[BUG] Cannot create prioritized replay buffer using old storage #3120
Description
Describe the bug
TensorDictReplayBuffer(storage=loaded_replay_buffer.storage, ...) where loaded_replay_buffer has been loaded from disk, does not work.
To Reproduce
from pathlib import Path
from tensordict import TensorDict
import torch
from torchrl.data import (
TensorDictReplayBuffer,
LazyTensorStorage,
PrioritizedSampler,
)
device = torch.device("cpu") # or "cuda", does not matter
def create_replay_buffer():
return TensorDictReplayBuffer(
storage=LazyTensorStorage(max_size=10, device=device),
# storage=LazyMemmapStorage(
# max_size=10, scratch_dir=Path("rb_scratch_dir"), device=torch.device("cpu")
# ),
sampler=PrioritizedSampler(max_capacity=10, alpha=0.7, beta=0.5),
batch_size=2,
priority_key="td_error",
)
# Create a replay buffer and add some data, WORKS
replay_buffer = create_replay_buffer()
_ = replay_buffer.extend(
TensorDict(
{"state": torch.ones(4, 2, dtype=torch.float32, device=device)},
batch_size=torch.Size((4,)),
)
)
td = replay_buffer.sample()
td["td_error"] = torch.arange(2, device=device)
replay_buffer.update_tensordict_priority(td)
replay_buffer.dumps(Path("tmp"))
del replay_buffer
# Load the replay buffer directly, WORKS
loaded_replay_buffer = create_replay_buffer()
loaded_replay_buffer.loads(Path("tmp"))
td = loaded_replay_buffer.sample()
# Only load storage, DOES NOT WORK
new_replay_buffer = TensorDictReplayBuffer(
storage=loaded_replay_buffer.storage,
sampler=PrioritizedSampler(
max_capacity=len(loaded_replay_buffer), alpha=0.7, beta=0.5
),
batch_size=2,
priority_key="td_error",
)
td = new_replay_buffer.sample()Traceback (most recent call last):
File "/home/valter/Documents/Projects/torchrl-issues/scripts/replay_buffer.py", line 56, in <module>
td = new_replay_buffer.sample()
File "/home/valter/Documents/Projects/torchrl-issues/.venv/lib/python3.13/site-packages/torchrl/data/replay_buffers/replay_buffers.py", line 1502, in sample
data, info = super().sample(batch_size, return_info=True)
~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/valter/Documents/Projects/torchrl-issues/.venv/lib/python3.13/site-packages/torchrl/data/replay_buffers/replay_buffers.py", line 859, in sample
result = self._sample(batch_size)
File "/home/valter/Documents/Projects/torchrl-issues/.venv/lib/python3.13/site-packages/torchrl/data/replay_buffers/utils.py", line 71, in decorated_fun
output = fun(self, *args, **kwargs)
File "/home/valter/Documents/Projects/torchrl-issues/.venv/lib/python3.13/site-packages/torchrl/data/replay_buffers/replay_buffers.py", line 1535, in _sample
index, info = self._sampler.sample(self._storage, batch_size)
~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/home/valter/Documents/Projects/torchrl-issues/.venv/lib/python3.13/site-packages/torchrl/data/replay_buffers/samplers.py", line 530, in sample
raise RuntimeError("non-positive p_sum")
RuntimeError: non-positive p_sumExpected behavior
No crash.
System info
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