code: def PrecomputableAffine(nO, nI, nF, nP, dropout=0.1):
      model = Model(
          "precomputable_affine",
          forward,
          init=init,
          dims={"nO": nO, "nI": nI, "nF": nF, "nP": nP},
          params={"W": None, "b": None, "pad": None},
          attrs={"dropout_rate": dropout},
      )
      return model
  
imports: from thinc.api import Model, normal_init
  from ..util import registry
label_desc: Use image node_id 1 for calling a global function with example usage: PrecomputableAffine(nO, nI, nF, nP, dropout) and returns: model