class_docstr: Image modality
  
  Parameters
  ----------
  images: Union[List, numpy.ndarray], optional
      A list or tensor of images that the row indices are
      aligned with user/item in `ids`.
  
  paths: List[str], optional
      A list of paths, to images stored on disk, which
      the row indices are aligned with user/item in `ids`..
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docstr: Build the model based on provided list of ordered ids
  
  Parameters
  ----------
  id_map: dict, optional
      A dictionary holds mapping from original ids to
      mapped integer indices of users/items.
  
  Returns
  -------
  image_modality: :obj:`<cornac.data.ImageModality>`
      An object of type `ImageModality`.
docstr_tok: ["Build","the","model","based","on","provided","list","of","ordered","ids","Parameters","--","--","--","--","--","id_map",":","dict",",","optional","A","dictionary","holds","mapping","from","original","ids","to","mapped","integer","indices","of","users\/items",".","Returns","--","--","--","-","image_modality",":",":","obj",":","`","<","cornac.data.ImageModality",">","`","An","object","of","type","`","ImageModality","`","."]
code: def build(self, id_map=None, **kwargs):
      """Build the model based on provided list of ordered ids
  
      Parameters
      ----------
      id_map: dict, optional
          A dictionary holds mapping from original ids to
          mapped integer indices of users/items.
  
      Returns
      -------
      image_modality: :obj:`<cornac.data.ImageModality>`
          An object of type `ImageModality`.
  
      """
      super().build(id_map=id_map)
      return self
  
imports: from .None import FeatureModality
label_desc: Use image node_id 2 for calling the ImageModality obj's underlying member method code with example usage: obj.build(id_map) and returns: self