fix: raise ValueError when provided seed is out-of-bounds

src/lightning/fabric/CHANGELOG.md

@@ -16,6 +16,10 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 -
 
+### Changed
+
+- Raise ValueError when seed is `out-of-bounds` or `cannot be cast to int` ([#21029](https://github.com/Lightning-AI/pytorch-lightning/pull/21029))
+
 
 ---
 

src/lightning/fabric/utilities/seed.py

@@ -27,7 +27,8 @@ def seed_everything(seed: Optional[int] = None, workers: bool = False, verbose:
     Args:
         seed: the integer value seed for global random state in Lightning.
             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.
+            ``PL_GLOBAL_SEED`` env variable is not set, then the seed defaults to 0. If seed is
+            not in bounds or cannot be cast to int, a ValueError is raised.
         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:
@@ -44,14 +45,12 @@ def seed_everything(seed: Optional[int] = None, workers: bool = False, verbose:
             try:
                 seed = int(env_seed)
             except ValueError:
-                seed = 0
-                rank_zero_warn(f"Invalid seed found: {repr(env_seed)}, seed set to {seed}")
+                raise ValueError(f"Invalid seed specified via PL_GLOBAL_SEED: {repr(env_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 = 0
+        raise ValueError(f"{seed} is not in bounds, numpy accepts from {min_seed_value} to {max_seed_value}")
 
     if verbose:
         log.info(rank_prefixed_message(f"Seed set to {seed}", _get_rank()))

tests/tests_fabric/utilities/test_seed.py

@@ -47,19 +47,29 @@ def test_correct_seed_with_environment_variable():
 
 @mock.patch.dict(os.environ, {"PL_GLOBAL_SEED": "invalid"}, clear=True)
 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 = seed_everything()
-    assert seed == 0
+    """Ensure that a ValueError is raised if an invalid seed is given."""
+    with pytest.raises(ValueError, match="Invalid seed specified"):
+        seed_everything()
 
 
 @mock.patch.dict(os.environ, {}, clear=True)
 @pytest.mark.parametrize("seed", [10e9, -10e9])
 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 = seed_everything(seed)
-    assert actual == 0
+    """Ensure that a ValueError is raised if an out-of-bounds seed is given."""
+    with pytest.raises(ValueError, match="is not in bounds"):
+        seed_everything(seed)
+
+
+def test_seed_everything_accepts_valid_seed_argument():
+    """Ensure that seed_everything returns the provided valid seed."""
+    seed_value = 45
+    assert seed_everything(seed_value) == seed_value
+
+
+@mock.patch.dict(os.environ, {"PL_GLOBAL_SEED": "17"}, clear=True)
+def test_seed_everything_accepts_valid_seed_from_env():
+    """Ensure that seed_everything uses the valid seed from the PL_GLOBAL_SEED environment variable."""
+    assert seed_everything() == 17
 
 
 def test_reset_seed_no_op():