Upgrade to CUDA 10.0

Jenkinsfile

@@ -64,7 +64,6 @@ pipeline {
  'build-cpu': { BuildCPU() },
  'build-cpu-rabit-mock': { BuildCPUMock() },
  'build-cpu-non-omp': { BuildCPUNonOmp() },
- 'build-gpu-cuda9.0': { BuildCUDA(cuda_version: '9.0') },
  'build-gpu-cuda10.0': { BuildCUDA(cuda_version: '10.0') },
  'build-gpu-cuda10.1': { BuildCUDA(cuda_version: '10.1') },
  'build-jvm-packages': { BuildJVMPackages(spark_version: '2.4.3') },
@@ -251,10 +250,10 @@ def BuildCUDA(args) {
  ${dockerRun} ${container_type} ${docker_binary} ${docker_args} bash -c "cd python-package && rm -rf dist/* && python setup.py bdist_wheel --universal"
  ${dockerRun} ${container_type} ${docker_binary} ${docker_args} python3 tests/ci_build/rename_whl.py python-package/dist/*.whl ${commit_id} manylinux2010_x86_64
  """
- // Stash wheel for CUDA 9.0 target
- if (args.cuda_version == '9.0') {
+ // Stash wheel for CUDA 10.0 target
+ if (args.cuda_version == '10.0') {
  echo 'Stashing Python wheel...'
- stash name: 'xgboost_whl_cuda9', includes: 'python-package/dist/*.whl'
+ stash name: 'xgboost_whl_cuda10', includes: 'python-package/dist/*.whl'
  path = ("${BRANCH_NAME}" == 'master') ? '' : "${BRANCH_NAME}/"
  s3Upload bucket: 'xgboost-nightly-builds', path: path, acl: 'PublicRead', workingDir: 'python-package/dist', includePathPattern:'**/*.whl'
  echo 'Stashing C++ test executable (testxgboost)...'
@@ -298,7 +297,7 @@ def BuildJVMDoc() {
 
 def TestPythonCPU() {
  node('linux && cpu') {
- unstash name: 'xgboost_whl_cuda9'
+ unstash name: 'xgboost_whl_cuda10'
  unstash name: 'srcs'
  unstash name: 'xgboost_cli'
  echo "Test Python CPU"
@@ -315,7 +314,7 @@ def TestPythonCPU() {
 def TestPythonGPU(args) {
  nodeReq = (args.multi_gpu) ? 'linux && mgpu' : 'linux && gpu'
  node(nodeReq) {
- unstash name: 'xgboost_whl_cuda9'
+ unstash name: 'xgboost_whl_cuda10'
  unstash name: 'srcs'
  echo "Test Python GPU: CUDA ${args.cuda_version}"
  def container_type = "gpu"

tests/python-gpu/test_gpu_basic_models.py

@@ -12,25 +12,15 @@
 class TestGPUBasicModels(unittest.TestCase):
  cputest = test_bm.TestModels()
 
- def test_eta_decay_gpu_hist(self):
- self.cputest.run_eta_decay('gpu_hist')
-
- def test_deterministic_gpu_hist(self):
- kRows = 1000
- kCols = 64
- kClasses = 4
- # Create large values to force rounding.
- X = np.random.randn(kRows, kCols) * 1e4
- y = np.random.randint(0, kClasses, size=kRows)
-
+ def run_cls(self, X, y, deterministic):
  cls = xgb.XGBClassifier(tree_method='gpu_hist',
- deterministic_histogram=True,
+ deterministic_histogram=deterministic,
  single_precision_histogram=True)
  cls.fit(X, y)
  cls.get_booster().save_model('test_deterministic_gpu_hist-0.json')
 
  cls = xgb.XGBClassifier(tree_method='gpu_hist',
- deterministic_histogram=True,
+ deterministic_histogram=deterministic,
  single_precision_histogram=True)
  cls.fit(X, y)
  cls.get_booster().save_model('test_deterministic_gpu_hist-1.json')
@@ -40,7 +30,24 @@ def test_deterministic_gpu_hist(self):
  with open('test_deterministic_gpu_hist-1.json', 'r') as fd:
  model_1 = fd.read()
 
- assert hash(model_0) == hash(model_1)
-
  os.remove('test_deterministic_gpu_hist-0.json')
  os.remove('test_deterministic_gpu_hist-1.json')
+
+ return hash(model_0), hash(model_1)
+
+ def test_eta_decay_gpu_hist(self):
+ self.cputest.run_eta_decay('gpu_hist')
+
+ def test_deterministic_gpu_hist(self):
+ kRows = 1000
+ kCols = 64
+ kClasses = 4
+ # Create large values to force rounding.
+ X = np.random.randn(kRows, kCols) * 1e4
+ y = np.random.randint(0, kClasses, size=kRows) * 1e4
+
+ model_0, model_1 = self.run_cls(X, y, True)
+ assert model_0 == model_1
+
+ model_0, model_1 = self.run_cls(X, y, False)
+ assert model_0 != model_1