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feat[logger] update mlflow limit for parameters length log #20636

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feat[logger] update mlflow limit for parameters length log #20636

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feat[logger] update mlflow limit for parameters length log using mlfl…
bastienjalbert Mar 11, 2025
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[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 11, 2025
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12 changes: 9 additions & 3 deletions src/lightning/pytorch/loggers/mlflow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -234,11 +234,17 @@ def log_hyperparams(self, params: Union[dict[str, Any], Namespace]) -> None:
params = _convert_params(params)
params = _flatten_dict(params)

import mlflow.utils.validation
from mlflow.entities import Param

# Truncate parameter values to 250 characters.
# TODO: MLflow 1.28 allows up to 500 characters: https://github.com/mlflow/mlflow/releases/tag/v1.28.0
params_list = [Param(key=k, value=str(v)[:250]) for k, v in params.items()]
# Check maximum param value length is available and use it
if hasattr(mlflow.utils.validation, "MAX_PARAM_VAL_LENGTH"):
param_length_limit = mlflow.utils.validation.MAX_PARAM_VAL_LENGTH
else: # Fallback
param_length_limit = 250 # Historical default value

# Use mlflow default limit or truncate parameter values to 250 characters if limit is not available
params_list = [Param(key=k, value=str(v)[:param_length_limit]) for k, v in params.items()]

# Log in chunks of 100 parameters (the maximum allowed by MLflow).
for idx in range(0, len(params_list), 100):
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