4fe67f10b4
- Initialize one partitioner for each batch. - Collect partition size during initialization. - Support base ridx in the finalization.
65 lines
1.5 KiB
Python
65 lines
1.5 KiB
Python
import sys
|
|
|
|
import pytest
|
|
from hypothesis import given, settings, strategies
|
|
|
|
from xgboost.testing import no_cupy
|
|
from xgboost.testing.updater import check_quantile_loss_extmem
|
|
|
|
sys.path.append("tests/python")
|
|
from test_data_iterator import run_data_iterator
|
|
from test_data_iterator import test_single_batch as cpu_single_batch
|
|
|
|
|
|
def test_gpu_single_batch() -> None:
|
|
cpu_single_batch("hist", "cuda")
|
|
|
|
|
|
@pytest.mark.skipif(**no_cupy())
|
|
@given(
|
|
strategies.integers(0, 1024),
|
|
strategies.integers(1, 7),
|
|
strategies.integers(0, 8),
|
|
strategies.booleans(),
|
|
strategies.booleans(),
|
|
strategies.booleans(),
|
|
)
|
|
@settings(deadline=None, max_examples=16, print_blob=True)
|
|
def test_gpu_data_iterator(
|
|
n_samples_per_batch: int,
|
|
n_features: int,
|
|
n_batches: int,
|
|
subsample: bool,
|
|
use_cupy: bool,
|
|
on_host: bool,
|
|
) -> None:
|
|
run_data_iterator(
|
|
n_samples_per_batch,
|
|
n_features,
|
|
n_batches,
|
|
"hist",
|
|
subsample=subsample,
|
|
device="cuda",
|
|
use_cupy=use_cupy,
|
|
on_host=on_host,
|
|
)
|
|
|
|
|
|
def test_cpu_data_iterator() -> None:
|
|
"""Make sure CPU algorithm can handle GPU inputs"""
|
|
run_data_iterator(
|
|
1024,
|
|
2,
|
|
3,
|
|
"approx",
|
|
device="cuda",
|
|
subsample=False,
|
|
use_cupy=True,
|
|
on_host=False,
|
|
)
|
|
|
|
|
|
def test_quantile_objective() -> None:
|
|
with pytest.raises(ValueError, match="external memory"):
|
|
check_quantile_loss_extmem(2, 2, 2, "hist", "cuda")
|