class_docstr: This class is taken from the original WHAMR! scripts.
  The original script can be found in
  http://wham.whisper.ai/
  
  This class is used to simulate the room-impulse-responses (RIRs) in the WHAMR dataset.
class_docstr_tok: ["This","class","is","taken","from","the","original","WHAMR","!","scripts",".","The","original","script","can","be","found","in","http",":","\/\/wham.whisper.ai\/","This","class","is","used","to","simulate","the","room-impulse-responses","(","RIRs",")","in","the","WHAMR","dataset","."]
code: def compute_rir(self):
      self.rir = []
      self.visibility = None
  
      self.image_source_model()
  
      for m, mic in enumerate(self.mic_array.R.T):
          h = []
          for s, source in enumerate(self.sources):
              h.append(
                  source.get_rir(
                      mic, self.visibility[s][m], self.fs, self.t0
                  )[: self.max_rir_len]
              )
          self.rir.append(h)
  
file_path: speechbrain/recipes/WHAMandWHAMR/enhancement/wham_room.py
imports: import numpy
  import pyroomacoustics
  from pyroomacoustics.parameters import constants
  from scipy.signal import resample_poly
label_desc: Use image node_id 3 for calling the WhamRoom obj's underlying member method code with example usage: obj.compute_rir() without return types