code: def _trainer(
      examples: InputArtifact[standard_artifacts.Examples],
      schema: InputArtifact[standard_artifacts.Schema],
      transform_graph: InputArtifact[standard_artifacts.TransformGraph],
      model: OutputArtifact[standard_artifacts.Model],
  ):
      del examples, schema, transform_graph, model
  
imports: from tfx.dsl.compiler import compiler
  from tfx.dsl.component.experimental.annotations import InputArtifact
  from tfx.dsl.component.experimental.annotations import OutputArtifact
  from tfx.dsl.component.experimental.decorators import component
  from tfx.dsl.control_flow.for_each import ForEach
  from tfx.dsl.experimental.conditionals import conditional
  from tfx.dsl.experimental.node_execution_options import utils
  from tfx.orchestration import pipeline
  from tfx.proto.orchestration import pipeline_pb2
  from tfx.types import standard_artifacts
label_desc: Use image node_id 6 for calling a global function with example usage: _trainer(examples, schema, transform_graph, model) without return types