code: def noise_like(shape, device, repeat=False):
      repeat_noise = lambda: torch.randn(
          (1, *shape[1:]), device=device
      ).repeat(shape[0], *((1,) * (len(shape) - 1)))
      noise = lambda: torch.randn(shape, device=device)
      return repeat_noise() if repeat else noise()
  
imports: from collections import OrderedDict
  from copy import copy
  import numpy
  import tensorrt
  import torch
  from polygraphy import cuda
  from polygraphy.backend.common import bytes_from_path
  from polygraphy.backend.trt import engine_from_bytes
  from polygraphy.backend.trt import util
label_desc: Use image node_id 5 for calling a global function with example usage: noise_like(shape, device, repeat) and returns: unknown