code: def test_predict_bias(model2):
      input_ = model2.ops.alloc2f(1, model2.get_dim("nI"))
      target_scores = model2.ops.alloc2f(1, model2.get_dim("nI"))
      scores = model2.predict(input_)
      assert_allclose(scores[0], target_scores[0])
      # Set bias for class 0
      model2.get_param("b")[0] = 2.0
      target_scores[0, 0] = 2.0
      scores = model2.predict(input_)
      assert_allclose(scores, target_scores)
      # Set bias for class 1
      model2.get_param("b")[1] = 5.0
      target_scores[0, 1] = 5.0
      scores = model2.predict(input_)
      assert_allclose(scores, target_scores)
  
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 12 for calling a global function with example usage: test_predict_bias(model2) without return types