code: def resolve(
      p: ph.Placeholder,
      exec_properties: Optional[Dict[str, Any]] = None,
  ) -> Any:
      """Resolves the given placeholder."""
      if isinstance(p, proto_placeholder.MakeProtoPlaceholder):
          p = p.serialize(ph.ProtoSerializationFormat.TEXT_FORMAT)
      return placeholder_utils.resolve_placeholder_expression(
          p.encode(),
          placeholder_utils.ResolutionContext(
              exec_info=data_types.ExecutionInfo(
                  pipeline_run_id="test-run-id",
                  exec_properties=exec_properties,
                  pipeline_info=pipeline_pb2.PipelineInfo(
                      id="test-pipeline-id"
                  ),
              ),
          ),
      )
  
imports: import base64
  import functools
  from typing import Any, Dict, Optional, Type, TypeVar
  import tensorflow
  from tfx.dsl.compiler import placeholder_utils
  from tfx.dsl.placeholder import placeholder
  from tfx.dsl.placeholder import proto_placeholder
  from tfx.orchestration.portable import data_types
  from tfx.proto.orchestration import execution_invocation_pb2
  from tfx.proto.orchestration import pipeline_pb2
  from google.protobuf import message
  from google.protobuf import text_format
  from ml_metadata.proto import metadata_store_pb2
label_desc: Use image node_id 1 for calling a global function with example usage: resolve(p, exec_properties) and returns: placeholder_utils