code: def test_pf_transformer_decode_execution(
      g_rng,
      tgt_len,
      batch_size,
      embed_dim,
      num_heads,
      dropout,
      rng,
      add_attn_bias,
      dim_feedforward,
      fix_parameters,
      ctx,
      func_name,
  ):
      rng = process_rng(rng)
  
      kw = {}
      insert_if_not_none(kw, "dim_feedforward", dim_feedforward)
      insert_if_not_default(kw, "dropout", dropout, 0.0)
      insert_if_not_none(kw, "rng", rng)
      insert_if_not_default(kw, "add_attn_bias", add_attn_bias, False)
      insert_if_not_default(kw, "fix_parameters", fix_parameters, False)
  
      tgt = nn.Variable.from_numpy_array(
          g_rng.randn(tgt_len, batch_size, embed_dim).astype(
              np.float32
          ),
          need_grad=True,
      )
      memory = nn.Variable.from_numpy_array(
          g_rng.randn(tgt_len, batch_size, embed_dim).astype(
              np.float32
          ),
          need_grad=True,
      )
  
      # Check execution
      y = PF.transformer_decode(tgt, memory, embed_dim, num_heads, **kw)
      y.forward()
      y.backward()
  
      if add_attn_bias:
          assert len(nn.get_parameters()) == 30
      else:
          assert len(nn.get_parameters()) == 26
  
imports: import pytest
  import numpy
  import nnabla
  import nnabla.functions
  import nnabla.parametric_functions
  import nnabla.initializer
  from nnabla.testing import assert_allclose
  from nbla_test_utils import list_context
label_desc: Use image node_id 30 for calling a global function with example usage: test_pf_transformer_decode_execution(g_rng, tgt_len, batch_size, embed_dim, num_heads, dropout, rng, add_attn_bias, dim_feedforward, fix_parameters, ctx, func_name) without return types