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Add GPU documentation (#2695)

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* Add GPU documentation

* Update Python GPU tests
This commit is contained in:
Rory Mitchell
2017-09-10 19:42:46 +12:00
committed by GitHub
parent e6a9063344
commit 9c85903f0b
4 changed files with 176 additions and 82 deletions
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61
tests/python-gpu/test_gpu_updaters.py
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@@ -1,9 +1,9 @@
from __future__ import print_function
#pylint: skip-file
import sys
sys.path.append("../../tests/python")
import xgboost as xgb
import testing as tm
import numpy as np
import unittest
from nose.plugins.attrib import attr
@@ -12,14 +12,15 @@ rng = np.random.RandomState(1994)
dpath = 'demo/data/'
def eprint(*args, **kwargs):
print(*args, file=sys.stderr, **kwargs)
print(*args, file=sys.stdout, **kwargs)
@attr('gpu')
class TestGPU(unittest.TestCase):
def test_grow_gpu(self):
tm._skip_if_no_sklearn()
from sklearn.datasets import load_digits
try:
from sklearn.model_selection import train_test_split
@@ -115,10 +116,8 @@ class TestGPU(unittest.TestCase):
assert self.non_decreasing(res['train']['auc'])
assert res['train']['auc'][0] >= 0.85
def test_grow_gpu_hist(self):
n_gpus=-1
tm._skip_if_no_sklearn()
n_gpus = -1
from sklearn.datasets import load_digits
try:
from sklearn.model_selection import train_test_split
@@ -128,16 +127,15 @@ class TestGPU(unittest.TestCase):
ag_dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train')
ag_dtest = xgb.DMatrix(dpath + 'agaricus.txt.test')
for max_depth in range(3, 10): # TODO: Doesn't work with 2 for some tests
# eprint("max_depth=%d" % (max_depth))
for max_bin_i in range(3, 11):
max_bin = np.power(2, max_bin_i)
# eprint("max_bin=%d" % (max_bin))
for max_depth in range(3,10): # TODO: Doesn't work with 2 for some tests
#eprint("max_depth=%d" % (max_depth))
for max_bin_i in range(3,11):
max_bin = np.power(2,max_bin_i)
#eprint("max_bin=%d" % (max_bin))
# regression test --- hist must be same as exact on all-categorial data
ag_param = {'max_depth': max_depth,
'tree_method': 'exact',
@@ -172,13 +170,13 @@ class TestGPU(unittest.TestCase):
ag_res3 = {}
num_rounds = 10
#eprint("normal updater");
# eprint("normal updater");
xgb.train(ag_param, ag_dtrain, num_rounds, [(ag_dtrain, 'train'), (ag_dtest, 'test')],
evals_result=ag_res)
#eprint("grow_gpu_hist updater 1 gpu");
# eprint("grow_gpu_hist updater 1 gpu");
xgb.train(ag_param2, ag_dtrain, num_rounds, [(ag_dtrain, 'train'), (ag_dtest, 'test')],
evals_result=ag_res2)
#eprint("grow_gpu_hist updater %d gpus" % (n_gpus));
# eprint("grow_gpu_hist updater %d gpus" % (n_gpus));
xgb.train(ag_param3, ag_dtrain, num_rounds, [(ag_dtrain, 'train'), (ag_dtest, 'test')],
evals_result=ag_res3)
# assert 1==0
@@ -203,11 +201,11 @@ class TestGPU(unittest.TestCase):
'debug_verbose': 0,
'eval_metric': 'auc'}
res = {}
#eprint("digits: grow_gpu_hist updater 1 gpu");
# eprint("digits: grow_gpu_hist updater 1 gpu");
xgb.train(param, dtrain, num_rounds, [(dtrain, 'train'), (dtest, 'test')],
evals_result=res)
assert self.non_decreasing(res['train']['auc'])
#assert self.non_decreasing(res['test']['auc'])
# assert self.non_decreasing(res['test']['auc'])
param2 = {'objective': 'binary:logistic',
'nthread': 0,
'tree_method': 'gpu_hist',
@@ -217,13 +215,13 @@ class TestGPU(unittest.TestCase):
'debug_verbose': 0,
'eval_metric': 'auc'}
res2 = {}
#eprint("digits: grow_gpu_hist updater %d gpus" % (n_gpus));
# eprint("digits: grow_gpu_hist updater %d gpus" % (n_gpus));
xgb.train(param2, dtrain, num_rounds, [(dtrain, 'train'), (dtest, 'test')],
evals_result=res2)
assert self.non_decreasing(res2['train']['auc'])
#assert self.non_decreasing(res2['test']['auc'])
# assert self.non_decreasing(res2['test']['auc'])
assert res['train']['auc'] == res2['train']['auc']
#assert res['test']['auc'] == res2['test']['auc']
# assert res['test']['auc'] == res2['test']['auc']
######################################################################
# fail-safe test for dense data
@@ -244,7 +242,7 @@ class TestGPU(unittest.TestCase):
xgb.train(param, dtrain2, num_rounds, [(dtrain2, 'train')], evals_result=res)
assert self.non_decreasing(res['train']['auc'])
if max_bin>32:
if max_bin > 32:
assert res['train']['auc'][0] >= 0.85
for j in range(X2.shape[1]):
@@ -257,7 +255,7 @@ class TestGPU(unittest.TestCase):
xgb.train(param, dtrain3, num_rounds, [(dtrain3, 'train')], evals_result=res)
assert self.non_decreasing(res['train']['auc'])
if max_bin>32:
if max_bin > 32:
assert res['train']['auc'][0] >= 0.85
for j in range(X2.shape[1]):
@@ -268,7 +266,7 @@ class TestGPU(unittest.TestCase):
res = {}
xgb.train(param, dtrain4, num_rounds, [(dtrain4, 'train')], evals_result=res)
assert self.non_decreasing(res['train']['auc'])
if max_bin>32:
if max_bin > 32:
assert res['train']['auc'][0] >= 0.85
######################################################################
@@ -284,7 +282,7 @@ class TestGPU(unittest.TestCase):
res = {}
xgb.train(param, dtrain2, num_rounds, [(dtrain2, 'train')], evals_result=res)
assert self.non_decreasing(res['train']['auc'])
if max_bin>32:
if max_bin > 32:
assert res['train']['auc'][0] >= 0.85
######################################################################
# subsampling
@@ -302,7 +300,7 @@ class TestGPU(unittest.TestCase):
res = {}
xgb.train(param, dtrain2, num_rounds, [(dtrain2, 'train')], evals_result=res)
assert self.non_decreasing(res['train']['auc'])
if max_bin>32:
if max_bin > 32:
assert res['train']['auc'][0] >= 0.85
######################################################################
# fail-safe test for max_bin=2
@@ -317,9 +315,8 @@ class TestGPU(unittest.TestCase):
res = {}
xgb.train(param, dtrain2, num_rounds, [(dtrain2, 'train')], evals_result=res)
assert self.non_decreasing(res['train']['auc'])
if max_bin>32:
if max_bin > 32:
assert res['train']['auc'][0] >= 0.85
def non_decreasing(self, L):
return all((x - y) < 0.001 for x, y in zip(L, L[1:]))
return all((x - y) < 0.001 for x, y in zip(L, L[1:]))