class_docstr: A trained model using C++ implementation that is ready to use for classification or export to
  CoreML.
  
  This model should not be constructed directly.
class_docstr_tok: ["A","trained","model","using","C++","implementation","that","is","ready","to","use","for","classification","or","export","to","CoreML",".","This","model","should","not","be","constructed","directly","."]
docstr: Stylize an SFrame of Images given a style index or a list of
  styles.
  
  Parameters
  ----------
  images : SFrame | SArray | turicreate.Image
      A dataset that has the same content image column that was used
      during training.
  
  style : None | int | list
      The selected style or list of styles to use on the ``images``. If
      `None`, all styles will be applied to each image in ``images``.
  
  verbose : bool, optional
      If True, print progress updates.
  
  max_size : int or tuple
      Max input image size that will not get resized during stylization.
  
      Images with a side larger than this value, will be scaled down, due
      to time and memory constraints. If tuple, interpreted as (max
      width, max height). Without resizing, larger input images take more
      time to stylize.  Resizing can effect the quality of the final
      stylized image.
  
  batch_size : int, optional
      If you are getting memory errors, try decreasing this value. If you
      have a powerful computer, increasing this value may improve
      performance.
  
  Returns
  -------
  out : SFrame or SArray or turicreate.Image
      If ``style`` is a list, an SFrame is always returned. If ``style``
      is a single integer, the output type will match the input type
      (Image, SArray, or SFrame).
  
  See Also
  --------
  create
  
  Examples
  --------
  >>> image = tc.Image("/path/to/image.jpg")
  >>> stylized_images = model.stylize(image, style=[0, 1])
  Data:
  +--------+-------+------------------------+
  | row_id | style |     stylized_image     |
  +--------+-------+------------------------+
  |   0    |   0   | Height: 256 Width: 256 |
  |   0    |   1   | Height: 256 Width: 256 |
  +--------+-------+------------------------+
  [2 rows x 3 columns]
  
