code: def __init__(self, globals_dict: dict) -> None:
      super().__init__(
          id="mse",
          name="MSE",
          score_func=metrics.mean_squared_error,
          greater_is_better=False,
          scorer="neg_mean_squared_error",
      )
  
imports: from typing import Any, Dict, Optional, Union
  import numpy
  from sklearn import metrics
  from sklearn.metrics._regression import _check_reg_targets
  from sklearn.metrics._scorer import _BaseScorer
  from sklearn.utils.validation import check_consistent_length
  import pycaret.containers.base_container
  import pycaret.internal.metrics
  from pycaret.containers.metrics.base_metric import MetricContainer
label_desc: Use image node_id 1 to create a new MSEMetricContainer object from inherited base classes: RegressionMetricContainer with example: obj = MSEMetricContainer(globals_dict)