code: def test_predict_weights(X, expected):
      W = numpy.asarray([1.0, 0.0, 0.0, 1.0], dtype="f").reshape((2, 2))
      bias = numpy.asarray([0.0, 0.0], dtype="f")
  
      model = Linear(W.shape[0], W.shape[1])
      model.set_param("W", W)
      model.set_param("b", bias)
  
      scores = model.predict(X.reshape((1, -1)))
      assert_allclose(scores.ravel(), expected)
  
imports: import numpy
  import pytest
  from hypothesis import given, settings
  from mock import MagicMock
  from numpy.testing import assert_allclose
  from thinc.api import SGD, Dropout, Linear, chain
  from ..strategies import arrays_OI_O_BI
  from ..util import get_model, get_shape
label_desc: Use image node_id 13 for calling a global function with example usage: test_predict_weights(X, expected) without return types