code: def mean_squared_log_error(
      y_true: ArrayLike,
      y_pred: ArrayLike,
      sample_weight: Optional[ArrayLike] = None,
      multioutput: Optional[str] = "uniform_average",
      compute: bool = True,
  ) -> ArrayLike:
      result = mean_squared_error(
          np.log1p(y_true),
          np.log1p(y_pred),
          sample_weight=sample_weight,
          multioutput=multioutput,
          compute=compute,
      )
      return result
  
file_path: dask-ml/dask_ml/metrics/regression.py
imports: from typing import Optional
  import dask.array
  import numpy
  import sklearn.metrics
  from dask import is_dask_collection
  from dask.utils import derived_from
  from .._typing import ArrayLike
label_desc: Use image node_id 7 for calling a global function with example usage: mean_squared_log_error(y_true, y_pred, sample_weight, multioutput, compute) and returns: result