Help protect the Great Barrier Reef with TensorFlow on Kaggle Join Challenge

tfma.writers.MetricsPlotsAndValidationsWriter

Returns metrics and plots writer.

tfma.writers.MetricsPlotsAndValidationsWriter(
    output_paths: Dict[str, str],
    eval_config: tfma.EvalConfig,
    add_metrics_callbacks: Optional[List[types.AddMetricsCallbackType]] = None,
    metrics_key: str = constants.METRICS_KEY,
    plots_key: str = constants.PLOTS_KEY,
    attributions_key: str = constants.ATTRIBUTIONS_KEY,
    validations_key: str = constants.VALIDATIONS_KEY,
    output_file_format: str = '',
    rubber_stamp: Optional[bool] = False
) -> tfma.writers.Writer

Note, sharding will be enabled by default if a output_file_format is provided. The files will be named -SSSSS-of-NNNNN. where SSSSS is the shard number and NNNNN is the number of shards.

output_paths Output paths keyed by output key (e.g. 'metrics', 'plots', 'validation').
eval_config Eval config.
add_metrics_callbacks Optional list of metric callbacks (if used).
metrics_key Name to use for metrics key in Evaluation output.
plots_key Name to use for plots key in Evaluation output.
attributions_key Name to use for attributions key in Evaluation output.
validations_key Name to use for validations key in Evaluation output.
output_file_format File format to use when saving files. Currently 'tfrecord' and 'parquet' are supported. If using parquet, the output metrics and plots files will contain two columns: 'slice_key' and 'serialized_value'. The 'slice_key' column will be a structured column matching the metrics_for_slice_pb2.SliceKey proto. the 'serialized_value' column will contain a serialized MetricsForSlice or PlotsForSlice proto. The validation result file will contain a single column 'serialized_value' which will contain a single serialized ValidationResult proto.
rubber_stamp True if this model is being rubber stamped. When a model is rubber stamped diff thresholds will be ignored if an associated baseline model is not passed.