(
n_samples_per_batch: int,
n_features: int,
n_batches: int,
tree_method: str,
subsample: bool,
device: str,
use_cupy: bool,
on_host: bool,
)
| 75 | |
| 76 | |
| 77 | def run_data_iterator( |
| 78 | n_samples_per_batch: int, |
| 79 | n_features: int, |
| 80 | n_batches: int, |
| 81 | tree_method: str, |
| 82 | subsample: bool, |
| 83 | device: str, |
| 84 | use_cupy: bool, |
| 85 | on_host: bool, |
| 86 | ) -> None: |
| 87 | n_rounds = 2 |
| 88 | # The test is more difficult to pass if the subsample rate is smaller as the root_sum |
| 89 | # is accumulated in parallel. Reductions with different number of entries lead to |
| 90 | # different floating point errors. |
| 91 | subsample_rate = 0.8 if subsample else 1.0 |
| 92 | |
| 93 | it = IteratorForTest( |
| 94 | *make_batches(n_samples_per_batch, n_features, n_batches, use_cupy), |
| 95 | cache="cache", |
| 96 | on_host=on_host, |
| 97 | ) |
| 98 | if n_batches == 0: |
| 99 | with pytest.raises(ValueError, match="1 batch"): |
| 100 | Xy = xgb.DMatrix(it) |
| 101 | return |
| 102 | |
| 103 | Xy_it = xgb.DMatrix(it) |
| 104 | assert Xy_it.num_row() == n_samples_per_batch * n_batches |
| 105 | assert Xy_it.num_col() == n_features |
| 106 | |
| 107 | parameters = { |
| 108 | "tree_method": tree_method, |
| 109 | "max_depth": 2, |
| 110 | "subsample": subsample_rate, |
| 111 | "device": device, |
| 112 | "seed": 0, |
| 113 | } |
| 114 | |
| 115 | if device.find("cuda") != -1: |
| 116 | parameters["sampling_method"] = "gradient_based" |
| 117 | |
| 118 | results_from_it: Dict[str, Dict[str, List[float]]] = {} |
| 119 | from_it = xgb.train( |
| 120 | parameters, |
| 121 | Xy_it, |
| 122 | num_boost_round=n_rounds, |
| 123 | evals=[(Xy_it, "Train")], |
| 124 | evals_result=results_from_it, |
| 125 | verbose_eval=False, |
| 126 | ) |
| 127 | if not subsample: |
| 128 | assert non_increasing(results_from_it["Train"]["rmse"]) |
| 129 | |
| 130 | X, y, w = it.as_arrays() |
| 131 | if use_cupy: |
| 132 | _y = y.get() |
| 133 | else: |
| 134 | _y = y |
no test coverage detected