A string that identifies how to handle input
pipelines that depend on external state. Possible values are
'ignore': The external state is silently ignored.
'warn': The external state is ignored, logging a warning.
'fail': The operation fails upon encountering external state.
By default we set it to 'fail'.
Returns
A SaveableObject for saving/restoring iterator state using Saver.
Raises
ValueError
If iterator does not support checkpointing.
ValueError
If external_state_policy is not one of 'warn', 'ignore' or
'fail'.
For example:
with tf.Graph().as_default():
ds = tf.data.Dataset.range(10)
iterator = ds.make_initializable_iterator()
# Build the iterator SaveableObject.
saveable_obj = tf.data.experimental.make_saveable_from_iterator(iterator)
# Add the SaveableObject to the SAVEABLE_OBJECTS collection so
# it can be automatically saved using Saver.
tf.compat.v1.add_to_collection(tf.GraphKeys.SAVEABLE_OBJECTS, saveable_obj)
saver = tf.compat.v1.train.Saver()
while continue_training:
... Perform training ...
if should_save_checkpoint:
saver.save()
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