code: def test_randn(size, seed, dtype, device):
      @triton.jit
      def kernel(X, N, seed, dtype: tl.constexpr):
          pid = tl.program_id(0).to(dtype)
          offset = pid * BLOCK + tl.arange(0, BLOCK)
          rand = tl.randn(seed, offset)
          tl.store(X + offset, rand, mask=offset < N)
  
      # triton result
      x = torch.empty(size, dtype=torch.float32, device=device)
      N = x.numel()
      grid = (triton.cdiv(N, BLOCK),)
      kernel[grid](x, N, seed, dtype=getattr(tl, dtype))
      assert abs(x.mean()) < 1e-2
      assert abs(x.std() - 1) < 1e-2
  
imports: import numpy
  import pytest
  import scipy.stats
  import torch
  import triton
  import triton.language
label_desc: Use image node_id 3 for calling a global function with example usage: test_randn(size, seed, dtype, device) without return types