Fixes for PR #4

lerobot/common/datasets/factory.py

@@ -73,7 +73,6 @@ def make_offline_buffer(cfg, sampler=None):
     elif cfg.env.name == "pusht":
         offline_buffer = PushtExperienceReplay(
             "pusht",
-            download=True,
             streaming=False,
             root=DATA_PATH,
             sampler=sampler,

lerobot/common/datasets/pusht.py

@@ -18,7 +18,7 @@ from torchrl.data.replay_buffers.writers import ImmutableDatasetWriter, Writer
 
 from diffusion_policy.common.replay_buffer import ReplayBuffer
 from diffusion_policy.env.pusht.pusht_env import pymunk_to_shapely
-from lerobot.common import utils
+from lerobot.common.datasets import utils
 
 # as define in env
 SUCCESS_THRESHOLD = 0.95  # 95% coverage,
@@ -97,17 +97,15 @@ class PushtExperienceReplay(TensorDictReplayBuffer):
         replacement: bool = None,
         streaming: bool = False,
         root: Path = None,
-        download: bool | str = False,
         sampler: Sampler = None,
         writer: Writer = None,
         collate_fn: Callable = None,
         pin_memory: bool = False,
         prefetch: int = None,
-        transform: "torchrl.envs.Transform" = None,  # noqa-F821
+        transform: "torchrl.envs.Transform" = None,  # noqa: F821
         split_trajs: bool = False,
         strict_length: bool = True,
     ):
-        self.download = download
         if streaming:
             raise NotImplementedError
         self.streaming = streaming
@@ -129,8 +127,7 @@ class PushtExperienceReplay(TensorDictReplayBuffer):
             os.makedirs(root, exist_ok=True)
 
         self.root = root
-        self.raw = self.root / "raw"
+        if not self._is_downloaded():
-        if self.download == "force" or (self.download and not self._is_downloaded()):
             storage = self._download_and_preproc()
         else:
             storage = TensorStorage(TensorDict.load_memmap(self.root / dataset_id))
@@ -192,9 +189,11 @@ class PushtExperienceReplay(TensorDictReplayBuffer):
 
     def _download_and_preproc(self):
         # download
-        self.raw.mkdir(exist_ok=True)
+        raw_dir = self.root / "raw"
-        utils.download_and_extract_zip(PUSHT_URL, self.raw)
+        zarr_path = (raw_dir / PUSHT_ZARR).resolve()
-        zarr_path = (self.raw / PUSHT_ZARR).resolve()
+        if not zarr_path.is_dir():
+            raw_dir.mkdir(parents=True, exist_ok=True)
+            utils.download_and_extract_zip(PUSHT_URL, raw_dir)
 
         # load
         dataset_dict = ReplayBuffer.copy_from_path(zarr_path)  # , keys=['img', 'state', 'action'])

lerobot/common/datasets/utils.py

@@ -0,0 +1,30 @@
+import io
+import zipfile
+from pathlib import Path
+
+import requests
+import tqdm
+
+
+def download_and_extract_zip(url: str, destination_folder: Path) -> bool:
+    print(f"downloading from {url}")
+    response = requests.get(url, stream=True)
+    if response.status_code == 200:
+        total_size = int(response.headers.get("content-length", 0))
+        progress_bar = tqdm.tqdm(total=total_size, unit="B", unit_scale=True)
+
+        zip_file = io.BytesIO()
+        for chunk in response.iter_content(chunk_size=1024):
+            if chunk:
+                zip_file.write(chunk)
+                progress_bar.update(len(chunk))
+
+        progress_bar.close()
+
+        zip_file.seek(0)
+
+        with zipfile.ZipFile(zip_file, "r") as zip_ref:
+            zip_ref.extractall(destination_folder)
+        return True
+    else:
+        return False

lerobot/common/utils.py

@@ -1,38 +1,9 @@
-import io
 import logging
 import random
-import zipfile
 from datetime import datetime
-from pathlib import Path
 
 import numpy as np
-import requests
 import torch
-import tqdm
-
-
-def download_and_extract_zip(url: str, destination_folder: Path) -> bool:
-    print(f"downloading from {url}")
-    response = requests.get(url, stream=True)
-    if response.status_code == 200:
-        total_size = int(response.headers.get("content-length", 0))
-        progress_bar = tqdm.tqdm(total=total_size, unit="B", unit_scale=True)
-
-        zip_file = io.BytesIO()
-        for chunk in response.iter_content(chunk_size=1024):
-            if chunk:
-                zip_file.write(chunk)
-                progress_bar.update(len(chunk))
-
-        progress_bar.close()
-
-        zip_file.seek(0)
-
-        with zipfile.ZipFile(zip_file, "r") as zip_ref:
-            zip_ref.extractall(destination_folder)
-        return True
-    else:
-        return False
 
 
 def set_seed(seed):