Error when checkpointing a dataset that uses SentencepieceTokenizer
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Description
I am running into a error when checkpointing a tf.data.Dataset iterator that uses a SentencepieceTokenizer for tokenization. It fails with:
tensorflow.python.framework.errors_impl.FailedPreconditionError: {{function_node __wrapped__SerializeIterator_device_/job:localhost/replica:0/task:0/device:CPU:0}} SentencepieceTokenizeOp is stateful. [Op:SerializeIterator] name:
As a result I cannot checkpoint datasets that use SentencepieceTokenizer. Is there a fix of work-around that would resolve the issue for me? I saw https://github.com/tensorflow/text/blob/dd919053e7d3e7fddc2dd8e8abccdd74d259a7a1/tensorflow_text/core/kernels/sentencepiece_kernels.cc#L404 which makes it looks like this supposed to be possible.
Code to reproduce the issue:
import tensorflow as tf
import tensorflow_text as tf_text
with open("/path/to/tokenizer.model", "rb") as f:
sp_model = f.read()
tokenizer = tf_text.SentencepieceTokenizer(sp_model)
ds = tf.data.Dataset.from_tensor_slices(dict(data=["ex1", "ex2", "ex3",]))
def _map(ex):
return dict(data=tokenizer.tokenize(ex["data"]))
ds: tf.data.Dataset = ds.map(_map)
iterator = iter(ds)
ckpt = tf.train.Checkpoint(iterator=iterator)
ckpt.write("/tmp/iterator")
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Research direction
Start by running the Python reproduction with the linked Colab example and inspect tensorflow_text/core/kernels/sentencepiece_kernels.cc around line 404. Trace why SentencepieceTokenizeOp is treated as stateful during SerializeIterator, then verify that checkpointing the reproduced tf.data iterator succeeds without the FailedPreconditionError.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp, python, tensorflow
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100