...

should serve from. ## If left empty, it defaults to the value of {{ .Values.mountPath }} ## If defined, it must be a sub-directory of the path specified in {{ .Values.mountPath }} ## bucketRoot: "" # Number of drives attached to a node drivesPerNode: 1 # Number of MinIO containers running replicas: 16 # Number of expanded MinIO clusters pools: 1 # Deploy if 'mode == gateway' - 4 replicas. gateway: type: "nas" # currently only "nas,gcs" are supported. replicas: 4 gcs: serviceAccountFile: "" # credential...

		Description:    "Invalid Encoding Method specified in Request",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrInvalidMaxParts: {
		Code:           "InvalidArgument",
		Description:    "Part number must be an integer between 1 and 10000, inclusive",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrInvalidPartNumberMarker: {
		Code:           "InvalidArgument",

The number of operands on the left
hand side must match the number of values.  For instance, if
<code>f</code> is a function returning two values,
</p>

<pre>
x, y = f()
</pre>

<p>
assigns the first value to <code>x</code> and the second to <code>y</code>.
In the second form, the number of operands on the left must equal the number

   * milliseconds to execute.
   */
  private static final boolean profileTests = Boolean.getBoolean("jsr166.profileTests");

  /**
   * The number of milliseconds that tests are permitted for execution without being reported, when
   * profileTests is set.
   */
  private static final long profileThreshold = Long.getLong("jsr166.profileThreshold", 100);

 * high contention, expected throughput of this class is significantly higher, at the expense of
 * higher space consumption.
 *
 * <p>This class extends {@link Number}, but does not define methods such as {@code
 * equals}, {@code hashCode} and {@code compareTo} because instances are expected to be mutated, and
 * so are not useful as collection keys.
 *

      theta_inputs[input_index];  // parameter we are grad checking

  // Convert from AbstractTensor to TF_Tensor.
  TF_Tensor* theta_tensor;
  TF_RETURN_IF_ERROR(GetValue(theta, &theta_tensor));

  // Get number of elements and fill data.
  int num_elems = TF_TensorElementCount(theta_tensor);
  vector<float> theta_data(num_elems);
  memcpy(theta_data.data(), TF_TensorData(theta_tensor),
         TF_TensorByteSize(theta_tensor));