  >>> images = tc.image_analysis.load_images('/path/to/images')
  >>> stylized_images = model.stylize(images)
  Data:
  +--------+-------+------------------------+
  | row_id | style |     stylized_image     |
  +--------+-------+------------------------+
  |   0    |   0   | Height: 256 Width: 256 |
  |   0    |   1   | Height: 256 Width: 256 |
  |   0    |   2   | Height: 256 Width: 256 |
  |   0    |   3   | Height: 256 Width: 256 |
  |   1    |   0   | Height: 640 Width: 648 |
  |   1    |   1   | Height: 640 Width: 648 |
  |   1    |   2   | Height: 640 Width: 648 |
  |   1    |   3   | Height: 640 Width: 648 |
  +--------+-------+------------------------+
  [8 rows x 3 columns]
docstr_tok: ["Stylize","an","SFrame","of","Images","given","a","style","index","or","a","list","of","styles",".","Parameters","--","--","--","--","--","images",":","SFrame","|","SArray","|","turicreate.Image","A","dataset","that","has","the","same","content","image","column","that","was","used","during","training",".","style",":","None","|","int","|","list","The","selected","style","or","list","of","styles","to","use","on","the","``","images","``",".","If","`","None","`",",","all","styles","will","be","applied","to","each","image","in","``","images","``",".","verbose",":","bool",",","optional","If","True",",","print","progress","updates",".","max_size",":","int","or","tuple","Max","input","image","size","that","will","not","get","resized","during","stylization",".","Images","with","a","side","larger","than","this","value",",","will","be","scaled","down",",","due","to","time","and","memory","constraints",".","If","tuple",",","interpreted","as","(","max","width",",","max","height",")",".","Without","resizing",",","larger","input","images","take","more","time","to","stylize",".","Resizing","can","effect","the","quality","of","the","final","stylized","image",".","batch_size",":","int",",","optional","If","you","are","getting","memory","errors",",","try","decreasing","this","value",".","If","you","have","a","powerful","computer",",","increasing","this","value","may","improve","performance",".","Returns","--","--","--","-","out",":","SFrame","or","SArray","or","turicreate.Image","If","``","style","``","is","a","list",",","an","SFrame","is","always","returned",".","If","``","style","``","is","a","single","integer",",","the","output","type","will","match","the","input","type","(","Image",",","SArray",",","or","SFrame",")",".","See","Also","--","--","--","--","create","Examples","--","--","--","--",">",">",">","image","=","tc.Image","(","``","\/path\/to\/image.jpg","''",")",">",">",">","stylized_images","=","model.stylize","(","image",",","style=","[","0",",","1","]",")","Data",":","+","--","--","--","--","+","--","--","--","-+","--","--","--","--","--","--","--","--","--","--","--","--","+","|","row_id","|","style","|","stylized_image","|","+","--","--","--","--","+","--","--","--","-+","--","--","--","--","--","--","--","--","--","--","--","--","+","|","0","|","0","|","Height",":","256","Width",":","256","|","|","0","|","1","|","Height",":","256","Width",":","256","|","+","--","--","--","--","+","--","--","--","-+","--","--","--","--","--","--","--","--","--","--","--","--","+","[","2","rows","x","3","columns","]",">",">",">","images","=","tc.image_analysis.load_images","(","'\/path\/to\/images","'",")",">",">",">","stylized_images","=","model.stylize","(","images",")","Data",":","+","--","--","--","--","+","--","--","--","-+","--","--","--","--","--","--","--","--","--","--","--","--","+","|","row_id","|","style","|","stylized_image","|","+","--","--","--","--","+","--","--","--","-+","--","--","--","--","--","--","--","--","--","--","--","--","+","|","0","|","0","|","Height",":","256","Width",":","256","|","|","0","|","1","|","Height",":","256","Width",":","256","|","|","0","|","2","|","Height",":","256","Width",":","256","|","|","0","|","3","|","Height",":","256","Width",":","256","|","|","1","|","0","|","Height",":","640","Width",":","648","|","|","1","|","1","|","Height",":","640","Width",":","648","|","|","1","|","2","|","Height",":","640","Width",":","648","|","|","1","|","3","|","Height",":","640","Width",":","648","|","+","--","--","--","--","+","--","--","--","-+","--","--","--","--","--","--","--","--","--","--","--","--","+","[","8","rows","x","3","columns","]"]
code: def stylize(
      self, images, style=None, verbose=True, max_size=800, batch_size=4
  ):
      """
      Stylize an SFrame of Images given a style index or a list of
      styles.
  
      Parameters
      ----------
      images : SFrame | SArray | turicreate.Image
          A dataset that has the same content image column that was used
          during training.
  
      style : None | int | list
          The selected style or list of styles to use on the ``images``. If
          `None`, all styles will be applied to each image in ``images``.
  
      verbose : bool, optional
          If True, print progress updates.
  
      max_size : int or tuple
          Max input image size that will not get resized during stylization.
  
          Images with a side larger than this value, will be scaled down, due
          to time and memory constraints. If tuple, interpreted as (max
          width, max height). Without resizing, larger input images take more
          time to stylize.  Resizing can effect the quality of the final
          stylized image.
  
      batch_size : int, optional
          If you are getting memory errors, try decreasing this value. If you
          have a powerful computer, increasing this value may improve
          performance.
  
      Returns
      -------
      out : SFrame or SArray or turicreate.Image
          If ``style`` is a list, an SFrame is always returned. If ``style``
          is a single integer, the output type will match the input type
          (Image, SArray, or SFrame).
  
