code: def stats_file(tmp_path: Path):
      p = tmp_path / "stats.npy"
  
      count = 5
      x = np.random.randn(count, 10)
      s = x.sum(0)
      s = np.pad(s, [0, 1], mode="constant", constant_values=count)
      s2 = (x**2).sum(0)
      s2 = np.pad(s2, [0, 1], mode="constant", constant_values=0.0)
  
      stats = np.stack([s, s2])
      np.save(p, stats)
  
      return p
  
imports: from pathlib import Path
  import numpy
  import pytest
  import torch
  from espnet2.asr.specaug.specaug import SpecAug
  from espnet2.asr_transducer.decoder.mega_decoder import MEGADecoder
  from espnet2.asr_transducer.decoder.rnn_decoder import RNNDecoder
  from espnet2.asr_transducer.decoder.rwkv_decoder import RWKVDecoder
  from espnet2.asr_transducer.decoder.stateless_decoder import StatelessDecoder
  from espnet2.asr_transducer.encoder.encoder import Encoder
  from espnet2.asr_transducer.espnet_transducer_model import ESPnetASRTransducerModel
  from espnet2.asr_transducer.joint_network import JointNetwork
  from espnet2.layers.global_mvn import GlobalMVN
  from espnet2.layers.utterance_mvn import UtteranceMVN
label_desc: Use image node_id 1 for calling a global function with example usage: stats_file(tmp_path) and returns: p