## Major Features and Improvements

TensorFlow 2.0 focuses on **simplicity** and **ease of use**, featuring updates
like:

*   Easy model building with Keras and eager execution.
*   Robust model deployment in production on any platform.
*   Powerful experimentation for research.
*   API simplification by reducing duplication and removing deprecated
    endpoints.

For details on best practices with 2.0, see

	reqInfo := logger.GetReqInfo(ctx)
	var newReqInfo *logger.ReqInfo
	if reqInfo != nil {
		newReqInfo = logger.NewReqInfo(reqInfo.RemoteHost, reqInfo.UserAgent, reqInfo.DeploymentID, reqInfo.RequestID, reqInfo.API, bucket, object)
	} else {
		newReqInfo = logger.NewReqInfo("", "", globalDeploymentID(), "", "Heal", bucket, object)
	}
	healCtx := logger.SetReqInfo(GlobalContext, newReqInfo)

		// to verify for legacy version.
		if formatLegacy {
			// We only need this code if we are moving
			// from `xl.json` to `xl.meta`, we can avoid
			// one extra readdir operation here for all
			// new deployments.
			entries, err := readDir(currentDataPath)
			if err != nil && err != errFileNotFound {
				return res, osErrToFileErr(err)
			}
			for _, entry := range entries {