class_docstr: Test PyTorch & CoreML forward pass parity, conversion success, ANE speed-up and trivial example accuracy
  of ANE-optimized distilbert models for sequence classification
class_docstr_tok: ["Test","PyTorch","&","CoreML","forward","pass","parity",",","conversion","success",",","ANE","speed-up","and","trivial","example","accuracy","of","ANE-optimized","distilbert","models","for","sequence","classification"]
code: def test_torch_parity(self):
      psnr = testing_utils.compute_psnr(
          self.outputs["ref"], self.outputs["test"]
      )
      logger.info(
          f"PSNR between original PyTorch module and optimized PyTorch module forward pass: {psnr}"
      )
      assert psnr > PSNR_THRESHOLD
  
file_path: ml-ane-transformers/ane_transformers/huggingface/test_distilbert.py
imports: from ane_transformers import testing_utils
  import collections
  import coremltools
  import logging
  import numpy
  import unittest
  import time
  import torch
  import transformers
  import distilbert
label_desc: Use image node_id 3 for calling the TestDistilBertForSequenceClassification obj's underlying member method code with example usage: obj.test_torch_parity() without return types