[HIL-SERL] Migrate threading to multiprocessing (#759)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

lerobot/scripts/server/buffer.py

@@ -23,6 +23,7 @@ from tqdm import tqdm
 
 from lerobot.common.datasets.lerobot_dataset import LeRobotDataset
 import os
+import pickle
 
 
 class Transition(TypedDict):
@@ -91,7 +92,7 @@ def move_transition_to_device(
     return transition
 
 
-def move_state_dict_to_device(state_dict, device):
+def move_state_dict_to_device(state_dict, device="cpu"):
     """
     Recursively move all tensors in a (potentially) nested
     dict/list/tuple structure to the CPU.
@@ -111,20 +112,41 @@ def move_state_dict_to_device(state_dict, device):
         return state_dict
 
 
-def state_to_bytes(state_dict: dict[str, torch.Tensor]) -> io.BytesIO:
+def state_to_bytes(state_dict: dict[str, torch.Tensor]) -> bytes:
     """Convert model state dict to flat array for transmission"""
     buffer = io.BytesIO()
 
     torch.save(state_dict, buffer)
 
-    return buffer
+    return buffer.getvalue()
 
 
-def bytes_buffer_size(buffer: io.BytesIO) -> int:
-    buffer.seek(0, io.SEEK_END)
-    result = buffer.tell()
+def bytes_to_state_dict(buffer: bytes) -> dict[str, torch.Tensor]:
+    buffer = io.BytesIO(buffer)
     buffer.seek(0)
-    return result
+    return torch.load(buffer)
+
+
+def python_object_to_bytes(python_object: Any) -> bytes:
+    return pickle.dumps(python_object)
+
+
+def bytes_to_python_object(buffer: bytes) -> Any:
+    buffer = io.BytesIO(buffer)
+    buffer.seek(0)
+    return pickle.load(buffer)
+
+
+def bytes_to_transitions(buffer: bytes) -> list[Transition]:
+    buffer = io.BytesIO(buffer)
+    buffer.seek(0)
+    return torch.load(buffer)
+
+
+def transitions_to_bytes(transitions: list[Transition]) -> bytes:
+    buffer = io.BytesIO()
+    torch.save(transitions, buffer)
+    return buffer.getvalue()
 
 
 def random_crop_vectorized(images: torch.Tensor, output_size: tuple) -> torch.Tensor: