code: def row_norms(X, squared=False):
      if isinstance(X, np.ndarray):
          return skm.row_norms(X, squared=squared)
      return X.map_blocks(
          skm.row_norms,
          chunks=(X.chunks[0],),
          drop_axis=1,
          squared=squared,
      )
  
imports: import contextlib
  import datetime
  import functools
  import logging
  import warnings
  from collections.abc import Sequence
  from multiprocessing import cpu_count
  from numbers import Integral
  from timeit import default_timer
  import dask
  import dask.array
  import dask.dataframe
  import numpy
  import pandas
  import sklearn.utils.extmath
  import sklearn.utils.validation
  from dask import delayed
  from dask.array.utils import assert_eq
  from dask.dataframe.utils import assert_eq
  from ._utils import ConstantFunction
label_desc: Use image node_id 6 for calling a global function with example usage: row_norms(X, squared) and returns: X, skm