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# SPDX-License-Identifier: Apache-2.0
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Regression tests for :mod:`gr00t.utils.determinism`.
Covers the four contracts future refactors must preserve:
1. Opt-in: no arg and no ``GR00T_EVAL_SEED`` => no-op, no global flags flipped.
2. Seeding actually makes Python / NumPy / torch CPU RNGs reproducible.
3. ``GR00T_EVAL_SEED=N`` is equivalent to ``seed_everything(N)``.
4. A malformed ``GR00T_EVAL_SEED`` raises instead of being silently ignored.
"""
from __future__ import annotations
import random
from gr00t.utils.determinism import EVAL_SEED_ENV_VAR, get_eval_seed, seed_everything
import numpy as np
import pytest
import torch
@pytest.fixture(autouse=True)
def _restore_deterministic_algorithms(monkeypatch):
"""Undo the one piece of global state that can break unrelated tests.
``use_deterministic_algorithms(True)`` makes legitimately-nondeterministic
ops in later tests raise; cudnn flags and CUBLAS env var are harmless to
leak. We also ensure the env var is not inherited from the outer shell.
"""
monkeypatch.delenv(EVAL_SEED_ENV_VAR, raising=False)
saved = torch.are_deterministic_algorithms_enabled()
try:
yield
finally:
torch.use_deterministic_algorithms(saved, warn_only=True)
def _sample():
return (random.random(), float(np.random.rand()), torch.rand(4).tolist())
def test_noop_when_unset():
before = torch.are_deterministic_algorithms_enabled()
assert seed_everything() is None
assert torch.are_deterministic_algorithms_enabled() == before
def test_seed_is_reproducible():
seed_everything(42)
first = _sample()
seed_everything(42)
assert _sample() == first
def test_env_var_fallback_matches_explicit_arg(monkeypatch):
monkeypatch.setenv(EVAL_SEED_ENV_VAR, "42")
assert seed_everything() == 42
via_env = _sample()
assert seed_everything(42) == 42
assert _sample() == via_env
def test_invalid_env_var_raises(monkeypatch):
monkeypatch.setenv(EVAL_SEED_ENV_VAR, "not-an-int")
with pytest.raises(ValueError, match=EVAL_SEED_ENV_VAR):
get_eval_seed()
def test_cudnn_flags_flipped_when_seeded():
seed_everything(0)
assert torch.backends.cudnn.deterministic is True
assert torch.backends.cudnn.benchmark is False
assert torch.are_deterministic_algorithms_enabled() is True
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