* you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

                            } catch (final IOException e) {
                                logger.warn("Failed to move thumbnail: path={}", path, e);
                            }
                        }
                    }
                });
            } catch (final IOException e) {
                logger.warn("Failed to migrate thumbnail images.", e);
            }

	}

	if !targetList.Exists(q.ARN.TargetID) {
		return &ErrARNNotFound{q.ARN}
	}

	return nil
}

// SetRegion - sets region value to queue's ARN.
func (q *Queue) SetRegion(region string) {
	q.ARN.region = region
}

// ToRulesMap - converts Queue to RulesMap
func (q Queue) ToRulesMap() RulesMap {
	pattern := q.Filter.RuleList.Pattern()
	return NewRulesMap(q.Events, pattern, q.ARN.TargetID)
}

 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

)

var (
	// ErrPermission is an error returned by the KMS when it has not
	// enough permissions to perform the operation.
	ErrPermission = Error{
		Code:    http.StatusForbidden,
		APICode: "kms:NotAuthorized",
		Err:     "insufficient permissions to perform KMS operation",
	}

	// ErrKeyExists is an error returned by the KMS when trying to
	// create a key that already exists.
	ErrKeyExists = Error{
		Code:    http.StatusConflict,

   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

 *
 * @author mbechler
 *
 */
public interface Address {

    /**
     * Unwrap the address to a specific type
     *
     * @param <T> the type to unwrap to
     * @param type the target type to unwrap to
     * @return instance for type, null if the type cannot be unwrapped
     */
    <T extends Address> T unwrap(Class<T> type);

    /**
     * Gets the host name of this address.
     *

  /**
   * Remove and return the next event from the recorded sequence.
   *
   * @param eventClass a class to assert that the returned event is an instance of, or null to
   *     take any event class.
   * @param elapsedMs the time in milliseconds elapsed since the immediately-preceding event, or
   *     -1L to take any duration.
   */
  fun takeEvent(
    eventClass: Class<out CallEvent>? = null,
    elapsedMs: Long = -1L,

   * ordering that spends a lot of cpu.
   */
  static class ExpensiveComputation implements Function<Integer, BigInteger> {
    @Override
    public BigInteger apply(Integer from) {
      BigInteger v = BigInteger.valueOf(from);
      // Math.sin is very slow for values outside 4*pi
      // Need to take absolute value to avoid inverting the value.

   * ordering that spends a lot of cpu.
   */
  static class ExpensiveComputation implements Function<Integer, BigInteger> {
    @Override
    public BigInteger apply(Integer from) {
      BigInteger v = BigInteger.valueOf(from);
      // Math.sin is very slow for values outside 4*pi
      // Need to take absolute value to avoid inverting the value.