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Updated to better support nested mappings and dataclasses in log_hyperparameters() #3

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Jul 25, 2025
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Updated to better support nested mappings and dataclasses in log_hyperparameters() #3

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23 changes: 2 additions & 21 deletions src/lightning/pytorch/loggers/neptune.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,7 +42,7 @@

log = logging.getLogger(__name__)

_NEPTUNE_SCALE_AVAILABLE = RequirementCache("neptune-scale")
_NEPTUNE_SCALE_AVAILABLE = RequirementCache("neptune-scale>=0.18.0")
_NEPTUNE_AVAILABLE = RequirementCache("neptune>=1.0")

if TYPE_CHECKING:
Expand Down Expand Up @@ -963,33 +963,14 @@ def log_hyperparams(self, params: Union[dict[str, Any], Namespace]) -> None:
neptune_scale_logger.log_hyperparams(PARAMS)

"""
from datetime import datetime

params = _convert_params(params)
params = _sanitize_callable_params(params)

parameters_key = self.PARAMETERS_KEY
parameters_key = self._construct_path_with_prefix(parameters_key)

allowed_datatypes = [int, float, str, datetime, bool, list, set]

def flatten(d: dict, prefix: str = "") -> dict[str, Any]:
"""Flatten a nested dictionary by concatenating keys with '/'."""
flattened = {}
for key, value in d.items():
new_key = f"{prefix}/{key}" if prefix else key
if isinstance(value, dict):
flattened.update(flatten(value, new_key))
elif type(value) in allowed_datatypes:
flattened[new_key] = value
else:
flattened[new_key] = str(value)
return flattened

flattened = flatten(params)

batched_configs = {f"{parameters_key}/{key}": value for key, value in flattened.items()}
self.run.log_configs(batched_configs)
self.run.log_configs({parameters_key: params}, flatten=True, cast_unsupported=True)

@override
@rank_zero_only
Expand Down
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