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)