Interleave function

I wish to understand what exactly happens when I apply tf.data.Dataset.interleave() function. I’m unable to clearly understand what happens under the hood and how does it help in training large models. Kindly someone explain it in layman terms.

Hi there,

I guess you read through the official documentation here: tf.data.Dataset  |  TensorFlow v2.12.0

In this source a rather illustrative example is discussed step by step:


Feel free to check it out!

The benefit of tf.data.Dataset.interleave() is in particular to process many input data - combined to one data set. This is especially useful if you want to train a model based on many (often big) data sources.

Best regards
Christian

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Thanks Christian! Understood the basic concept.

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Glad to hear that. In case of any questions, pls. do not hesitate to ask, @Harshit1097.

Happy learning!

Best regards
Christian

Yes sure. Thanks again.

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