project(":okhttp-logging-interceptor").name = "logging-interceptor"

val androidHome = System.getenv("ANDROID_HOME")
val localProperties = Properties().apply {
  val file = File("local.properties")
  if (file.exists()) {
    load(file.inputStream())
  }
}
val sdkDir = localProperties.getProperty("sdk.dir")
if (androidHome != null || sdkDir != null) {
  include(":android-test")
  include(":android-test-app")
}

  command: server http://site2-minio{1...4}/data{1...2}
  environment:
    - MINIO_PROMETHEUS_AUTH_TYPE=public
    - CI=true

# starts 4 docker containers running minio server instances.
# using nginx reverse proxy, load balancing, you can access
# it through port 9000.
services:
  site2-minio1:
    <<: *minio-common
    hostname: site2-minio1
    volumes:
      - site2-data1-1:/data1
      - site2-data1-2:/data2

  healthcheck:
    test: ["CMD", "mc", "ready", "local"]
    interval: 5s
    timeout: 5s
    retries: 5

# starts 4 docker containers running minio server instances.
# using nginx reverse proxy, load balancing, you can access
# it through port 9000.
services:
  minio1:
    <<: *minio-common
    hostname: minio1
    volumes:
      - pdata1-1:/pdata1
      - pdata1-2:/pdata2

  minio2:

}

// load the cache content with name from minioMetaBackgroundOpsBucket.
// Only backend errors are returned as errors.
// The loader is optimistic and has no locking, but tries 5 times before giving up.
// If the object is not found, a nil error with empty data usage cache is returned.
func (d *dataUsageCache) load(ctx context.Context, store objectIO, name string) error {

    </default>
  </defaults>

  <classes>
    <class rootElement="true" xml.tagName="extensions" xsd.compositor="sequence">
      <name>CoreExtensions</name>
      <description>Extensions to load.</description>
      <version>1.0.0+</version>
      <fields>
        <field>
          <name>extensions</name>
          <description>A set of build extensions to use from this project.</description>

   
   
   *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.

	entries, err = r.readN(0, false, true, false, "")
	if err != nil {
		t.Fatal(err, entries.len())
	}
	if entries.len() != len(want) {
		t.Fatal("unexpected length:", entries.len(), "want:", len(want))
	}

	// Reload.
	r = loadMetacacheSample(t)
	defer r.Close()
	entries, err = r.readN(0, false, true, false, "")
	if err != nil {
		t.Fatal(err, entries.len())
	}
	if entries.len() != len(want) {

            try {
                mavenWrapperPropertyFileInputStream = new FileInputStream(mavenWrapperPropertyFile);
                Properties mavenWrapperProperties = new Properties();
                mavenWrapperProperties.load(mavenWrapperPropertyFileInputStream);
                url = mavenWrapperProperties.getProperty(PROPERTY_NAME_WRAPPER_URL, url);
            } catch (IOException e) {

        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

		tx.Statement.DB = tx
	}

	if config.Context != nil {
		tx.Statement.Context = config.Context
	}

	if config.PrepareStmt {
		var preparedStmt *PreparedStmtDB

		if v, ok := db.cacheStore.Load(preparedStmtDBKey); ok {
			preparedStmt = v.(*PreparedStmtDB)
		} else {
			preparedStmt = NewPreparedStmtDB(db.ConnPool, db.PrepareStmtMaxSize, db.PrepareStmtTTL)
			db.cacheStore.Store(preparedStmtDBKey, preparedStmt)