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lerobot/common/datasets/v21/convert_dataset_v20_to_v21.py

@@ -38,7 +38,10 @@ from huggingface_hub import HfApi
 
 from lerobot.common.datasets.lerobot_dataset import CODEBASE_VERSION, LeRobotDataset
 from lerobot.common.datasets.utils import EPISODES_STATS_PATH, STATS_PATH, load_stats, write_info
-from lerobot.common.datasets.v21.convert_stats import check_aggregate_stats, convert_stats, convert_stats_parallel
+from lerobot.common.datasets.v21.convert_stats import (
+    check_aggregate_stats,
+    convert_stats_parallel,
+)
 
 V20 = "v2.0"
 V21 = "v2.1"

lerobot/common/datasets/v21/convert_stats.py

@@ -13,11 +13,10 @@
 # limitations under the License.
 
 from concurrent.futures import ThreadPoolExecutor, as_completed
+from multiprocessing import cpu_count
 
 import numpy as np
 from tqdm import tqdm
-from multiprocessing import cpu_count
-from concurrent.futures import ProcessPoolExecutor, as_completed
 
 from lerobot.common.datasets.compute_stats import aggregate_stats, get_feature_stats, sample_indices
 from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
@@ -56,7 +55,7 @@ def convert_episode_stats(dataset: LeRobotDataset, ep_idx: int, is_parallel: boo
 
     if not is_parallel:
         dataset.meta.episodes_stats[ep_idx] = ep_stats
-    
+
     return ep_stats, ep_idx
 
 
@@ -86,14 +85,12 @@ def convert_stats_parallel(dataset: LeRobotDataset, num_workers: int = 0):
     print("Computing episodes stats")
     total_episodes = dataset.meta.total_episodes
     futures = []
-    
+
     max_workers = min(cpu_count(), num_workers)
     if num_workers > 0:
         with ThreadPoolExecutor(max_workers=max_workers) as executor:
             for ep_idx in range(total_episodes):
-                futures.append(
-                    executor.submit(convert_episode_stats, dataset, ep_idx, True)
-                )
+                futures.append(executor.submit(convert_episode_stats, dataset, ep_idx, True))
             for future in tqdm(as_completed(futures), total=total_episodes, desc="Converting episodes stats"):
                 ep_stats, ep_data = future.result()
                 dataset.meta.episodes_stats[ep_idx] = ep_data
@@ -103,7 +100,7 @@ def convert_stats_parallel(dataset: LeRobotDataset, num_workers: int = 0):
 
     for ep_idx in tqdm(range(total_episodes)):
         write_episode_stats(ep_idx, dataset.meta.episodes_stats[ep_idx], dataset.root)
-        
+
 
 def check_aggregate_stats(
     dataset: LeRobotDataset,

lerobot/common/datasets/video_utils.py

@@ -257,11 +257,11 @@ def decode_video_frames_decord(
     frame_ts: np.ndarray = vr.get_frame_timestamp(range(num_frames))
     indices = np.abs(frame_ts[:, :1] - timestamps).argmin(axis=0)
     frames = vr.get_batch(indices)
-    
+
     frames_tensor = torch.tensor(frames.asnumpy()).type(torch.float32).permute(0, 3, 1, 2) / 255
     return frames_tensor
 
-    
+
 def encode_video_frames(
     imgs_dir: Path | str,
     video_path: Path | str,