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Oleksandr Shchur 2026-01-19 08:51:12 +00:00
parent 76463ed744
commit 1f405f5a2d
3 changed files with 11 additions and 7 deletions
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7
src/chronos/base.py
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@ -165,10 +165,11 @@ class BaseChronosPipeline(metaclass=PipelineRegistry):
quantile_levels
Quantile levels to compute
validate_inputs
When True, the dataframe(s) will be validated before prediction, ensuring that timestamps have a
regular frequency, and item IDs match between past and future data. Setting to False disables these checks.
[ADVANCED] When False, skips validation. You must ensure: (1) df and future_df (if provided)
are sorted by (id_column, timestamp_column); (2) future_df (if provided) contains exactly
prediction_length rows per item. Defaults to True.
freq
Frequency string for timestamp generation (e.g., "h", "D", "W"). Can only be used when
Frequency string for timestamp generation (e.g., "H", "D", "W"). Can only be used when
validate_inputs=False. When provided, skips frequency inference from the data.
**predict_kwargs
Additional arguments passed to predict_quantiles

5
src/chronos/chronos2/pipeline.py
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@ -865,8 +865,9 @@ class Chronos2Pipeline(BaseChronosPipeline):
For optimal results, consider using a batch size around 100 (as used in the Chronos-2 technical report).
- Cross-learning is most helpful when individual time series have limited historical context, as the model can leverage patterns from related series in the batch.
validate_inputs
When True, the dataframe(s) will be validated before prediction, ensuring that timestamps have a
regular frequency, and item IDs match between past and future data. Setting to False disables these checks.
[ADVANCED] When False, skips validation. You must ensure: (1) df and future_df (if provided)
are sorted by (id_column, timestamp_column); (2) future_df (if provided) contains exactly
prediction_length rows per item. Defaults to True.
freq
Frequency string for timestamp generation (e.g., "h", "D", "W"). Can only be used when
validate_inputs=False. When provided, skips frequency inference from the data.

6
src/chronos/df_utils.py
View file

@ -231,10 +231,12 @@ def convert_df_input_to_list_of_dicts_input(
timestamp_column
Name of column containing timestamps
freq
Frequency string for timestamp generation (e.g., "h", "D", "W"). Can only be used
Frequency string for timestamp generation (e.g., "H", "D", "W"). Can only be used
when validate_inputs=False. When provided, skips frequency inference from the data.
validate_inputs
When True, the dataframe(s) will be validated before conversion
[ADVANCED] When False, skips validation. You must ensure: (1) df and future_df (if provided)
are sorted by (id_column, timestamp_column); (2) future_df (if provided) contains exactly
prediction_length rows per item. Defaults to True.
Returns
-------