class_docstr: Module used to multiply features in a pipeline by a score.
class_docstr_tok: ["Module","used","to","multiply","features","in","a","pipeline","by","a","score","."]
code: def __init__(self, operator, score):
      super(Multiply, self).__init__(operator)
  
      self.score = score
  
file_path: hummingbird/hummingbird/ml/operator_converters/sklearn/pipeline.py
imports: import numpy
  from onnxconverter_common.registration import register_converter
  import torch
  from ..None import constants
  from .._array_feature_extractor_implementations import ArrayFeatureExtractor
  from .._physical_operator import PhysicalOperator
  from .._pipeline_implementations import Concat
label_desc: Use image node_id 1 to create a new Multiply object from inherited base classes: PhysicalOperator, torch.nn with example: obj = Multiply(operator, score)