code: def test_random_fns_are_deterministic_with_seed(self):
      for random_fn in [
          Tensor.randn,
          Tensor.normal,
          Tensor.uniform,
          Tensor.scaled_uniform,
          Tensor.glorot_uniform,
          Tensor.kaiming_normal,
      ]:
          with self.subTest(msg=f"Tensor.{random_fn.__name__}"):
              Tensor.manual_seed(1337)
              a = random_fn(10, 10).realize()
              Tensor.manual_seed(1337)
              b = random_fn(10, 10).realize()
              np.testing.assert_allclose(a.numpy(), b.numpy())
  
imports: import numpy
  import torch
  import unittest, copy
  import mmap
  from tinygrad import Tensor, Device, dtypes
  from tinygrad.helpers import temp
  from extra.gradcheck import numerical_jacobian, jacobian, gradcheck
label_desc: Use image node_id 9 for calling the TestTinygrad obj's underlying member method code with example usage: obj.test_random_fns_are_deterministic_with_seed() without return types