code: def random_channel_shift(x, intensity_range, channel_axis=0):
      """Performs a random channel shift.
  
      # Arguments
          x: Input tensor. Must be 3D.
          intensity_range: Transformation intensity.
          channel_axis: Index of axis for channels in the input tensor.
  
      # Returns
          Numpy image tensor.
      """
      intensity = np.random.uniform(-intensity_range, intensity_range)
      return apply_channel_shift(
          x, intensity, channel_axis=channel_axis
      )
  
file_path: keras-preprocessing/keras_preprocessing/image/affine_transformations.py
imports: import numpy
  from .utils import array_to_img, img_to_array
label_desc: Use image node_id 7 for calling a global function with example usage: random_channel_shift(x, intensity_range, channel_axis) and returns: apply_channel_shift