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Backports for v0.16.2 #3260

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Merged
merged 2 commits into from
Jun 27, 2025
Merged

Backports for v0.16.2 #3260

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b8aa549
Make observed_value_field optional in TFTInstanceSplitter (#3259)
abdulfatir Jun 27, 2025
45b7df3
Cap rpy2 version (#3261)
lostella Jun 27, 2025
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2 changes: 1 addition & 1 deletion requirements/requirements-extras-r.txt
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Original file line number Diff line number Diff line change
@@ -1 +1 @@
rpy2~=3.5
rpy2~=3.5,<3.6
3 changes: 3 additions & 0 deletions requirements/requirements-extras-statsforecast.txt
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@@ -1 +1,4 @@
# scipy cap can be removed once this is resolved: https://github.com/statsmodels/statsmodels/issues/9584
scipy<1.16.0; python_version > "3.7.0"
scipy~=1.7.3; python_version <= "3.7.0"
statsforecast~=1.0
3 changes: 2 additions & 1 deletion requirements/requirements-pytorch.txt
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Expand Up @@ -2,5 +2,6 @@ torch>=1.9,<3
lightning>=2.2.2,<2.5
# Capping `lightning` does not cap `pytorch_lightning`, so we cap manually
pytorch_lightning>=2.2.2,<2.5
scipy~=1.10; python_version > "3.7.0"
# scipy cap can be removed once this is resolved: https://github.com/statsmodels/statsmodels/issues/9584
scipy<1.16.0; python_version > "3.7.0"
scipy~=1.7.3; python_version <= "3.7.0"
10 changes: 4 additions & 6 deletions src/gluonts/transform/split.py
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Expand Up @@ -494,7 +494,7 @@ def __init__(
is_pad_field: str = FieldName.IS_PAD,
start_field: str = FieldName.START,
forecast_start_field: str = FieldName.FORECAST_START,
observed_value_field: str = FieldName.OBSERVED_VALUES,
observed_value_field: Optional[str] = FieldName.OBSERVED_VALUES,
lead_time: int = 0,
output_NTC: bool = True,
time_series_fields: List[str] = [],
Expand Down Expand Up @@ -529,11 +529,9 @@ def flatmap_transform(

sampled_indices = self.instance_sampler(target)

slice_cols = (
self.ts_fields
+ self.past_ts_fields
+ [self.target_field, self.observed_value_field]
)
slice_cols = self.ts_fields + self.past_ts_fields + [self.target_field]
if self.observed_value_field is not None:
slice_cols.append(self.observed_value_field)
for i in sampled_indices:
pad_length = max(self.past_length - i, 0)
d = data.copy()
Expand Down
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