class_docstr: Calculate performance metrics of a given model on a given dataset.
  
  Parameters
  ----------
  scorers: Union[Dict[str, Union[Callable, str]], List[Any]] , default: None
      Scorers to override the default scorers (metrics), find more about the supported formats at
      https://docs.deepchecks.com/stable/user-guide/general/metrics_guide.html
  {additional_check_init_params:2*indent}
docstr: Compute the metric result using the ignite metrics compute method and reduce to a scalar.
docstr_tok: ["Compute","the","metric","result","using","the","ignite","metrics","compute","method","and","reduce","to","a","scalar","."]
code: def compute(
      self, context: Context, dataset_kind: DatasetKind.TRAIN
  ) -> CheckResult:
      """Compute the metric result using the ignite metrics compute method and reduce to a scalar."""
      results_dict = {}
      for name, scorer in self.scorers.items():
          result = scorer.compute()
          results_dict[name] = (
              [result] if isinstance(result, Number) else result
          )
      result_df = metric_results_to_df(
          results_dict, context.get_data_by_kind(dataset_kind)
      )
      display = result_df if context.with_display else None
      return CheckResult(
          result_df,
          header="Single Dataset Performance",
          display=display,
      )
  
imports: from numbers import Number
  from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Union
  from deepchecks.core import CheckResult, ConditionResult, DatasetKind
  from deepchecks.core.condition import ConditionCategory
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.core.reduce_classes import ReduceMetricClassMixin
  from deepchecks.utils.docref import doclink
  from deepchecks.vision._shared_docs import docstrings
  from deepchecks.vision.base_checks import SingleDatasetCheck
  from deepchecks.vision.context import Context
  from deepchecks.vision.metrics_utils.scorers import get_scorers_dict, metric_results_to_df
  from deepchecks.vision.vision_data.batch_wrapper import BatchWrapper
label_desc: Use image node_id 4 for calling the SingleDatasetPerformance obj's underlying member method code with example usage: obj.compute(context, dataset_kind) and returns: CheckResult