Bases: TomlConfig
Dataclass providing kwargs to FederatedServer and FederatedClient.
Attributes:
| Name |
Type |
Description |
metrics |
MetricSet or None
|
Optional MetricSet instance, defining evaluation metrics to compute
in addition to the model's loss. It may be parsed from a list of
Metric names or (name, config) tuples), or from a MetricSet config
dict. |
checkpoint |
str or None
|
The checkpoint folder path where to save the server's and client-wise
outputs (round-wise model weights, evaluation metrics, logs, etc.). |
Source code in declearn/quickrun/_config.py
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112 | @dataclasses.dataclass
class ExperimentConfig(TomlConfig):
"""Dataclass providing kwargs to `FederatedServer` and `FederatedClient`.
Attributes
----------
metrics: MetricSet or None
Optional MetricSet instance, defining evaluation metrics to compute
in addition to the model's loss. It may be parsed from a list of
Metric names or (name, config) tuples), or from a MetricSet config
dict.
checkpoint: str or None
The checkpoint folder path where to save the server's and client-wise
outputs (round-wise model weights, evaluation metrics, logs, etc.).
"""
metrics: Optional[MetricSet] = None
checkpoint: Optional[str] = None
def parse_metrics(
self,
inputs: Union[MetricSet, Dict[str, Any], List[MetricInputType], None],
) -> Optional[MetricSet]:
"""Parser for metrics."""
if inputs is None or isinstance(inputs, MetricSet):
return None
try:
# Case of a manual listing of metrics (most expected).
if isinstance(inputs, (tuple, list)):
return MetricSet.from_specs(inputs)
# Case of a MetricSet config dict (unexpected but supported).
if isinstance(inputs, dict):
return MetricSet.from_config(inputs)
except (TypeError, ValueError) as exc:
raise TypeError(
f"Failed to parse inputs for field 'metrics': {exc}."
) from exc
raise TypeError(
"Failed to parse inputs for field 'metrics': unproper type."
)
|
parse_metrics(inputs)
Parser for metrics.
Source code in declearn/quickrun/_config.py
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112 | def parse_metrics(
self,
inputs: Union[MetricSet, Dict[str, Any], List[MetricInputType], None],
) -> Optional[MetricSet]:
"""Parser for metrics."""
if inputs is None or isinstance(inputs, MetricSet):
return None
try:
# Case of a manual listing of metrics (most expected).
if isinstance(inputs, (tuple, list)):
return MetricSet.from_specs(inputs)
# Case of a MetricSet config dict (unexpected but supported).
if isinstance(inputs, dict):
return MetricSet.from_config(inputs)
except (TypeError, ValueError) as exc:
raise TypeError(
f"Failed to parse inputs for field 'metrics': {exc}."
) from exc
raise TypeError(
"Failed to parse inputs for field 'metrics': unproper type."
)
|