code: def __init__(self, globals_dict: dict) -> None:
      super().__init__(
          id="rmse",
          name="RMSE",
          score_func=metrics.mean_squared_error,
          greater_is_better=False,
          args={"squared": False},
          scorer="neg_root_mean_squared_error",
      )
  
imports: from typing import Any, Dict, Optional, Union
  import numpy
  import pandas
  from sklearn import metrics
  from sklearn.metrics._scorer import _BaseScorer
  from sktime.performance_metrics.forecasting._functions import mean_absolute_percentage_error, mean_absolute_scaled_error, mean_squared_scaled_error
  import pycaret.internal.metrics
  from pycaret.containers.metrics.base_metric import MetricContainer
label_desc: Use image node_id 1 to create a new RMSEMetricContainer object from inherited base classes: TimeSeriesMetricContainer with example: obj = RMSEMetricContainer(globals_dict)