code: def plot_plotly(
      self,
      fcst,
      ax=None,
      uncertainty=True,
      plot_cap=True,
      xlabel="ds",
      ylabel="y",
      figsize=(10, 6),
      include_legend=False,
      **kwargs,
  ):
      """Plot the NeuralProphet forecast.
  
      Parameters
      ----------
      fcst: pd.DataFrame output of self.predict.
      ax: Optional matplotlib axes on which to plot.
      uncertainty: Not supported in NeuralProphet.
      plot_cap: Not supported in NeuralProphet.
      xlabel: Optional label name on X-axis
      ylabel: Optional label name on Y-axis
      figsize: Optional tuple width, height in inches.
      include_legend: Not supported in NeuralProphet.
  
      Returns
      -------
      A matplotlib figure.
      """
      log.warning(
          "The attributes `uncertainty`, `plot_cap` and `include_legend` are not supported by NeuralProphet"
      )
      fig = super(TorchProphet, self).plot(
          fcst=fcst,
          ax=ax,
          xlabel=xlabel,
          ylabel=ylabel,
          figsize=figsize,
          plotting_backend="plotly",
          **kwargs,
      )
      return fig
  
imports: import logging
  import numpy
  from neuralprophet.forecaster import NeuralProphet
label_desc: Use image node_id 2 for calling a global function with example usage: plot_plotly(fcst, ax, uncertainty, plot_cap, xlabel, ylabel, figsize, include_legend) and returns: fig