Comments (1)
Hi, sorry for replying late.
Users of ParameterServerStrategy with the Model.fit
API need to use a DatasetCreator as the input. An instance of this class will be passed to fit
when using a callable (with a input_context
argument) that returns a tf.data.Dataset
. According to TensorFlow's document:
If you instead create your dataset with tf.keras.utils.experimental.DatasetCreator, the code in dataset_fn will be invoked on the input device, which is usually the CPU, on each of the worker machines.
So Model.fit
usage with DatasetCreator is intended to work across all tf.distribute.Strategy
, as long as Strategy.scope
is used at model creation. tf.distribute
will call the input function on the CPU device of each of the workers.
from ml-distributed-training.
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