Add data aggregations to data preparation #49
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Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
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Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
…ggregations Signed-off-by: Frankie Siino <fsiino@nvidia.com>
…odel Signed-off-by: Frankie Siino <fsiino@nvidia.com>
bxyu-nvidia
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Sep 18, 2025
nemo_gym/train_data_utils.py
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| self, dataset_config: DatasetConfig | ||
| ) -> DatasetValidatorState: | ||
| state = DatasetValidatorState() | ||
| data = [] |
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having data be a list here is going to increase memory consumption like crazy. let's fold the aggregate_other_metrics call into _validate_samples_and_aggregate_metrics_single_sample
nemo_gym/dataset_viewer.py
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| def get_aggregate_metrics(data: List[DatasetViewerVerifyResponse], raw_lines: List[str]) -> Dict[str, Any]: | ||
| def get_aggregate_metrics(raw_lines: List[str]) -> Dict[str, Any]: | ||
| dataset_metrics = DatasetMetrics() | ||
| line_dicts = [] |
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same comment as below. ideally we would try to save on the memory here
Signed-off-by: Frankie Siino <fsiino@nvidia.com>
bxyu-nvidia
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Sep 18, 2025
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This change updates the train_data_utils via `ng_prepare_data` to apply data aggregations to the other keys within an `example.jsonl`. file. --------- Signed-off-by: Frankie Siino <fsiino@nvidia.com> Co-authored-by: bxyu-nvidia <bxyu@nvidia.com>
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This change updates the train_data_utils via `ng_prepare_data` to apply data aggregations to the other keys within an `example.jsonl`. file. --------- Signed-off-by: Frankie Siino <fsiino@nvidia.com> Co-authored-by: bxyu-nvidia <bxyu@nvidia.com>
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This change updates the train_data_utils via
ng_prepare_datato apply data aggregations to the other keys within anexample.jsonl. file.