code: def series_memory_usage(series, index=True, deep=False):
      """
      Return the memory usage of the Series.
  
      The memory usage can optionally include the contribution of
      the index and of elements of `object` dtype.
  
      Parameters
      ----------
      index : bool, default True
          Specifies whether to include the memory usage of the Series index.
      deep : bool, default False
          If True, introspect the data deeply by interrogating
          `object` dtypes for system-level memory consumption, and include
          it in the returned value.
  
      Returns
      -------
      int
          Bytes of memory consumed.
  
      See Also
      --------
      numpy.ndarray.nbytes : Total bytes consumed by the elements of the
          array.
      DataFrame.memory_usage : Bytes consumed by a DataFrame.
  
      Examples
      --------
      >>> import mars.dataframe as md
      >>> s = md.Series(range(3))
      >>> s.memory_usage().execute()
      152
  
      Not including the index gives the size of the rest of the data, which
      is necessarily smaller:
  
      >>> s.memory_usage(index=False).execute()
      24
  
      The memory footprint of `object` values is ignored by default:
  
      >>> s = md.Series(["a", "b"])
      >>> s.values.execute()
      array(['a', 'b'], dtype=object)
  
      >>> s.memory_usage().execute()
      144
  
      >>> s.memory_usage(deep=True).execute()
      260
      """
      op = DataFrameMemoryUsage(index=index, deep=deep)
      return op(series)
  
imports: import operator
  from functools import reduce
  import numpy
  import pandas
  from ...None import opcodes
  from ...config import options
  from ...core.operand import OperandStage
  from ...serialization.serializables import BoolField, Int64Field
  from ...utils import ceildiv, lazy_import
  from ..operands import DataFrameOperand, DataFrameOperandMixin
  from ..core import IndexValue
  from ..utils import parse_index
label_desc: Use image node_id 2 for calling a global function with example usage: series_memory_usage(series, index, deep) and returns: op