code: def __call__(self, x, uttid=None, train=True):
      if not train:
          return x
  
      x = x.astype(numpy.float32)
  
      if x.ndim != 1:
          # Must be single channel
          raise RuntimeError(
              "Input x must be one dimensional array, but got {}".format(
                  x.shape
              )
          )
  
      rir, rate = self.utt2rir[uttid]
      if rir.ndim == 2:
          # FIXME(kamo): Use chainer.convolution_1d?
          # return [Time, Channel]
          return numpy.stack(
              [scipy.convolve(x, r, mode="same") for r in rir], axis=-1
          )
      else:
          return scipy.convolve(x, rir, mode="same")
  
imports: import librosa
  import numpy
  import scipy
  import soundfile
  from espnet.utils.io_utils import SoundHDF5File
label_desc: Use image node_id 3 for calling the RIRConvolve obj's underlying member method code with example usage: obj.__call__(x, uttid, train) and returns: x, numpy, scipy