Files
AstrAI/tests/trainer/test_trainer.py
T
ViperEkura a27c8a819d test: prune low-value and duplicate tests
- Remove tautological test_trainer assertions that never trained
- Drop grpo isfinite-only smokes and merge frozen-model checks via parametrize
- Merge duplicate tool_parser cases (find/streaming/factory) with parametrize
- Collapse duplicate dataset store/detect_format tests
- Remove misleading scheduler/task tests that asserted the opposite of their names
- Merge signal-handler SIGTERM/SIGINT into one parametrized case
- Drop cross-file grpo strategy duplication kept in online_strategy
2026-08-01 16:01:20 +08:00

37 lines
1.1 KiB
Python

import pytest
from astrai.trainer import Trainer
def test_training_runs_with_various_batch_sizes(
base_test_env, random_dataset, train_config_factory
):
"""Training should complete for a range of batch sizes without error."""
for batch_per_device in [1, 2, 4]:
train_config = train_config_factory(
model_fn=lambda: base_test_env["model"],
dataset=random_dataset,
test_dir=base_test_env["test_dir"],
device=base_test_env["device"],
batch_per_device=batch_per_device,
)
trainer = Trainer(train_config)
trainer.train()
@pytest.mark.slow
def test_gradient_accumulation_runs(
base_test_env, random_dataset, train_config_factory
):
"""Training with gradient accumulation should complete."""
train_config = train_config_factory(
model_fn=lambda: base_test_env["model"],
dataset=random_dataset,
test_dir=base_test_env["test_dir"],
device=base_test_env["device"],
batch_per_device=2,
grad_accum_steps=4,
)
trainer = Trainer(train_config)
trainer.train()