original_docstring: Implement the training algorithm given the components defined in
          `self.define`.
  
          INSTRUCTIONS
          ------------
          This method should implement a training interval (possibly multiple
          dataset epochs) as a loop up to some iterations (increment `self.iter`
          until some period argument in `self.args`). Then, the loop should be
          followed by evaluation and visualization code.
  
          .. info:: This routine will be executed multiple times until the
             experiment's termination criterion, described by `self.is_done`,
             is fulfilled.
  
          
docstring: Implement the training algorithm given the components defined in
  `self.define`.
  
  INSTRUCTIONS
  
  This method should implement a training interval (possibly multiple
  dataset epochs) as a loop up to some iterations (increment `self.iter`
  until some period argument in `self.args`). Then, the loop should be
  followed by evaluation and visualization code.
  
  : This routine will be executed multiple times until the
  experiment's termination criterion, described by `self.is_done`,
  is fulfilled.
docstring_tokens: Implement the training algorithm given the components defined in ` self . define ` . INSTRUCTIONS This method should implement a training interval ( possibly multiple dataset epochs ) as a loop up to some iterations ( increment ` self . iter ` until some period argument in ` self . args ` ) . Then the loop should be followed by evaluation and visualization code . : This routine will be executed multiple times until the experiment ' s termination criterion described by ` self . is_done ` is fulfilled .
code: def execute(self):
          """Implement the training algorithm given the components defined in
          `self.define`.
  
          INSTRUCTIONS
          ------------
          This method should implement a training interval (possibly multiple
          dataset epochs) as a loop up to some iterations (increment `self.iter`
          until some period argument in `self.args`). Then, the loop should be
          followed by evaluation and visualization code.
  
          .. info:: This routine will be executed multiple times until the
             experiment's termination criterion, described by `self.is_done`,
             is fulfilled.
  
          """
          pass
code_tokens: def execute ( self ) : pass
short_docstring: Implement the training algorithm given the components defined in
  `self.define`.
short_docstring_tokens: Implement the training algorithm given the components defined in ` self . define ` .
comment: """Implement the training algorithm given the components defined in
          `self.define`.
  
          INSTRUCTIONS
          ------------
          This method should implement a training interval (possibly multiple
          dataset epochs) as a loop up to some iterations (increment `self.iter`
          until some period argument in `self.args`). Then, the loop should be
          followed by evaluation and visualization code.
  
          .. info:: This routine will be executed multiple times until the
             experiment's termination criterion, described by `self.is_done`,
             is fulfilled.
  
          """