docstr: This function selects a random segment of a given length withing the mixture.
  The corresponding targets are selected accordingly
docstr_tok: ["This","function","selects","a","random","segment","of","a","given","length","withing","the","mixture",".","The","corresponding","targets","are","selected","accordingly"]
code: def cut_signals(self, mixture, targets):
      """This function selects a random segment of a given length withing the mixture.
      The corresponding targets are selected accordingly"""
      randstart = torch.randint(
          0,
          1
          + max(0, mixture.shape[1] - self.hparams.training_signal_len),
          (1,),
      ).item()
      targets = targets[
          :, randstart : randstart + self.hparams.training_signal_len, :
      ]
      mixture = mixture[
          :, randstart : randstart + self.hparams.training_signal_len
      ]
      return mixture, targets
  
imports: import os
  import sys
  import torch
  import torch.nn.functional
  import torchaudio
  import speechbrain
  import speechbrain.nnet.schedulers
  from speechbrain.utils.distributed import run_on_main
  from hyperpyyaml import load_hyperpyyaml
  import numpy
  from tqdm import tqdm
  import csv
  import logging
  from speechbrain.core import AMPConfig
label_desc: Use image node_id 7 for calling the Separation obj's underlying member method code with example usage: obj.cut_signals(mixture, targets) and returns: mixture,  targets