class_docstr: Compares two documents to solve a classification task.
  
  :param config: A :py:class:`finetune.config.Settings` object or None (for default config).
  :param \**kwargs: key-value pairs of config items to override.
class_docstr_tok: ["Compares","two","documents","to","solve","a","classification","task",".",":","param","config",":","A",":","py",":","class",":","`","finetune.config.Settings","`","object","or","None","(","for","default","config",")",".",":","param","\\","*","*","kwargs",":","key-value","pairs","of","config","items","to","override","."]
code: def _pre_target_model_hook(self, featurizer_state):
      featurizer_state["sequence_features"] = tf.abs(
          tf.reduce_sum(
              input_tensor=featurizer_state["sequence_features"], axis=1
          )
      )
      featurizer_state["features"] = tf.abs(
          tf.reduce_sum(
              input_tensor=featurizer_state["features"], axis=1
          )
      )
  
imports: import numpy
  import tensorflow
  import copy
  from finetune.errors import FinetuneError
  from finetune.base import BaseModel
  from finetune.target_models.classifier import Classifier, ClassificationPipeline
  from finetune.encoding.input_encoder import EncodedOutput, tokenize_context
label_desc: Use image node_id 3 for calling the Comparison obj's underlying member method code with example usage: obj._pre_target_model_hook(featurizer_state) without return types