c5b229632d
* prevent multi-gpu usage * fix distributed test * combine gpu predictor tests * set upper bound on n_gpus
51 lines
2.0 KiB
Python
51 lines
2.0 KiB
Python
import numpy as np
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import sys
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import unittest
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import pytest
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sys.path.append("tests/python")
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from regression_test_utilities import run_suite, parameter_combinations, \
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assert_results_non_increasing
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def assert_gpu_results(cpu_results, gpu_results):
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for cpu_res, gpu_res in zip(cpu_results, gpu_results):
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# Check final eval result roughly equivalent
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assert np.allclose(cpu_res["eval"][-1],
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gpu_res["eval"][-1], 1e-2, 1e-2)
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datasets = ["Boston", "Cancer", "Digits", "Sparse regression",
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"Sparse regression with weights", "Small weights regression"]
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class TestGPU(unittest.TestCase):
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def test_gpu_hist(self):
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test_param = parameter_combinations({'n_gpus': [1], 'max_depth': [2, 8],
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'max_leaves': [255, 4],
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'max_bin': [2, 256],
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'grow_policy': ['lossguide']})
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test_param.append({'single_precision_histogram': True})
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test_param.append({'min_child_weight': 0,
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'lambda': 0})
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for param in test_param:
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param['tree_method'] = 'gpu_hist'
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gpu_results = run_suite(param, select_datasets=datasets)
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assert_results_non_increasing(gpu_results, 1e-2)
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param['tree_method'] = 'hist'
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cpu_results = run_suite(param, select_datasets=datasets)
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assert_gpu_results(cpu_results, gpu_results)
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@pytest.mark.mgpu
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def test_specified_gpu_id_gpu_update(self):
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variable_param = {'n_gpus': [1],
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'gpu_id': [1],
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'max_depth': [8],
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'max_leaves': [255, 4],
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'max_bin': [2, 64],
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'grow_policy': ['lossguide'],
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'tree_method': ['gpu_hist']}
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for param in parameter_combinations(variable_param):
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gpu_results = run_suite(param, select_datasets=datasets)
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assert_results_non_increasing(gpu_results, 1e-2)
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