9c9070aea2
* Do not derive from unittest.TestCase (not needed for pytest) * assertRaises -> pytest.raises * Simplify test_empty_dmatrix with test parametrization * setUpClass -> setup_class, tearDownClass -> teardown_class * Don't import unittest; import pytest * Use plain assert * Use parametrized tests in more places * Fix test_gpu_with_sklearn.py * Put back run_empty_dmatrix_reg / run_empty_dmatrix_cls * Fix test_eta_decay_gpu_hist * Add parametrized tests for monotone constraints * Fix test names * Remove test parametrization * Revise test_slice to be not flaky
57 lines
2.1 KiB
Python
57 lines
2.1 KiB
Python
import numpy as np
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import xgboost as xgb
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import json
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rng = np.random.RandomState(1994)
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class TestGPUTrainingContinuation:
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def run_training_continuation(self, use_json):
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kRows = 64
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kCols = 32
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X = np.random.randn(kRows, kCols)
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y = np.random.randn(kRows)
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dtrain = xgb.DMatrix(X, y)
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params = {'tree_method': 'gpu_hist', 'max_depth': '2',
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'gamma': '0.1', 'alpha': '0.01',
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'enable_experimental_json_serialization': use_json}
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bst_0 = xgb.train(params, dtrain, num_boost_round=64)
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dump_0 = bst_0.get_dump(dump_format='json')
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bst_1 = xgb.train(params, dtrain, num_boost_round=32)
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bst_1 = xgb.train(params, dtrain, num_boost_round=32, xgb_model=bst_1)
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dump_1 = bst_1.get_dump(dump_format='json')
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def recursive_compare(obj_0, obj_1):
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if isinstance(obj_0, float):
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assert np.isclose(obj_0, obj_1, atol=1e-6)
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elif isinstance(obj_0, str):
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assert obj_0 == obj_1
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elif isinstance(obj_0, int):
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assert obj_0 == obj_1
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elif isinstance(obj_0, dict):
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keys_0 = list(obj_0.keys())
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keys_1 = list(obj_1.keys())
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values_0 = list(obj_0.values())
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values_1 = list(obj_1.values())
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for i in range(len(obj_0.items())):
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assert keys_0[i] == keys_1[i]
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if list(obj_0.keys())[i] != 'missing':
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recursive_compare(values_0[i],
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values_1[i])
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else:
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for i in range(len(obj_0)):
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recursive_compare(obj_0[i], obj_1[i])
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assert len(dump_0) == len(dump_1)
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for i in range(len(dump_0)):
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obj_0 = json.loads(dump_0[i])
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obj_1 = json.loads(dump_1[i])
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recursive_compare(obj_0, obj_1)
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def test_gpu_training_continuation_binary(self):
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self.run_training_continuation(False)
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def test_gpu_training_continuation_json(self):
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self.run_training_continuation(True)
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