Add context manager for seeding (#164)

lerobot/common/utils/utils.py

@@ -1,8 +1,10 @@
 import logging
 import os.path as osp
 import random
+from contextlib import contextmanager
 from datetime import datetime
 from pathlib import Path
+from typing import Generator
 
 import hydra
 import numpy as np
@@ -39,6 +41,31 @@ def set_global_seed(seed):
     torch.cuda.manual_seed_all(seed)
 
 
+@contextmanager
+def seeded_context(seed: int) -> Generator[None, None, None]:
+    """Set the seed when entering a context, and restore the prior random state at exit.
+
+    Example usage:
+
+    ```
+    a = random.random()  # produces some random number
+    with seeded_context(1337):
+        b = random.random()  # produces some other random number
+    c = random.random()  # produces yet another random number, but the same it would have if we never made `b`
+    ```
+    """
+    random_state = random.getstate()
+    np_random_state = np.random.get_state()
+    torch_random_state = torch.random.get_rng_state()
+    torch_cuda_random_state = torch.cuda.random.get_rng_state()
+    set_global_seed(seed)
+    yield None
+    random.setstate(random_state)
+    np.random.set_state(np_random_state)
+    torch.random.set_rng_state(torch_random_state)
+    torch.cuda.random.set_rng_state(torch_cuda_random_state)
+
+
 def init_logging():
     def custom_format(record):
         dt = datetime.now().strftime("%Y-%m-%d %H:%M:%S")

tests/test_utils.py

@@ -0,0 +1,38 @@
+import random
+from typing import Callable
+
+import numpy as np
+import pytest
+import torch
+
+from lerobot.common.utils.utils import seeded_context, set_global_seed
+
+
+@pytest.mark.parametrize(
+    "rand_fn",
+    [
+        random.random,
+        np.random.random,
+        lambda: torch.rand(1).item(),
+    ]
+    + [lambda: torch.rand(1, device="cuda")]
+    if torch.cuda.is_available()
+    else [],
+)
+def test_seeding(rand_fn: Callable[[], int]):
+    set_global_seed(0)
+    a = rand_fn()
+    with seeded_context(1337):
+        c = rand_fn()
+    b = rand_fn()
+    set_global_seed(0)
+    a_ = rand_fn()
+    b_ = rand_fn()
+    # Check that `set_global_seed` lets us reproduce a and b.
+    assert a_ == a
+    # Additionally, check that the `seeded_context` didn't interrupt the global RNG.
+    assert b_ == b
+    set_global_seed(1337)
+    c_ = rand_fn()
+    # Check that `seeded_context` and `global_seed` give the same reproducibility.
+    assert c_ == c