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https://github.com/huggingface/lerobot.git
synced 2026-05-15 08:39:49 +00:00
fix(tests): ensure tensor stats comparison accounts for reshaping in normalization tests
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@@ -1804,13 +1804,15 @@ def test_stats_override_preservation_in_load_state_dict():
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override_normalizer.stats[key][stat_name], original_stats[key][stat_name]
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), f"Stats for {key}.{stat_name} should not match original stats"
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# Verify that _tensor_stats are also correctly set to match the override stats
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# Verify that _tensor_stats values match the override stats
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# Note: visual stats are reshaped from (C,) to (C,1,1) by _reshape_visual_stats
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expected_tensor_stats = to_tensor(override_stats)
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for key in expected_tensor_stats:
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for stat_name in expected_tensor_stats[key]:
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if isinstance(expected_tensor_stats[key][stat_name], torch.Tensor):
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torch.testing.assert_close(
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override_normalizer._tensor_stats[key][stat_name], expected_tensor_stats[key][stat_name]
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override_normalizer._tensor_stats[key][stat_name].squeeze(),
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expected_tensor_stats[key][stat_name].squeeze(),
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)
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@@ -1849,12 +1851,16 @@ def test_stats_without_override_loads_normally():
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# Stats should now match the original stats (normal behavior)
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# Check that all keys and values match
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assert set(new_normalizer.stats.keys()) == set(original_stats.keys())
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# Note: visual stats are reshaped from (C,) to (C,1,1) by _reshape_visual_stats,
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# so we squeeze before comparing values.
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for key in original_stats:
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assert set(new_normalizer.stats[key].keys()) == set(original_stats[key].keys())
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for stat_name in original_stats[key]:
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np.testing.assert_allclose(
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new_normalizer.stats[key][stat_name], original_stats[key][stat_name], rtol=1e-6, atol=1e-6
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)
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actual = new_normalizer.stats[key][stat_name]
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expected = original_stats[key][stat_name]
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if hasattr(actual, "squeeze"):
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actual = actual.squeeze()
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np.testing.assert_allclose(actual, expected, rtol=1e-6, atol=1e-6)
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def test_stats_explicit_provided_flag_detection():
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@@ -2075,8 +2081,9 @@ def test_stats_reconstruction_after_load_state_dict():
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assert ACTION in new_normalizer.stats
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# Check that values are correct (converted back from tensors)
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np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["mean"], [0.5, 0.5, 0.5])
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np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["std"], [0.2, 0.2, 0.2])
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# Note: visual stats are reshaped to (C,1,1), so we squeeze before comparing
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np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["mean"].squeeze(), [0.5, 0.5, 0.5])
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np.testing.assert_allclose(new_normalizer.stats[OBS_IMAGE]["std"].squeeze(), [0.2, 0.2, 0.2])
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np.testing.assert_allclose(new_normalizer.stats[OBS_STATE]["min"], [0.0, -1.0])
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np.testing.assert_allclose(new_normalizer.stats[OBS_STATE]["max"], [1.0, 1.0])
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np.testing.assert_allclose(new_normalizer.stats[ACTION]["mean"], [0.0, 0.0])
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