class_docstr: Compares two documents to solve a regression 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","regression","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 _predict_op(self, logits, **kwargs):
      return logits
  
imports: import tensorflow
  import numpy
  from finetune.encoding.target_encoders import RegressionEncoder
  from finetune.target_models.comparison import ComparisonPipeline
  from finetune.nn.target_blocks import regressor
  from finetune.base import BaseModel
  from finetune.model import PredictMode
label_desc: Use image node_id 8 for calling the ComparisonRegressor obj's underlying member method code with example usage: obj._predict_op(logits) and returns: logits