class_docstr: Class collect metrics from the training engine and send it to plugins, when send is called
class_docstr_tok: ["Class","collect","metrics","from","the","training","engine","and","send","it","to","plugins",",","when","send","is","called"]
docstr: Appends outputs.MatplotlibPlot output, with specified parameters.
  
  Args:
      **kwargs: keyword arguments for MatplotlibPlot
  
  Returns:
      Plotlosses object (so it works for chaining)
docstr_tok: ["Appends","outputs.MatplotlibPlot","output",",","with","specified","parameters",".","Args",":","*","*","kwargs",":","keyword","arguments","for","MatplotlibPlot","Returns",":","Plotlosses","object","(","so","it","works","for","chaining",")"]
code: def to_matplotlib(self, **kwargs) -> "PlotLosses":
      """Appends outputs.MatplotlibPlot output, with specified parameters.
  
      Args:
          **kwargs: keyword arguments for MatplotlibPlot
  
      Returns:
          Plotlosses object (so it works for chaining)
      """
      self.outputs.append(outputs.MatplotlibPlot(**kwargs))
      return self
  
file_path: livelossplot/livelossplot/plot_losses.py
imports: import warnings
  from typing import Type, TypeVar, List, Union
  import livelossplot
  from livelossplot.main_logger import MainLogger
  from livelossplot import outputs
label_desc: Use image node_id 6 for calling the PlotLosses obj's underlying member method code with example usage: obj.to_matplotlib() and returns: self