Zohar Yahav

What do you mean by not block the execution? Are you looking for it to "run in the background" or for a way to get the execution deferred? Note that...

tf.text can be used within the tf.transform `preprocessing_fn`, as well as tf.transform's vocabulary functionality (`tft.compute_and_apply_vocabulary`, `tft.vocabulary`, etc.). Is there a particular functionality that you're looking for with tf.transform that you...

It currently has basic support, to be extended some time soon. Currently, SequenceExamples are supported by providing serialized SequenceExamples as a single feature to the preprocessing_fn which can then be...

We basically expect the following to write and flush: https://github.com/tensorflow/transform/blob/a183f6848d266e399e8cd2a2d37111411e8bd4e4/tensorflow_transform/tf_metadata/metadata_io.py#L122 I'm surprised that the directory doesn't even exist though because of this: https://github.com/tensorflow/transform/blob/a183f6848d266e399e8cd2a2d37111411e8bd4e4/tensorflow_transform/tf_metadata/metadata_io.py#L119 Do we know the extent of TF's...

@rmothukuru this issue should be on the TFX repo because it's referring to TFX documentation (of a preprocessing_fn). @sakinaljana please take a look at this guide and let us know...

From https://www.tensorflow.org/tfx/api_docs/python/tfx/components/Transform#args: > The path to python function that implements a 'preprocessing_fn'. See 'module_file' for expected signature of the function. Exactly one of 'module_file' or 'preprocessing_fn' must be supplied. It...

@zhitaoli would it be possible to update the documentation?

Note that the example above is relevant only to using tf.transform directly, i.e. without a TFX Transform component. When using tf.transform within a TFX Transform component then the snippets in...

Yes, please have a look at [`tft.experimental.get_vocabulary_size_by_name `](https://www.tensorflow.org/tfx/transform/api_docs/python/tft/experimental/get_vocabulary_size_by_name) and [`tft.get_num_buckets_for_transformed_feature`](https://www.tensorflow.org/tfx/transform/api_docs/python/tft/get_num_buckets_for_transformed_feature), both of these should help achieve what you're looking for, which is obtaining vocabulary size from within a `preprocessing_fn`. The...

The second example snippet above is hardcoding the path: `model_path = "gs://mybucekt/custom_embedding_model/"` What's the reason for not doing the same in the first snippet, when using TFX Transform?