code: def gelu(activations: torch.Tensor) -> torch.Tensor:
      assert activations.is_contiguous()
      assert get_accelerator().on_accelerator(activations)
  
      output = torch.empty_like(activations)
      n_elements = output.numel()
      grid = lambda meta: (triton.cdiv(n_elements, meta["BLOCK_SIZE"]),)
      gelu_kernel[grid](
          activations, output, n_elements, BLOCK_SIZE=1024
      )
      return output
  
imports: import torch
  import triton
  import triton.language
  from deepspeed.accelerator import get_accelerator
label_desc: Use image node_id 3 for calling a global function with example usage: gelu(activations) and returns: output