tf.experimental.function_executor

TensorFlow 1 version

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Represents discretized dense input bucketed by boundaries.

View aliases

Compat aliases for migration

See Migration guide for more details.

tf.compat.v1.feature_column.bucketized_column

tf.feature_column.bucketized_column(
    source_column, boundaries
)

Used in the notebooks

Used in the tutorials
Classify structured data with feature columns End to end example for BigQuery TensorFlow reader

Buckets include the left boundary, and exclude the right boundary. Namely, boundaries=[0., 1., 2.] generates buckets (-inf, 0.), [0., 1.), [1., 2.), and [2., +inf).

For example, if the inputs are

boundaries = [0, 10, 100]
input tensor = [[-5, 10000]
                [150,   10]
                [5,    100]]

then the output will be

output = [[0, 3]
          [3, 2]
          [1, 3]]

Example:

price = tf.feature_column.numeric_column('price')
bucketized_price = tf.feature_column.bucketized_column(
    price, boundaries=[...])
columns = [bucketized_price, ...]
features = tf.io.parse_example(
    ..., features=tf.feature_column.make_parse_example_spec(columns))
dense_tensor = tf.keras.layers.DenseFeatures(columns)(features)

A bucketized_column can also be crossed with another categorical column using crossed_column:

price = tf.feature_column.numeric_column('price')
# bucketized_column converts numerical feature to a categorical one.
bucketized_price = tf.feature_column.bucketized_column(
    price, boundaries=[...])
# 'keywords' is a string feature.
price_x_keywords = tf.feature_column.crossed_column(
    [bucketized_price, 'keywords'], 50K)
columns = [price_x_keywords, ...]
features = tf.io.parse_example(
    ..., features=tf.feature_column.make_parse_example_spec(columns))
dense_tensor = tf.keras.layers.DenseFeatures(columns)(features)
linear_model = tf.keras.experimental.LinearModel(units=...)(dense_tensor)

Args
`source_column`	A one-dimensional dense column which is generated with `numeric_column`.
`boundaries`	A sorted list or tuple of floats specifying the boundaries.

Returns
A `BucketizedColumn`.

Raises
`ValueError`	If `source_column` is not a numeric column, or if it is not one-dimensional.
`ValueError`	If `boundaries` is not a sorted list or tuple.

TensorFlow

tf

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tf.compat

tf.config

tf.data

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tf.distribute

tf.dtypes

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tf.estimator

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tf.strings

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tf.sysconfig

tf.test

tf.tpu

tf.train

tf.version

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tf.experimental / function_executor_type

View aliases

Used in the notebooks

Example:

Args

Returns

Raises