Thread.currentThread().interrupt() // Retain interrupted status.
      }
    }

    if (!::bytes.isInitialized) {
      // May have failed with an IOException
      throw IllegalStateException("Unable to load $path resource.").apply {
        initCause(readFailure)
      }
    }
  }

  abstract val path: Any

  /**
   * Reads the public suffix list treating the operation as uninterruptible. We always want to read

    void testCustomLifecycle() throws ComponentLookupException {
        List<Lifecycle> myLifecycles = new ArrayList<>();
        Lifecycle myLifecycle =
                new Lifecycle("etl", Arrays.asList("extract", "transform", "load"), Collections.emptyMap());
        myLifecycles.add(myLifecycle);
        myLifecycles.addAll(defaultLifeCycles.getLifeCycles());

		return globalLockServer
	}
	return newlockRESTClient(endpoint)
}

// Returns a lock rest client.
func newlockRESTClient(ep Endpoint) *lockRESTClient {
	return &lockRESTClient{globalLockGrid.Load().Connection(ep.GridHost())}

                return doc
            } catch (ClassDocGenerationException e) {
                throw e
            } catch (Exception e) {
                throw new ClassDocGenerationException("Could not load the class documentation for class '$className'.", e)
            }
        } finally {
            currentlyBuilding.removeLast()
        }
    }

    private File getFileForClass(String className) {

        repository.put('class', value)

        when:
        repository.store(file)
        def newRepo = new SimpleClassMetaDataRepository<TestDomainObject>()
        newRepo.load(file)

        then:
        newRepo.find('class') == value
    }
}

class TestDomainObject implements Attachable<TestDomainObject>, Serializable {
    def value

      } catch (e: Exception) {
        AndroidLog.androidLog(
          loggerName = OkHttpClient::class.java.name,
          logLevel = Platform.WARN,
          message = "unable to load android socket classes",
          t = e,
        )
        null
      }
  }

 * under the License.
 */
package org.apache.maven.cli.internal.extension.model;

import java.io.Serializable;
import java.util.ArrayList;
import java.util.List;

/**
 * Extensions to load.
 *
 * @deprecated Use {@link org.apache.maven.api.cli.extensions.CoreExtension} instead
 */
@Deprecated
@SuppressWarnings("all")
public class CoreExtensions implements Serializable {

	req.Header.Set(xhttp.MinIOPeerCall, "true")

	resp, err := httpClient.Do(req)
	if err != nil {
		return err
	}
	xhttp.DrainBody(resp.Body)

	return nil
}

// connect to list of endpoints and load all Erasure disk formats, validate the formats are correct
// and are in quorum, if no formats are found attempt to initialize all of them for the first
// time. additionally make sure to close all the disks used in this attempt.

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   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.

            .concurrencyLevel(segments)
            .maximumSize(maximumSize)
            .build(
                new CacheLoader<Integer, Integer>() {
                  @Override
                  public Integer load(Integer from) {
                    return (int) misses.incrementAndGet();
                  }
                });

    // To start, fill up the cache.