class_docstr: A set that includes all instance types.
  
  Generally used to help represent that data that is flowing between nodes in the metric dataflow plan.
class_docstr_tok: ["A","set","that","includes","all","instance","types",".","Generally","used","to","help","represent","that","data","that","is","flowing","between","nodes","in","the","metric","dataflow","plan","."]
code: def spec_set(self) -> InstanceSpecSet:  # noqa: D
      return InstanceSpecSet(
          measure_specs=tuple(x.spec for x in self.measure_instances),
          dimension_specs=tuple(
              x.spec for x in self.dimension_instances
          ),
          time_dimension_specs=tuple(
              x.spec for x in self.time_dimension_instances
          ),
          entity_specs=tuple(x.spec for x in self.entity_instances),
          metric_specs=tuple(x.spec for x in self.metric_instances),
          metadata_specs=tuple(x.spec for x in self.metadata_instances),
      )
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from dataclasses import dataclass
  from typing import Generic, List, Tuple, TypeVar
  from dbt_semantic_interfaces.dataclass_serialization import SerializableDataclass
  from dbt_semantic_interfaces.references import MetricModelReference, SemanticModelElementReference
  from metricflow.aggregation_properties import AggregationState
  from metricflow.specs.column_assoc import ColumnAssociation
  from metricflow.specs.specs import DimensionSpec, EntitySpec, InstanceSpec, InstanceSpecSet, MeasureSpec, MetadataSpec, MetricSpec, TimeDimensionSpec
label_desc: Use image node_id 3 for calling the InstanceSet obj's underlying member method code with example usage: obj.spec_set() and returns: InstanceSpecSet