results

results

Result compilation for Safe Synthesizer pipeline runs.

Assembles generation output, evaluation scores, and timing into the SafeSynthesizerResults and SafeSynthesizerSummary containers consumed by the SDK and CLI.

Functions:

Name	Description
make_nss_summary	Build a pipeline summary from timing, generation results, and evaluation.
make_nss_results	Build the final pipeline results container.

make_nss_summary(timing, results=None, report=None)

Build a pipeline summary from timing, generation results, and evaluation.

Extracts evaluation scores from report when available. If report is None (e.g. PII-only mode), all scores default to None.

Parameters:

Name	Type	Description	Default
timing	SafeSynthesizerTiming	Wall-clock timing breakdown for the pipeline.	required
results	GenerateJobResults | DataFrame | None	Generation output -- a GenerateJobResults with record counts, or a raw DataFrame, or None.	None
report	MultimodalReport | None	Evaluation report containing component scores.	None

Returns:

Type	Description
SafeSynthesizerSummary	A populated SafeSynthesizerSummary.

Source code in src/nemo_safe_synthesizer/results.py

def make_nss_summary(
    timing: SafeSynthesizerTiming,
    results: GenerateJobResults | pd.DataFrame | None = None,
    report: MultimodalReport | None = None,
) -> SafeSynthesizerSummary:
    """Build a pipeline summary from timing, generation results, and evaluation.

    Extracts evaluation scores from ``report`` when available. If ``report``
    is ``None`` (e.g. PII-only mode), all scores default to ``None``.

    Args:
        timing: Wall-clock timing breakdown for the pipeline.
        results: Generation output -- a ``GenerateJobResults`` with record
            counts, or a raw ``DataFrame``, or ``None``.
        report: Evaluation report containing component scores.

    Returns:
        A populated ``SafeSynthesizerSummary``.
    """
    # Extract scores from report if available, otherwise use None for all scores
    # (e.g., when running PII-only mode without evaluation)
    if report is not None:
        synthetic_data_quality_score = report.get_score_by_name("Synthetic Quality Score")
        column_correlation_stability_score = report.get_score_by_name("Column Correlation Stability")
        deep_structure_stability_score = report.get_score_by_name("Deep Structure Stability")
        column_distribution_stability_score = report.get_score_by_name("Column Distribution Stability")
        text_semantic_similarity_score = report.get_score_by_name("Text Semantic Similarity")
        text_structure_similarity_score = report.get_score_by_name("Text Structure Similarity")
        data_privacy_score = report.get_score_by_name("Data Privacy Score")
        membership_inference_protection_score = report.get_score_by_name("Membership Inference Protection")
        attribute_inference_protection_score = report.get_score_by_name("Attribute Inference Protection")
    else:
        synthetic_data_quality_score = None
        column_correlation_stability_score = None
        deep_structure_stability_score = None
        column_distribution_stability_score = None
        text_semantic_similarity_score = None
        text_structure_similarity_score = None
        data_privacy_score = None
        membership_inference_protection_score = None
        attribute_inference_protection_score = None

    num_valid_records = None
    num_invalid_records = None
    num_prompts = None
    valid_record_fraction = None
    if isinstance(results, GenerateJobResults):
        num_valid_records = results.num_valid_records
        num_invalid_records = results.num_invalid_records
        num_prompts = results.num_prompts
        valid_record_fraction = results.valid_record_fraction

    return SafeSynthesizerSummary(
        timing=timing,
        num_valid_records=num_valid_records,
        num_invalid_records=num_invalid_records,
        num_prompts=num_prompts,
        valid_record_fraction=valid_record_fraction,
        synthetic_data_quality_score=synthetic_data_quality_score,
        column_correlation_stability_score=column_correlation_stability_score,
        deep_structure_stability_score=deep_structure_stability_score,
        column_distribution_stability_score=column_distribution_stability_score,
        text_semantic_similarity_score=text_semantic_similarity_score,
        text_structure_similarity_score=text_structure_similarity_score,
        data_privacy_score=data_privacy_score,
        membership_inference_protection_score=membership_inference_protection_score,
        attribute_inference_protection_score=attribute_inference_protection_score,
    )

make_nss_results(generate_results, total_time=None, training_time=None, generation_time=None, evaluation_time=None, report=None)

Build the final pipeline results container.

Combines generation output, timing, and an optional evaluation report into a single SafeSynthesizerResults object.

Parameters:

Name	Type	Description	Default
generate_results	GenerateJobResults | DataFrame	Generation output -- a GenerateJobResults or a raw DataFrame of synthetic records.	required
total_time	float | None	Total wall-clock time in seconds.	None
training_time	float | None	Training phase time in seconds.	None
generation_time	float | None	Generation phase time in seconds.	None
evaluation_time	float | None	Evaluation phase time in seconds.	None
report	MultimodalReport | None	Evaluation report to render as HTML.	None

Returns:

Type	Description
SafeSynthesizerResults	A SafeSynthesizerResults with synthetic data, summary, and
SafeSynthesizerResults	optional HTML evaluation report.

Raises:

Type	Description
ValueError	If generate_results is None or an empty DataFrame.

Source code in src/nemo_safe_synthesizer/results.py

def make_nss_results(
    generate_results: GenerateJobResults | pd.DataFrame,
    total_time: float | None = None,
    training_time: float | None = None,
    generation_time: float | None = None,
    evaluation_time: float | None = None,
    report: MultimodalReport | None = None,
) -> SafeSynthesizerResults:
    """Build the final pipeline results container.

    Combines generation output, timing, and an optional evaluation report
    into a single ``SafeSynthesizerResults`` object.

    Args:
        generate_results: Generation output -- a ``GenerateJobResults`` or
            a raw ``DataFrame`` of synthetic records.
        total_time: Total wall-clock time in seconds.
        training_time: Training phase time in seconds.
        generation_time: Generation phase time in seconds.
        evaluation_time: Evaluation phase time in seconds.
        report: Evaluation report to render as HTML.

    Returns:
        A ``SafeSynthesizerResults`` with synthetic data, summary, and
        optional HTML evaluation report.

    Raises:
        ValueError: If ``generate_results`` is ``None`` or an empty
            ``DataFrame``.
    """
    timing = SafeSynthesizerTiming(
        total_time_sec=total_time,
        evaluation_time_sec=evaluation_time,
        training_time_sec=training_time,
        generation_time_sec=generation_time,
    )
    summary = make_nss_summary(timing, generate_results, report)
    if generate_results is None:
        raise ValueError("generate_results is required")
    if isinstance(generate_results, pd.DataFrame) and generate_results.empty:
        raise ValueError("generate_results are empty")
    return SafeSynthesizerResults(
        synthetic_data=generate_results.df if isinstance(generate_results, GenerateJobResults) else generate_results,
        summary=summary,
        evaluation_report_html=render_report(report) if report else None,
    )