For example, if elements of the dataset are shaped [B, a0, a1, ...],
where B may vary for each input element, then for each element in the
dataset, the unbatched dataset will contain B consecutive elements
of shape [a0, a1, ...].
# NOTE: The following example uses `{ ... }` to represent the contents# of a dataset.a={['a','b','c'],['a','b'],['a','b','c','d']}a.unbatch()=={'a','b','c','a','b','a','b','c','d'}
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-04-26 UTC."],[],[],null,["# tf.data.experimental.unbatch\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.16.1/tensorflow/python/data/experimental/ops/batching.py#L268-L295) |\n\nSplits elements of a dataset into multiple elements on the batch dimension. (deprecated)\n\n#### View aliases\n\n\n**Compat aliases for migration**\n\nSee\n[Migration guide](https://www.tensorflow.org/guide/migrate) for\nmore details.\n\n[`tf.compat.v1.data.experimental.unbatch`](https://www.tensorflow.org/api_docs/python/tf/data/experimental/unbatch)\n\n\u003cbr /\u003e\n\n tf.data.experimental.unbatch()\n\n| **Deprecated:** THIS FUNCTION IS DEPRECATED. It will be removed in a future version. Instructions for updating: Use [`tf.data.Dataset.unbatch()`](../../../tf/data/Dataset#unbatch).\n\nFor example, if elements of the dataset are shaped `[B, a0, a1, ...]`,\nwhere `B` may vary for each input element, then for each element in the\ndataset, the unbatched dataset will contain `B` consecutive elements\nof shape `[a0, a1, ...]`. \n\n # NOTE: The following example uses `{ ... }` to represent the contents\n # of a dataset.\n a = { ['a', 'b', 'c'], ['a', 'b'], ['a', 'b', 'c', 'd'] }\n\n a.unbatch() == {\n 'a', 'b', 'c', 'a', 'b', 'a', 'b', 'c', 'd'}\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Returns ------- ||\n|---|---|\n| A `Dataset` transformation function, which can be passed to [`tf.data.Dataset.apply`](../../../tf/data/Dataset#apply). ||\n\n\u003cbr /\u003e"]]