code: def calculate_loss(Cui, X, Y, regularization, solver=None):
      """Calculates the loss for an ALS model"""
      if not isinstance(Cui, implicit.gpu.CSRMatrix):
          Cui = implicit.gpu.CSRMatrix(Cui)
      if not isinstance(X, implicit.gpu.Matrix):
          X = implicit.gpu.Matrix(X)
      if not isinstance(Y, implicit.gpu.Matrix):
          Y = implicit.gpu.Matrix(Y)
      if solver is None:
          solver = implicit.gpu.LeastSquaresSolver()
  
      return solver.calculate_loss(Cui, X, Y, regularization)
  
imports: import logging
  import time
  import numpy
  from tqdm.auto import tqdm
  import implicit.gpu
  from implicit.gpu.matrix_factorization_base import MatrixFactorizationBase, check_random_state
  from implicit.utils import check_csr
label_desc: Use image node_id 1 for calling a global function with example usage: calculate_loss(Cui, X, Y, regularization, solver) and returns: solver