Update pre-commits (#733)

tests/scripts/save_dataset_to_safetensors.py

@@ -49,17 +49,17 @@ def save_dataset_to_safetensors(output_dir, repo_id="lerobot/pusht"):
     # save 2 first frames of first episode
     i = dataset.episode_data_index["from"][0].item()
     save_file(dataset[i], repo_dir / f"frame_{i}.safetensors")
-    save_file(dataset[i + 1], repo_dir / f"frame_{i+1}.safetensors")
+    save_file(dataset[i + 1], repo_dir / f"frame_{i + 1}.safetensors")
 
     # save 2 frames at the middle of first episode
     i = int((dataset.episode_data_index["to"][0].item() - dataset.episode_data_index["from"][0].item()) / 2)
     save_file(dataset[i], repo_dir / f"frame_{i}.safetensors")
-    save_file(dataset[i + 1], repo_dir / f"frame_{i+1}.safetensors")
+    save_file(dataset[i + 1], repo_dir / f"frame_{i + 1}.safetensors")
 
     # save 2 last frames of first episode
     i = dataset.episode_data_index["to"][0].item()
-    save_file(dataset[i - 2], repo_dir / f"frame_{i-2}.safetensors")
-    save_file(dataset[i - 1], repo_dir / f"frame_{i-1}.safetensors")
+    save_file(dataset[i - 2], repo_dir / f"frame_{i - 2}.safetensors")
+    save_file(dataset[i - 1], repo_dir / f"frame_{i - 1}.safetensors")
 
     # TODO(rcadene): Enable testing on second and last episode
     # We currently cant because our test dataset only contains the first episode

tests/test_datasets.py

@@ -336,9 +336,9 @@ def test_backward_compatibility(repo_id):
         assert new_keys == old_keys, f"{new_keys=} and {old_keys=} are not the same"
 
         for key in new_frame:
-            assert torch.isclose(
-                new_frame[key], old_frame[key]
-            ).all(), f"{key=} for index={i} does not contain the same value"
+            assert torch.isclose(new_frame[key], old_frame[key]).all(), (
+                f"{key=} for index={i} does not contain the same value"
+            )
 
     # test2 first frames of first episode
     i = dataset.episode_data_index["from"][0].item()

tests/test_image_transforms.py

@@ -343,13 +343,13 @@ def test_save_all_transforms(img_tensor_factory, tmp_path):
     # Check if the combined transforms directory exists and contains the right files
     combined_transforms_dir = tmp_path / "all"
     assert combined_transforms_dir.exists(), "Combined transforms directory was not created."
-    assert any(
-        combined_transforms_dir.iterdir()
-    ), "No transformed images found in combined transforms directory."
+    assert any(combined_transforms_dir.iterdir()), (
+        "No transformed images found in combined transforms directory."
+    )
     for i in range(1, n_examples + 1):
-        assert (
-            combined_transforms_dir / f"{i}.png"
-        ).exists(), f"Combined transform image {i}.png was not found."
+        assert (combined_transforms_dir / f"{i}.png").exists(), (
+            f"Combined transform image {i}.png was not found."
+        )
 
 
 def test_save_each_transform(img_tensor_factory, tmp_path):
@@ -369,6 +369,6 @@ def test_save_each_transform(img_tensor_factory, tmp_path):
         # Check for specific files within each transform directory
         expected_files = [f"{i}.png" for i in range(1, n_examples + 1)] + ["min.png", "max.png", "mean.png"]
         for file_name in expected_files:
-            assert (
-                transform_dir / file_name
-            ).exists(), f"{file_name} was not found in {transform} directory."
+            assert (transform_dir / file_name).exists(), (
+                f"{file_name} was not found in {transform} directory."
+            )

tests/test_online_buffer.py

@@ -132,9 +132,9 @@ def test_fifo():
     buffer.add_data(new_data)
     n_more_episodes = 2
     # Developer sanity check (in case someone changes the global `buffer_capacity`).
-    assert (
-        n_episodes + n_more_episodes
-    ) * n_frames_per_episode > buffer_capacity, "Something went wrong with the test code."
+    assert (n_episodes + n_more_episodes) * n_frames_per_episode > buffer_capacity, (
+        "Something went wrong with the test code."
+    )
     more_new_data = make_spoof_data_frames(n_more_episodes, n_frames_per_episode)
     buffer.add_data(more_new_data)
     assert len(buffer) == buffer_capacity, "The buffer should be full."
@@ -203,9 +203,9 @@ def test_delta_timestamps_outside_tolerance_outside_episode_range():
     item = buffer[2]
     data, is_pad = item["index"], item["index_is_pad"]
     assert torch.equal(data, torch.tensor([0, 0, 2, 4, 4])), "Data does not match expected values"
-    assert torch.equal(
-        is_pad, torch.tensor([True, False, False, True, True])
-    ), "Padding does not match expected values"
+    assert torch.equal(is_pad, torch.tensor([True, False, False, True, True])), (
+        "Padding does not match expected values"
+    )
 
 
 # Arbitrarily set small dataset sizes, making sure to have uneven sizes.

tests/test_policies.py

@@ -193,12 +193,12 @@ def test_policy(ds_repo_id, env_name, env_kwargs, policy_name, policy_kwargs):
     observation_ = deepcopy(observation)
     with torch.inference_mode():
         action = policy.select_action(observation).cpu().numpy()
-    assert set(observation) == set(
-        observation_
-    ), "Observation batch keys are not the same after a forward pass."
-    assert all(
-        torch.equal(observation[k], observation_[k]) for k in observation
-    ), "Observation batch values are not the same after a forward pass."
+    assert set(observation) == set(observation_), (
+        "Observation batch keys are not the same after a forward pass."
+    )
+    assert all(torch.equal(observation[k], observation_[k]) for k in observation), (
+        "Observation batch values are not the same after a forward pass."
+    )
 
     # Test step through policy
     env.step(action)