code: def test_map_list():
      nI = 4
      nO = 9
      Xs = [
          numpy.zeros((6, nI), dtype="f"),
          numpy.ones((3, nI), dtype="f"),
      ]
      Y_shapes = [(x.shape[0], nO) for x in Xs]
      model = map_list(Linear())
      model.initialize(
          X=Xs, Y=[numpy.zeros(shape, dtype="f") for shape in Y_shapes]
      )
      Ys, backprop = model(Xs, is_train=True)
      assert isinstance(Ys, list)
      assert len(Ys) == len(Xs)
      layer = model.layers[0]
      for X, Y in zip(Xs, Ys):
          assert_allclose(layer.predict(X), Y)
      dXs = backprop(Ys)
      assert isinstance(dXs, list)
      assert len(dXs) == len(Xs)
      assert dXs[0].shape == Xs[0].shape
      assert dXs[1].shape == Xs[1].shape
  
imports: import numpy
  import pytest
  from numpy.testing import assert_allclose
  from thinc.api import Dropout, Linear, Model, NumpyOps, add, clone, concatenate, map_list, noop
  from thinc.layers import chain, tuplify
label_desc: Use image node_id 37 for calling a global function with example usage: test_map_list() without return types