Adds reshuffle_each_iteration argument to deterministic_data.create_dataset().
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…e_dataset()`. This argument is passed to `tf.data.Dataset.shuffle()` and controls whether the dataset is reshuffled each time it is iterated over. The default value is `None`, which is the same as the default value of `reshuffle_each_iteration` in `tf.data.Dataset.shuffle()`. This change is being made to support the use of `deterministic_data.create_dataset()` in evaluation loops that need to access the same evaluation data batches in each iteration of the dataset without reshuffling before each iteration/epoch over the dataset. This is useful, for example, in visualizing the progress of image generation models at different model checkpoints. Visualizing the model progress on the same evaluation data makes Tensorboard qualitative evaluation easier. This change is backwards compatible. If the `reshuffle_each_iteration` argument is not specified, the default value of `None` will be used. PiperOrigin-RevId: 661355447
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Adds
reshuffle_each_iterationargument todeterministic_data.create_dataset().This argument is passed to
tf.data.Dataset.shuffle()and controls whether the dataset is reshuffled each time it is iterated over. The default value isNone, which is the same as the default value ofreshuffle_each_iterationintf.data.Dataset.shuffle().This change is being made to support the use of
deterministic_data.create_dataset()in evaluation loops that need to access the same evaluation data batches in each iteration of the dataset without reshuffling before each iteration/epoch over the dataset. This is useful, for example, in visualizing the progress of image generation models at different model checkpoints. Visualizing the model progress on the same evaluation data makes Tensorboard qualitative evaluation easier.This change is backwards compatible. If the
reshuffle_each_iterationargument is not specified, the default value ofNonewill be used.