      See Also
      --------
      create
  
      Examples
      --------
      >>> image = tc.Image("/path/to/image.jpg")
      >>> stylized_images = model.stylize(image, style=[0, 1])
      Data:
      +--------+-------+------------------------+
      | row_id | style |     stylized_image     |
      +--------+-------+------------------------+
      |   0    |   0   | Height: 256 Width: 256 |
      |   0    |   1   | Height: 256 Width: 256 |
      +--------+-------+------------------------+
      [2 rows x 3 columns]
  
      >>> images = tc.image_analysis.load_images('/path/to/images')
      >>> stylized_images = model.stylize(images)
      Data:
      +--------+-------+------------------------+
      | row_id | style |     stylized_image     |
      +--------+-------+------------------------+
      |   0    |   0   | Height: 256 Width: 256 |
      |   0    |   1   | Height: 256 Width: 256 |
      |   0    |   2   | Height: 256 Width: 256 |
      |   0    |   3   | Height: 256 Width: 256 |
      |   1    |   0   | Height: 640 Width: 648 |
      |   1    |   1   | Height: 640 Width: 648 |
      |   1    |   2   | Height: 640 Width: 648 |
      |   1    |   3   | Height: 640 Width: 648 |
      +--------+-------+------------------------+
      [8 rows x 3 columns]
      """
      if not isinstance(images, (_tc.SFrame, _tc.SArray, _tc.Image)):
          raise TypeError(
              '"image" parameter must be of type SFrame, SArray or turicreate.Image.'
          )
      if (
          isinstance(images, (_tc.SFrame, _tc.SArray))
          and len(images) == 0
      ):
          raise _ToolkitError('"image" parameter cannot be empty')
      if style is not None and not isinstance(style, (int, list)):
          raise TypeError(
              '"style" must parameter must be a None, int or a list'
          )
      if not isinstance(max_size, int):
          raise TypeError('"max_size" must parameter must be an int')
      if max_size < 1:
          raise _ToolkitError(
              "'max_size' must be greater than or equal to 1"
          )
      if not isinstance(batch_size, int):
          raise TypeError('"batch_size" must parameter must be an int')
      if batch_size < 1:
          raise _ToolkitError(
              "'batch_size' must be greater than or equal to 1"
          )
  
      options = {}
      options["style_idx"] = style
      options["verbose"] = verbose
      options["max_size"] = max_size
      options["batch_size"] = batch_size
  
      if isinstance(style, list) or style is None:
          if isinstance(images, _tc.SFrame):
              image_feature = _tkutl._find_only_image_column(images)
              stylized_images = self.__proxy__.predict(
                  images[image_feature], options
              )
              stylized_images = stylized_images.rename(
                  {"stylized_image": "stylized_" + str(image_feature)}
              )
              return stylized_images
          return self.__proxy__.predict(images, options)
      else:
          if isinstance(images, _tc.SFrame):
              if len(images) == 0:
                  raise _ToolkitError("SFrame cannot be empty")
              image_feature = _tkutl._find_only_image_column(images)
              stylized_images = self.__proxy__.predict(
                  images[image_feature], options
              )
              stylized_images = stylized_images.rename(
                  {"stylized_image": "stylized_" + str(image_feature)}
              )
              return stylized_images
          elif isinstance(images, (_tc.Image)):
              stylized_images = self.__proxy__.predict(images, options)
              return stylized_images["stylized_image"][0]
          elif isinstance(images, (_tc.SArray)):
              stylized_images = self.__proxy__.predict(images, options)
              return stylized_images["stylized_image"]
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import turicreate.toolkits._internal_utils
  from turicreate.toolkits import _coreml_utils
  from turicreate.toolkits._internal_utils import _raise_error_if_not_sframe
  from turicreate._deps.minimal_package import _minimal_package_import_check
  from ..None import _pre_trained_models
  from turicreate.toolkits._model import Model
  from turicreate.toolkits._main import ToolkitError
  import turicreate
  from .._mps_utils import MpsStyleGraphAPI
label_desc: Use image node_id 7 for calling the StyleTransfer obj's underlying member method code with example usage: obj.stylize(images, style, verbose, max_size, batch_size) and returns: self, stylized_images, stylized_images, stylized_images, stylized_images