class_docstr: Factorization machine base class.
class_docstr_tok: ["Factorization","machine","base","class","."]
code: def __init__(
      self,
      n_factors,
      weight_optimizer,
      latent_optimizer,
      loss,
      sample_normalization,
      l1_weight,
      l2_weight,
      l1_latent,
      l2_latent,
      intercept,
      intercept_lr,
      weight_initializer,
      latent_initializer,
      clip_gradient,
      seed,
  ):
      super().__init__(
          n_factors=n_factors,
          weight_optimizer=weight_optimizer,
          latent_optimizer=latent_optimizer,
          loss=loss,
          sample_normalization=sample_normalization,
          l1_weight=l1_weight,
          l2_weight=l2_weight,
          l1_latent=l1_latent,
          l2_latent=l2_latent,
          intercept=intercept,
          intercept_lr=intercept_lr,
          weight_initializer=weight_initializer,
          latent_initializer=latent_initializer,
          clip_gradient=clip_gradient,
          seed=seed,
      )
  
imports: from __future__ import annotations
  import collections
  import functools
  import itertools
  import numpy
  from river import base, optim, utils
  from .base import BaseFM
label_desc: Use image node_id 1 to create a new FM object from inherited base classes: BaseFM with example: obj = FM(n_factors, weight_optimizer, latent_optimizer, loss, sample_normalization, l1_weight, l2_weight, l1_latent, l2_latent, intercept, intercept_lr, weight_initializer, latent_initializer, clip_gradient, seed)