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gradient can be zero and two parameter cancellation is caught

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Max Zwiessele 2014-03-31 14:09:47 +01:00
parent 59ff2c8d00
commit 68a8c3a691
1 changed files with 0 additions and 1 deletions
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GPy/core/model.py
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@ -294,7 +294,6 @@ class Model(Parameterized):
global_diff = np.abs(f1 - f2) < tolerance and np.allclose(gradient, 0, atol=tolerance)
if global_ratio is np.nan:
global_ratio = 0
print global_ratio, global_diff, np.allclose(gradient, 0, atol=tolerance), np.abs(1. - global_ratio), np.abs(f1-f2).sum() + np.abs((2 * np.dot(dx, gradient))).sum()
return np.abs(1. - global_ratio) < tolerance or global_diff
else:
# check the gradient of each parameter individually, and do some pretty printing