code: def _smooth(image, sigma, mode, cval, channel_axis):
      """Return image with each channel smoothed by the Gaussian filter."""
      smoothed = np.empty_like(image)
  
      # apply Gaussian filter to all channels independently
      if channel_axis is not None:
          # can rely on gaussian to insert a 0 entry at channel_axis
          channel_axis = channel_axis % image.ndim
          sigma = (sigma,) * (image.ndim - 1)
      else:
          channel_axis = None
      gaussian(
          image,
          sigma,
          output=smoothed,
          mode=mode,
          cval=cval,
          channel_axis=channel_axis,
      )
      return smoothed
  
file_path: scikit-image/skimage/transform/pyramids.py
imports: import math
  import numpy
  from .._shared.filters import gaussian
  from .._shared.utils import convert_to_float
  from ._warps import resize
label_desc: Use image node_id 1 for calling a global function with example usage: _smooth(image, sigma, mode, cval, channel_axis) and returns: smoothed