code: def normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None):
      dtype = dtype or floatx()
      dtype = to_torch_dtype(dtype)
      # Do not use generator during symbolic execution.
      if get_device() == "meta":
          return torch.normal(
              mean, stddev, size=shape, dtype=dtype, device=get_device()
          )
      generator = torch_seed_generator(seed)
      return torch.normal(
          mean,
          stddev,
          size=shape,
          generator=generator,
          dtype=dtype,
          device=get_device(),
      )
  
imports: import torch
  import torch._dynamo
  import torch.nn.functional
  from keras.backend.config import floatx
  from keras.backend.torch.core import convert_to_tensor
  from keras.backend.torch.core import get_device
  from keras.backend.torch.core import to_torch_dtype
  from keras.random.seed_generator import SeedGenerator
  from keras.random.seed_generator import draw_seed
  from keras.random.seed_generator import make_default_seed
label_desc: Use image node_id 2 for calling a global function with example usage: normal(shape, mean, stddev, dtype, seed) and returns: torch, torch