code: def test_act_with_bias():
      input_tensor = torch.randn(
          832,
          4096,
          dtype=torch.float16,
          device=get_accelerator().current_device(),
      )
      bias = torch.randn(
          4096,
          dtype=torch.float16,
          device=get_accelerator().current_device(),
      )
  
      # Reference output
      ref_output = reference_geglu_implementation(
          input_tensor, bias=bias, act_fn=ActivationType.GEGLU
      )
  
      cuda_act = CUDAGatedActivation(
          4096, torch.float16, ActivationType.GEGLU
      )
  
      # New output
      output_tensor = torch.empty(
          832,
          2048,
          dtype=torch.float16,
          device=get_accelerator().current_device(),
      )
  
      cuda_act(output_tensor, input_tensor, bias)
  
      assert allclose(output_tensor, ref_output)
  
file_path: deepspeed/tests/unit/inference/v2/kernels/core_ops/test_gated_activation.py
imports: from typing import Iterable, Optional
  import pytest
  import torch
  from deepspeed.accelerator import get_accelerator
  from deepspeed.inference.v2.kernels.core_ops import CUDAGatedActivation
  from deepspeed.inference.v2.inference_utils import ActivationType
  from ....v2.inference_test_utils import get_dtypes, allclose
label_desc: Use image node_id 4 for calling a global function with example usage: test_act_with_bias() without return types