class_docstr: Class for experiment with multiple trial types.
  
  A canonical use case for this is tuning a large production system
  with limited evaluation budget and a simulator which approximates
  evaluations on the main system. Trial deployment and data fetching
  is separate for the two systems, but the final data is combined and
  fed into multi-task models.
  
  See the Multi-Task Modeling tutorial for more details.
  
  Attributes:
      name: Name of the experiment.
      description: Description of the experiment.
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code: def remove_tracking_metric(
      self, metric_name: str
  ) -> "MultiTypeExperiment":
      if metric_name not in self._tracking_metrics:
          raise ValueError(
              f"Metric `{metric_name}` doesn't exist on experiment."
          )
  
      # Required fields
      del self._tracking_metrics[metric_name]
      del self._metric_to_trial_type[metric_name]
  
      # Optional
      if metric_name in self._metric_to_canonical_name:
          del self._metric_to_canonical_name[metric_name]
      return self
  
imports: import logging
  from typing import Any, Dict, List, Optional, Set
  from ax.core.arm import Arm
  from ax.core.base_trial import BaseTrial
  from ax.core.data import Data
  from ax.core.experiment import DataType, Experiment
  from ax.core.metric import Metric, MetricFetchResult
  from ax.core.optimization_config import OptimizationConfig
  from ax.core.runner import Runner
  from ax.core.search_space import SearchSpace
  from ax.utils.common.docutils import copy_doc
  from ax.utils.common.logger import get_logger
label_desc: Use image node_id 6 for calling the MultiTypeExperiment obj's underlying member method code with example usage: obj.remove_tracking_metric(metric_name) and returns: self