Certain Tensorflow PS have much higher memory usage than others
when training dnn model via Tensorflow on kubernetes, found most ps have a memory cost ~ 2Gi, but one has more than 70Gi, and also have two around 16Gi. Not sure the reason.
Details:
tf.min_max_variable_partitioner to create a partitioner, and used in tf.get_variable() to assistant place variables
tensorflow distributed
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when training dnn model via Tensorflow on kubernetes, found most ps have a memory cost ~ 2Gi, but one has more than 70Gi, and also have two around 16Gi. Not sure the reason.
Details:
tf.min_max_variable_partitioner to create a partitioner, and used in tf.get_variable() to assistant place variables
tensorflow distributed
add a comment |
when training dnn model via Tensorflow on kubernetes, found most ps have a memory cost ~ 2Gi, but one has more than 70Gi, and also have two around 16Gi. Not sure the reason.
Details:
tf.min_max_variable_partitioner to create a partitioner, and used in tf.get_variable() to assistant place variables
tensorflow distributed
when training dnn model via Tensorflow on kubernetes, found most ps have a memory cost ~ 2Gi, but one has more than 70Gi, and also have two around 16Gi. Not sure the reason.
Details:
tf.min_max_variable_partitioner to create a partitioner, and used in tf.get_variable() to assistant place variables
tensorflow distributed
tensorflow distributed
asked Nov 15 '18 at 7:13
mia ichmia ich
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