tf.keras.layers.experimental.preprocessing.Discretization

Buckets data into discrete ranges.

Inherits From: Layer

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tf.compat.v1.keras.layers.experimental.preprocessing.Discretization

tf.keras.layers.experimental.preprocessing.Discretization(
    bins, **kwargs
)

This layer will place each element of its input data into one of several contiguous ranges and output an integer index indicating which range each element was placed in.

Input shape:

Any tf.Tensor or tf.RaggedTensor of dimension 2 or higher.

Output shape:

Same as input shape.

Examples:

Bucketize float values based on provided buckets.

input = np.array([[-1.5, 1.0, 3.4, .5], [0.0, 3.0, 1.3, 0.0]]) layer = tf.keras.layers.experimental.preprocessing.Discretization( ... bins=[0., 1., 2.]) layer(input)

Attributes
bins	Optional boundary specification. Bins include the left boundary and exclude the right boundary, so bins=[0., 1., 2.] generates bins (-inf, 0.), [0., 1.), [1., 2.), and [2., +inf).