Relax test for decision stump in distributed environment. (#6919)
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@ -1023,7 +1023,17 @@ class TestWithDask:
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evals=[(m, 'train')])['history']
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note(history)
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history = history['train'][dataset.metric]
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assert tm.non_increasing(history)
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def is_stump():
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return params["max_depth"] == 1 or params["max_leaves"] == 1
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def minimum_bin():
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return "max_bin" in params and params["max_bin"] == 2
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if minimum_bin() and is_stump():
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assert tm.non_increasing(history, tolerance=1e-3)
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else:
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assert tm.non_increasing(history)
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# Make sure that it's decreasing
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assert history[-1] < history[0]
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