tf.keras.layers.experimental.preprocessing.Discretization.DiscretizingCombiner
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Combiner for the Discretization preprocessing layer.
tf.keras.layers.experimental.preprocessing.Discretization.DiscretizingCombiner(
epsilon, num_bins
)
This class encapsulates the computations for finding the quantile boundaries
of a set of data in a stable and numerically correct way. Its associated
accumulator is a namedtuple('summaries'), representing summarizations of
the data used to generate boundaries.
Attributes |
|---|
epsilon
|
Error tolerance.
|
num_bins
|
The desired number of buckets.
|
Methods
compute
View source
compute(
values, accumulator=None
)
Compute a step in this computation, returning a new accumulator.
deserialize
View source
deserialize(
encoded_accumulator
)
Deserialize an accumulator received from 'serialize()'.
View source
extract(
accumulator
)
Convert an accumulator into a dict of output values.
merge
View source
merge(
accumulators
)
Merge several accumulators to a single accumulator.
restore
View source
restore(
output
)
Create an accumulator based on 'output'.
serialize
View source
serialize(
accumulator
)
Serialize an accumulator for a remote call.
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Last updated 2021-05-14 UTC.
[[["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complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2021-05-14 UTC."],[],[],null,["# tf.keras.layers.experimental.preprocessing.Discretization.DiscretizingCombiner\n\n\u003cbr /\u003e\n\n|--------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [View source on GitHub](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/preprocessing/discretization.py#L281-L358) |\n\nCombiner for the Discretization preprocessing layer.\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.keras.layers.experimental.preprocessing.Discretization.DiscretizingCombiner`](https://www.tensorflow.org/api_docs/python/tf/keras/layers/experimental/preprocessing/Discretization/DiscretizingCombiner)\n\n\u003cbr /\u003e\n\n tf.keras.layers.experimental.preprocessing.Discretization.DiscretizingCombiner(\n epsilon, num_bins\n )\n\nThis class encapsulates the computations for finding the quantile boundaries\nof a set of data in a stable and numerically correct way. Its associated\naccumulator is a namedtuple('summaries'), representing summarizations of\nthe data used to generate boundaries.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\n| Attributes ---------- ||\n|------------|--------------------------------|\n| `epsilon` | Error tolerance. |\n| `num_bins` | The desired number of buckets. |\n\n\u003cbr /\u003e\n\nMethods\n-------\n\n### `compute`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/preprocessing/discretization.py#L300-L316) \n\n compute(\n values, accumulator=None\n )\n\nCompute a step in this computation, returning a new accumulator.\n\n### `deserialize`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/preprocessing/discretization.py#L351-L354) \n\n deserialize(\n encoded_accumulator\n )\n\nDeserialize an accumulator received from 'serialize()'.\n\n### `extract`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/preprocessing/discretization.py#L329-L337) \n\n extract(\n accumulator\n )\n\nConvert an accumulator into a dict of output values.\n\n### `merge`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/preprocessing/discretization.py#L318-L327) \n\n merge(\n accumulators\n )\n\nMerge several accumulators to a single accumulator.\n\n### `restore`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/preprocessing/discretization.py#L339-L342) \n\n restore(\n output\n )\n\nCreate an accumulator based on 'output'.\n\n### `serialize`\n\n[View source](https://github.com/tensorflow/tensorflow/blob/v2.5.0/tensorflow/python/keras/layers/preprocessing/discretization.py#L344-L349) \n\n serialize(\n accumulator\n )\n\nSerialize an accumulator for a remote call."]]
View source on GitHub