Change dangerous default random seed selection (#18846)

src/lightning/fabric/CHANGELOG.md

@@ -17,6 +17,8 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Calling a method other than `forward` that invokes submodules is now an error when the model is wrapped (e.g., with DDP) ([#18819](https://github.com/Lightning-AI/lightning/pull/18819))
 
 
+- `seed_everything()` without passing in a seed no longer randomly selects a seed, and now defaults to `0` ([#18846](https://github.com/Lightning-AI/lightning/pull/18846))
+
 
 ### Deprecated
 

src/lightning/fabric/utilities/seed.py

@@ -17,16 +17,16 @@
 
 
 def seed_everything(seed: Optional[int] = None, workers: bool = False) -> int:
-    r"""Function that sets seed for pseudo-random number generators in: pytorch, numpy, python.random In addition,
-    sets the following environment variables:
+    r"""Function that sets the seed for pseudo-random number generators in: torch, numpy, and Python's random module.
+    In addition, sets the following environment variables:
 
     - ``PL_GLOBAL_SEED``: will be passed to spawned subprocesses (e.g. ddp_spawn backend).
     - ``PL_SEED_WORKERS``: (optional) is set to 1 if ``workers=True``.
 
     Args:
         seed: the integer value seed for global random state in Lightning.
-            If ``None``, will read seed from ``PL_GLOBAL_SEED`` env variable
-            or select it randomly.
+            If ``None``, it will read the seed from ``PL_GLOBAL_SEED`` env variable. If ``None`` and the
+            ``PL_GLOBAL_SEED`` env variable is not set, then the seed defaults to 0.
         workers: if set to ``True``, will properly configure all dataloaders passed to the
             Trainer with a ``worker_init_fn``. If the user already provides such a function
             for their dataloaders, setting this argument will have no influence. See also:
@@ -36,20 +36,20 @@ def seed_everything(seed: Optional[int] = None, workers: bool = False) -> int:
     if seed is None:
         env_seed = os.environ.get("PL_GLOBAL_SEED")
         if env_seed is None:
-            seed = _select_seed_randomly(min_seed_value, max_seed_value)
+            seed = 0
             rank_zero_warn(f"No seed found, seed set to {seed}")
         else:
             try:
                 seed = int(env_seed)
             except ValueError:
-                seed = _select_seed_randomly(min_seed_value, max_seed_value)
+                seed = 0
                 rank_zero_warn(f"Invalid seed found: {repr(env_seed)}, seed set to {seed}")
     elif not isinstance(seed, int):
         seed = int(seed)
 
     if not (min_seed_value <= seed <= max_seed_value):
         rank_zero_warn(f"{seed} is not in bounds, numpy accepts from {min_seed_value} to {max_seed_value}")
-        seed = _select_seed_randomly(min_seed_value, max_seed_value)
+        seed = 0
 
     log.info(rank_prefixed_message(f"Seed set to {seed}", _get_rank()))
     os.environ["PL_GLOBAL_SEED"] = str(seed)
@@ -63,10 +63,6 @@ def seed_everything(seed: Optional[int] = None, workers: bool = False) -> int:
     return seed
 
 
-def _select_seed_randomly(min_seed_value: int = min_seed_value, max_seed_value: int = max_seed_value) -> int:
-    return random.randint(min_seed_value, max_seed_value)  # noqa: S311
-
-
 def reset_seed() -> None:
     r"""Reset the seed to the value that :func:`~lightning.fabric.utilities.seed.seed_everything` previously set.
 

src/lightning/pytorch/CHANGELOG.md

@@ -14,6 +14,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ### Changed
 
+- `seed_everything()` without passing in a seed no longer randomly selects a seed, and now defaults to `0` ([#18846](https://github.com/Lightning-AI/lightning/pull/18846))
 - `LightningCLI` no longer allows setting a normal class instance as default. A `lazy_instance` can be used instead ([#18822](https://github.com/Lightning-AI/lightning/pull/18822))
 
 

tests/tests_fabric/utilities/test_seed.py

@@ -4,10 +4,16 @@
 import lightning.fabric.utilities
 import pytest
 import torch
-from lightning.fabric.utilities import seed as seed_utils
 from lightning.fabric.utilities.seed import _collect_rng_states, _set_rng_states
 
 
+@mock.patch.dict(os.environ, clear=True)
+def test_default_seed():
+    """Test that the default seed is 0 when no seed provided and no environment variable set."""
+    assert lightning.fabric.utilities.seed.seed_everything() == 0
+    assert os.environ["PL_GLOBAL_SEED"] == "0"
+
+
 @mock.patch.dict(os.environ, {}, clear=True)
 def test_seed_stays_same_with_multiple_seed_everything_calls():
     """Ensure that after the initial seed everything, the seed stays the same for the same run."""
@@ -30,22 +36,20 @@ def test_correct_seed_with_environment_variable():
 
 
 @mock.patch.dict(os.environ, {"PL_GLOBAL_SEED": "invalid"}, clear=True)
-@mock.patch.object(seed_utils, attribute="_select_seed_randomly", return_value=123)
-def test_invalid_seed(_):
+def test_invalid_seed():
     """Ensure that we still fix the seed even if an invalid seed is given."""
     with pytest.warns(UserWarning, match="Invalid seed found"):
         seed = lightning.fabric.utilities.seed.seed_everything()
-    assert seed == 123
+    assert seed == 0
 
 
 @mock.patch.dict(os.environ, {}, clear=True)
-@mock.patch.object(seed_utils, attribute="_select_seed_randomly", return_value=123)
 @pytest.mark.parametrize("seed", [10e9, -10e9])
-def test_out_of_bounds_seed(_, seed):
+def test_out_of_bounds_seed(seed):
     """Ensure that we still fix the seed even if an out-of-bounds seed is given."""
     with pytest.warns(UserWarning, match="is not in bounds"):
         actual = lightning.fabric.utilities.seed.seed_everything(seed)
-    assert actual == 123
+    assert actual == 0
 
 
 def test_reset_seed_no_op():