code: def _test_base_layer_gate(d_model, batch_size, n_expert):
      _ensure_initialized()
      gate = BaseLayerGate(
          d_model, n_expert, dist.get_world_size()
      ).cuda()
      x = torch.rand(batch_size, d_model).cuda()
      x.requires_grad = True
      top_idx, top_val = gate(x)
      print(top_idx, top_val)
  
file_path: thu-pacman-faster-moe/tests/test_gates.py
imports: import pytest
  import os
  import sys
  import json
  import math
  import torch
  import torch.distributed
  import torch.nn.functional
  from fmoe.gates import GShardGate, SwitchGate, BaseLayerGate
  from test_ddp import _run_distributed
label_desc: Use image node_id 7 for calling a global function with example usage: _test_base_layer_gate(d_model, batch_size, n_expert) without return types