class_docstr: Encoding stage splitting the input by small values.
  
  This encoding stage will split the input into two outputs: the value and the
  indices of the elements whose absolute value is larger than a certain
  threshold. The elements smaller than the threshold is then decoded to zero.
docstr: See base class.
docstr_tok: ["See","base","class","."]
code: def encode(self, x, encode_params):
      """See base class."""
  
      threshold = tf.cast(
          encode_params[self.THRESHOLD_PARAMS_KEY], x.dtype
      )
      indices = tf.cast(
          tf.compat.v2.where(tf.abs(x) > threshold), tf.int32
      )
      non_zero_x = tf.gather_nd(x, indices)
      indices = tf.squeeze(indices, axis=1)
      return collections.OrderedDict(
          [
              (self.ENCODED_INDICES_KEY, indices),
              (self.ENCODED_VALUES_KEY, non_zero_x),
          ]
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  import tensorflow
  from tensorflow_model_optimization.python.core.internal.tensor_encoding.core import encoding_stage
label_desc: Use image node_id 7 for calling the SplitBySmallValueEncodingStage obj's underlying member method code with example usage: obj.encode(x, encode_params) and returns: collections