tf.data.experimental.unique
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Creates a Dataset
from another Dataset
, discarding duplicates.
tf.data.experimental.unique()
Use this transformation to produce a dataset that contains one instance of
each unique element in the input. For example:
dataset = tf.data.Dataset.from_tensor_slices([1, 37, 2, 37, 2, 1])
# Using `unique()` will drop the duplicate elements.
dataset = dataset.apply(tf.data.experimental.unique()) # ==> { 1, 37, 2 }
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Last updated 2020-10-01 UTC.
[null,null,["Last updated 2020-10-01 UTC."],[],[],null,["# tf.data.experimental.unique\n\n\u003cbr /\u003e\n\n|----------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------|\n| [TensorFlow 2 version](/api_docs/python/tf/data/experimental/unique) | [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v1.15.0/tensorflow/python/data/experimental/ops/unique.py#L26-L48) |\n\nCreates a `Dataset` from another `Dataset`, discarding duplicates.\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.unique`](/api_docs/python/tf/data/experimental/unique), \\`tf.compat.v2.data.experimental.unique\\`\n\n\u003cbr /\u003e\n\n tf.data.experimental.unique()\n\nUse this transformation to produce a dataset that contains one instance of\neach unique element in the input. For example: \n\n dataset = tf.data.Dataset.from_tensor_slices([1, 37, 2, 37, 2, 1])\n\n # Using `unique()` will drop the duplicate elements.\n dataset = dataset.apply(tf.data.experimental.unique()) # ==\u003e { 1, 37, 2 }\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"]]