chore: import upstream snapshot with attribution

rllib/utils/debug/deterministic.py

@@ -0,0 +1,42 @@
+import random
+from typing import Optional
+
+import numpy as np
+
+from ray.rllib.utils.annotations import DeveloperAPI
+from ray.rllib.utils.framework import try_import_tf
+from ray.rllib.utils.torch_utils import set_torch_seed
+
+
+@DeveloperAPI
+def update_global_seed_if_necessary(
+    framework: Optional[str] = None, seed: Optional[int] = None
+) -> None:
+    """Seed global modules such as random, numpy, torch, or tf.
+
+    This is useful for debugging and testing.
+
+    Args:
+        framework: The framework specifier (may be None).
+        seed: An optional int seed. If None, will not do
+            anything.
+    """
+    if seed is None:
+        return
+
+    # Python random module.
+    random.seed(seed)
+    # Numpy.
+    np.random.seed(seed)
+
+    # Torch.
+    if framework == "torch":
+        set_torch_seed(seed=seed)
+    elif framework == "tf2":
+        tf1, tf, tfv = try_import_tf()
+        # Tf2.x.
+        if tfv == 2:
+            tf.random.set_seed(seed)
+        # Tf1.x.
+        else:
+            tf1.set_random_seed(seed)