tensorflow - Does tf.estimator discard data partially?

Question

Let us say we are using tf.data and tf.estimator. The data_input_fn() returns dataset.shuffle(SHUFFLE_BUFFER_SIZE).repeat().batch(BATCH_SIZE) for training. Note the dataset will repeat indefinitely unless there is a stopping training event.

For example, one complete traversal of training dataset (epoch) contains 11 iteration steps [1, 2, 3, ..., 11], and tf.estimator has configuration save_checkpoints_steps=3. Then, parameter updates of the last two iteration steps [10, 11] won't be able to be saved as checkpoints. Since the tf.estimator creates new session for each new epoch, will this lose parameter updates of the training samples corresponding to the iteration steps [10, 11]?

question from:https://stackoverflow.com/questions/65623583/does-tf-estimator-discard-data-partially

Answer 1

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