code: def numeric_gradient(predict, weights, epsilon=1e-4):
      out1 = predict(weights + epsilon)
      out2 = predict(weights - epsilon)
      return (out1 - out2) / (2 * epsilon)
  
imports: from functools import partial
  import numpy
  import pytest
  from numpy.testing import assert_allclose
  from thinc.api import Linear, NumpyOps, Relu, chain
label_desc: Use image node_id 11 for calling a global function with example usage: numeric_gradient(predict, weights, epsilon) and returns: unknown