tensorflow - scalar summaries not showing up with distributed ML engine custom tier -


i ran ml engine model on cloud --scale-tier:basic_gpu , of scalar/histogram summaries displayed in tensorboard. think decided switch custom-tier following configuration:

traininginput:   scaletier: custom   mastertype: complex_model_s   workertype: complex_model_m_gpu   parameterservertype: large_model   workercount: 1   parameterservercount: 1

when looking @ logs, model training, evaluation being performed , eval_metric_ops being output, summary scalars/histograms not being output on tensorboard anymore. in fact, loss not showing updates on tensoboard (even see decreasing in stackdriver logs). running tf.train.estimator custom model_fn defined , assuming have not set model_fn handle distributed training. however, still peculiar logs showing training occurring, while tensorboard behaving nothing occurring? should summaries explicitly handled master or ensure written right place?


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