code: def test_real_safetensors(self):
      import torch
      from safetensors.torch import save_file
  
      torch.manual_seed(1337)
      tensors = {
          "weight1": torch.randn((16, 16)),
          "weight2": torch.arange(0, 17, dtype=torch.uint8),
          "weight3": torch.arange(0, 17, dtype=torch.int32).reshape(
              17, 1, 1
          ),
          "weight4": torch.arange(0, 2, dtype=torch.uint8),
      }
      save_file(tensors, temp("model.safetensors"))
  
      ret = safe_load(temp("model.safetensors"))
      for k, v in tensors.items():
          np.testing.assert_array_equal(ret[k].numpy(), v.numpy())
      safe_save(ret, temp("model.safetensors_alt"))
      with open(temp("model.safetensors"), "rb") as f:
          with open(temp("model.safetensors_alt"), "rb") as g:
              assert f.read() == g.read()
      ret2 = safe_load(temp("model.safetensors_alt"))
      for k, v in tensors.items():
          np.testing.assert_array_equal(ret2[k].numpy(), v.numpy())
  
imports: import pathlib, unittest
  import numpy
  from tinygrad import Tensor, Device, dtypes
  from tinygrad.nn.state import safe_load, safe_save, get_state_dict, torch_load
  from tinygrad.helpers import Timing, CI, fetch, temp
label_desc: Use image node_id 1 for calling the TestSafetensors obj's underlying member method code with example usage: obj.test_real_safetensors() without return types