class_docstr: Module that implements plain scalar product
  as the retrieval criterion
class_docstr_tok: ["Module","that","implements","plain","scalar","product","as","the","retrieval","criterion"]
docstr: Args:
      X: numpy matrix of shape (users, features)
      Y: numpy matrix of shape (items, features)
docstr_tok: ["Args",":","X",":","numpy","matrix","of","shape","(","users",",","features",")","Y",":","numpy","matrix","of","shape","(","items",",","features",")"]
code: def __init__(self, X, Y, **kwargs):
      """
      Args:
          X: numpy matrix of shape (users, features)
          Y: numpy matrix of shape (items, features)
      """
      self.X = X
      self.Y = Y
  
file_path: recommenders/recommenders/models/geoimc/geoimc_predict.py
imports: import numpy
  from scipy.linalg import sqrtm
  from recommenders.utils.python_utils import binarize
label_desc: Use image node_id 1 to create a new PlainScalarProduct object from inherited base classes: object with example: obj = PlainScalarProduct(X, Y)