Electron microscopy
 
tf.keras.layers.Discretization
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Some preprocessing layers have an internal state that can be computed based on a sample of the training data. The stateful preprocessing layers are:
          i) TextVectorization. It holds a mapping between string tokens and integer indices
          ii) StringLookup and IntegerLookup. They hold a mapping between input values and integer indices.
          iii) Normalization. It holds the mean and standard deviation of the features.
          iv) Discretization. It holds information about value bucket boundaries.

Discretization is also a trainable layer.

tf.keras.layers.Discretization is a preprocessing layer which buckets continuous features into discrete ranges.
         tf.keras.layers.Discretization(
         bin_boundaries=None,
         num_bins=None,
         epsilon=0.01,
         output_mode='int',
         sparse=False,
         **kwargs
         )

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