[Fix] Unpin torch beyond 2.6.0 & torchcodec beyond 0.2.1

pyproject.toml

@@ -68,8 +68,8 @@ dependencies = [
     "pyzmq>=26.2.1",
     "rerun-sdk>=0.21.0",
     "termcolor>=2.4.0",
-    "torch>=2.2.1,<2.7",
-    "torchcodec==0.2.1; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')",
+    "torch>=2.2.1",
+    "torchcodec>=0.2.1; sys_platform != 'win32' and (sys_platform != 'linux' or (platform_machine != 'aarch64' and platform_machine != 'arm64' and platform_machine != 'armv7l')) and (sys_platform != 'darwin' or platform_machine != 'x86_64')",
     "torchvision>=0.21.0",
     "wandb>=0.16.3",
     "zarr>=2.17.0",

tests/artifacts/image_transforms/save_image_transforms_to_safetensors.py

@@ -28,7 +28,7 @@
 from lerobot.common.utils.random_utils import seeded_context
 
 ARTIFACT_DIR = Path("tests/artifacts/image_transforms")
-DATASET_REPO_ID = "lerobot/aloha_mobile_shrimp"
+DATASET_REPO_ID = "lerobot/aloha_static_cups_open"
 
 
 def save_default_config_transform(original_frame: torch.Tensor, output_dir: Path):

tests/datasets/test_image_transforms.py

@@ -16,6 +16,7 @@
 
 import pytest
 import torch
+from packaging import version
 from safetensors.torch import load_file
 from torchvision.transforms import v2
 from torchvision.transforms.v2 import functional as F  # noqa: N812
@@ -253,7 +254,14 @@ def test_backward_compatibility_single_transforms(
 
 
 @require_x86_64_kernel
+@pytest.mark.skipif(
+    version.parse(torch.__version__) < version.parse("2.7.0"),
+    reason="Test artifacts were generated with PyTorch >= 2.7.0 which has different multinomial behavior",
+)
 def test_backward_compatibility_default_config(img_tensor, default_transforms):
+    # NOTE: PyTorch versions have different randomness, it might break this test.
+    # See this PR: https://github.com/huggingface/lerobot/pull/1127.
+
     cfg = ImageTransformsConfig(enable=True)
     default_tf = ImageTransforms(cfg)
 

tests/optim/test_schedulers.py

@@ -37,7 +37,6 @@ def test_diffuser_scheduler(optimizer):
         "base_lrs": [0.001],
         "last_epoch": 1,
         "lr_lambdas": [None],
-        "verbose": False,
     }
     assert scheduler.state_dict() == expected_state_dict
 
@@ -56,7 +55,6 @@ def test_vqbet_scheduler(optimizer):
         "base_lrs": [0.001],
         "last_epoch": 1,
         "lr_lambdas": [None],
-        "verbose": False,
     }
     assert scheduler.state_dict() == expected_state_dict
 
@@ -77,7 +75,6 @@ def test_cosine_decay_with_warmup_scheduler(optimizer):
         "base_lrs": [0.001],
         "last_epoch": 1,
         "lr_lambdas": [None],
-        "verbose": False,
     }
     assert scheduler.state_dict() == expected_state_dict
 

tests/policies/test_policies.py

@@ -20,6 +20,7 @@
 import einops
 import pytest
 import torch
+from packaging import version
 from safetensors.torch import load_file
 
 from lerobot import available_policies
@@ -408,7 +409,16 @@ def test_backward_compatibility(ds_repo_id: str, policy_name: str, policy_kwargs
         4. Check that this test now passes.
         5. Remember to restore `tests/scripts/save_policy_to_safetensors.py` to its original state.
         6. Remember to stage and commit the resulting changes to `tests/artifacts`.
+
+    NOTE: If the test does not pass, and you don't change the policy, it is likely that the test artifact
+    is out of date. For example, some PyTorch versions have different randomness, see this PR:
+    https://github.com/huggingface/lerobot/pull/1127.
+
     """
+    # NOTE: ACT policy has different randomness, after PyTorch 2.7.0
+    if policy_name == "act" and version.parse(torch.__version__) < version.parse("2.7.0"):
+        pytest.skip(f"Skipping act policy test with PyTorch {torch.__version__}. Requires PyTorch >= 2.7.0")
+
     ds_name = ds_repo_id.split("/")[-1]
     artifact_dir = Path("tests/artifacts/policies") / f"{ds_name}_{policy_name}_{file_name_extra}"
     saved_output_dict = load_file(artifact_dir / "output_dict.safetensors")