code: def test_dvc_integrated_compress(shape):
      # test the overall integrated compression pipeline
      # (to be used by final trained model)
      rng = np.random.default_rng(1234)
      image1 = gen_random_image(shape, rng)
      image2 = gen_random_image(shape, rng)
  
      # test compression functions
      model = DVC()
      model.update(force=True)
      model = model.eval()
      compressed = model.compress(image1, image2)
      image2_est = model.decompress(image1, compressed)
  
      assert image2_est.shape == image2.shape
  
file_path: NeuralCompression/tests/test_models.py
imports: import numpy
  import pytest
  import torch
  from utils import create_input
  import neuralcompression.functional
  from neuralcompression.models.deep_video_compression import DVC, DVCCompressionDecoder, DVCCompressionEncoder, DVCMotionCompensationModel, DVCPyramidFlowEstimator
label_desc: Use image node_id 5 for calling a global function with example usage: test_dvc_integrated_compress(shape) without return types