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Fix test comparing uninitialized array segment

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The test was inadvertently comparing uninitialized parts of the array,
which could lead to inconsistent or undefined results. This fix ensures
only the relevant, properly initialized sections are checked.

Co-authored-by: Eugene Mironov <helper2424@gmail.com>
This commit is contained in:
AdilZouitine
2025-04-22 15:13:10 +02:00
parent 4ce3362724
commit 5231752487
1 changed files with 15 additions and 14 deletions
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29
tests/server/test_replay_buffer.py
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@@ -401,26 +401,27 @@ def test_from_lerobot_dataset(tmp_path):
ds, state_keys=list(state_dims()), device="cpu", capacity=replay_buffer.capacity, use_drq=False
)
assert len(reconverted_buffer) == 4, "Reconverted Replay buffer should have the same size as original"
assert torch.equal(reconverted_buffer.actions, replay_buffer.actions), (
"Actions from converted buffer should be equal to the original replay buffer."
)
assert torch.equal(reconverted_buffer.rewards, replay_buffer.rewards), (
"Rewards from converted buffer should be equal to the original replay buffer."
)
assert torch.equal(reconverted_buffer.dones, replay_buffer.dones), (
"Dones from converted buffer should be equal to the original replay buffer."
)
# Check only the part of the buffer that's actually filled with data
assert torch.equal(
reconverted_buffer.actions[: len(replay_buffer)],
replay_buffer.actions[: len(replay_buffer)],
), "Actions from converted buffer should be equal to the original replay buffer."
assert torch.equal(
reconverted_buffer.rewards[: len(replay_buffer)], replay_buffer.rewards[: len(replay_buffer)]
), "Rewards from converted buffer should be equal to the original replay buffer."
assert torch.equal(
reconverted_buffer.dones[: len(replay_buffer)], replay_buffer.dones[: len(replay_buffer)]
), "Dones from converted buffer should be equal to the original replay buffer."
# Lerobot DS haven't supported truncateds yet
expected_truncateds = torch.zeros(replay_buffer.truncateds.shape[0]).bool()
assert torch.equal(reconverted_buffer.truncateds, expected_truncateds), (
expected_truncateds = torch.zeros(len(replay_buffer)).bool()
assert torch.equal(reconverted_buffer.truncateds[: len(replay_buffer)], expected_truncateds), (
"Truncateds from converted buffer should be equal False"
)
assert torch.equal(
replay_buffer.states["observation.state"], reconverted_buffer.states["observation.state"]
replay_buffer.states["observation.state"][: len(replay_buffer)],
reconverted_buffer.states["observation.state"][: len(replay_buffer)],
), "State should be the same after converting to dataset and return back"
for i in range(4):