I am loading a tensorboard for my ml engine experiment that is running in local mode and got the following warning:
"Found more than one graph event per run, or there was a metagraph containing a graph_def, as well as one or more graph events. Overwriting the graph with the newest event.
W0825 19:26:12.435613 Reloader event_accumulator.py:311] Found more than one metagraph event per run. Overwriting the metagraph with the newest event."
Originally, I suspected that this was because I had not cleared my --logdir=$OUTPUT_PATH
(as other posts suggested -- however, even if I performed rm -rf $OUTPUT_PATH/*
I am still getting this error for a local train. Could this error be indicative of a larger issue in my graph?
It looks like you may have already come across this post, but without more information, it's the best information I can provide:
This is a known issue, TensorBoard doesn't like it when you write
multiple event files from separate runs in the same directory. It will
be fixed if you use a new subdirectory for every run (new
hyperparameters = new subdirectory).
You may be inadvertently writing multiple event files in the same directory (e.g. training and eval?).
Also, be sure you are returning an appropriate tf.estimator.EstimatorSpec
when in modes.EVAL
. From the census sample:
if mode == Modes.EVAL:
labels_one_hot = tf.one_hot(
label_indices_vector,
depth=label_values.shape[0],
on_value=True,
off_value=False,
dtype=tf.bool
)
eval_metric_ops = {
'accuracy': tf.metrics.accuracy(label_indices, predicted_indices),
'auroc': tf.metrics.auc(labels_one_hot, probabilities)
}
return tf.estimator.EstimatorSpec(
mode, loss=loss, eval_metric_ops=eval_metric_ops)