code: def test_predict_extensive(W_b_input):
      W, b, input_ = W_b_input
      nr_out, nr_in = W.shape
      model = Linear(nr_out, nr_in)
      model.set_param("W", W)
      model.set_param("b", b)
  
      einsummed = numpy.einsum(
          "bi,oi->bo",
          numpy.asarray(input_, dtype="float32"),
          numpy.asarray(W, dtype="float32"),
          optimize=False,
      )
  
      expected_output = einsummed + b
  
      predicted_output = model.predict(input_)
      assert_allclose(
          predicted_output, expected_output, rtol=1e-04, atol=0.0001
      )
  
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 7 for calling a global function with example usage: test_predict_extensive(W_b_input) without return types