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Runtime crash in Samformer initialization when metadata is None #2402

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9 changes: 9 additions & 0 deletions pytorch_forecasting/models/samformer/_samformer_v2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -30,6 +30,12 @@ class Samformer(BaseModel):
Whether to use Reverse Instance Normalization. Default is True.
persistence_weight : float, optional
Weight for persistence baseline. Default is 0.0.
metadata : dict
Dataset metadata produced by
:class:`~pytorch_forecasting.data.data_module\
.EncoderDecoderTimeSeriesDataModule`.
Must contain ``"max_encoder_length"``, ``"max_prediction_length"``,
and ``"encoder_cont"``.
"""

@classmethod
Expand Down Expand Up @@ -58,6 +64,9 @@ def __init__(
metadata: dict | None = None,
**kwargs,
):
if metadata is None:
raise ValueError("metadata is required")

super().__init__(
loss=loss,
logging_metrics=logging_metrics,
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10 changes: 10 additions & 0 deletions tests/test_models/test_samformer_v2.py
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@@ -0,0 +1,10 @@
import pytest
import torch.nn as nn

from pytorch_forecasting.models.samformer._samformer_v2 import Samformer


def test_samformer_requires_metadata():
"""Test that Samformer rejects missing metadata explicitly."""
with pytest.raises(ValueError, match="metadata is required"):
Samformer(loss=nn.MSELoss(), hidden_size=512, use_revin=True, metadata=None)
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