code: def test_pf_transformer_execution(
      g_rng,
      src_len,
      tgt_len,
      batch_size,
      embed_dim,
      num_heads,
      dropout,
      rng,
      add_attn_bias,
      num_encoder_layers,
      num_decoder_layers,
      fix_parameters,
      ctx,
      func_name,
  ):
      rng = process_rng(rng)
  
      kw = {}
      insert_if_not_none(kw, "embed_dim", embed_dim)
      insert_if_not_none(kw, "num_heads", num_heads)
      insert_if_not_none(kw, "num_encoder_layers", num_encoder_layers)
      insert_if_not_none(kw, "num_decoder_layers", num_decoder_layers)
      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)
  
      src = nn.Variable.from_numpy_array(
          g_rng.randn(src_len, batch_size, embed_dim).astype(
              np.float32
          ),
          need_grad=True,
      )
      tgt = 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(src, tgt, **kw)
      y.forward()
      y.backward()
  
      if add_attn_bias:
          assert (
              len(nn.get_parameters())
              == 18 * num_encoder_layers + 30 * num_decoder_layers
          )
      else:
          assert (
              len(nn.get_parameters())
              == 16 * num_encoder_layers + 26 * num_decoder_layers
          )
  
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 28 for calling a global function with example usage: test_pf_transformer_execution(g_rng, src_len, tgt_len, batch_size, embed_dim, num_heads, dropout, rng, add_attn_bias, num_encoder_layers, num_decoder_layers, fix_parameters, ctx, func_name) without return types