metric
Metrics to use for training or explanations.
Metric
#
Represents a metric for the explainable model.
TorchMetric
#
Represent a metric to be used in the training or evaluation process for the whole model (global metric).
Parameters:
Name | Type | Description | Default |
---|---|---|---|
metric |
The torchmetrics metric to use, as partial. |
required | |
display_metric_type |
If set, overrides the default metric name in XpViz. |
required | |
on_raw_data |
If set, value are compute from raw data and not preprocessed data (inputs or targets). |
required |
TorchLeafMetric
#
Represent a metric to be used during the training or the evaluation process, per leaf.
Parameters:
Name | Type | Description | Default |
---|---|---|---|
metric |
The torchmetrics metric to use, as partial. |
required | |
display_metric_type |
If set, overrides the default metric name in XpViz. |
required | |
on_raw_data |
If set, value are compute from raw data and not preprocessed data (inputs or targets). |
required |
DictMetrics
#
Dictionary of metrics (torch eval etc...) used in training or explain stage.
Each metric will be computed globally (for the whole model) and per leaf. In the training stage, help to monitor the training. In the explain stage, allow to visualize metrics in xpdeep-viz along with explanations.