def launch(): """Launch t2t_trainer on Cloud ML Engine.""" validate_flags() job_spec = configure_job() job_name = job_spec["jobId"] tf.logging.info("Launching job %s with ML Engine spec:\n%s", job_name, job_spec) assert cloud.confirm() train_dir = FLAGS.output_dir t2t_tar = tar_and_copy_t2t(train_dir) configure_trainer_package(job_spec, t2t_tar) if FLAGS.t2t_usr_dir: usr_tar = tar_and_copy_usr_dir(FLAGS.t2t_usr_dir, train_dir) configure_usr_dir(job_spec, usr_tar) launch_job(job_spec) tf.logging.info("Launched %s. See console to track: %s.", job_name, CONSOLE_URL)
def launch(): """Launch t2t_trainer on Cloud ML Engine.""" assert not FLAGS.cloud_tpu assert not job_dir() assert FLAGS.output_dir.startswith('gs://') assert FLAGS.data_dir.startswith('gs://') assert FLAGS.worker_replicas <= 1 assert FLAGS.ps_replicas <= 0 build_t2t_python_package() job_spec = configure_job() job_name = job_spec['jobId'] tf.logging.info('Launching job %s with ML Engine spec:\n%s', job_name, job_spec) assert cloud.confirm() train_dir = FLAGS.output_dir trainer_package_gcs_path = upload_trainer_package_to_gcs(train_dir) configure_trainer_package(job_spec, trainer_package_gcs_path) launch_job(job_spec) tf.logging.info('Launched %s. See console to track: %s.', job_name, CONSOLE_URL)
def launch(): """Launch t2t_trainer on Cloud ML Engine.""" assert not FLAGS.cloud_tpu assert not FLAGS.job_dir assert FLAGS.output_dir.startswith('gs://') assert FLAGS.data_dir.startswith('gs://') assert FLAGS.worker_replicas <= 1 assert FLAGS.ps_replicas <= 0 job_spec = configure_job() job_name = job_spec['jobId'] tf.logging.info('Launching job %s with ML Engine spec:\n%s', job_name, job_spec) assert cloud.confirm() train_dir = FLAGS.output_dir t2t_tar = tar_and_copy_t2t(train_dir) configure_trainer_package(job_spec, t2t_tar) if FLAGS.t2t_usr_dir: usr_tar = tar_and_copy_usr_dir(FLAGS.t2t_usr_dir, train_dir) configure_usr_dir(job_spec, usr_tar) launch_job(job_spec) tf.logging.info('Launched %s. See console to track: %s.', job_name, CONSOLE_URL)