code: def mock_model():
      config_embed = sockeye.encoder.EmbeddingConfig(
          vocab_size=20, num_embed=4, dropout=0.0
      )
      config_encoder = sockeye.encoder.EncoderConfig(
          model_size=4,
          attention_heads=1,
          feed_forward_num_hidden=4,
          act_type="relu",
          num_layers=1,
          dropout_attention=0.0,
          dropout_act=0.0,
          dropout_prepost=0.0,
          positional_embedding_type="fixed",
          preprocess_sequence="none",
          postprocess_sequence="none",
          max_seq_len_source=30,
          max_seq_len_target=30,
      )
      config = sockeye.model.ModelConfig(
          config_data=None,
          vocab_source_size=20,
          vocab_target_size=20,
          config_embed_source=config_embed,
          config_embed_target=config_embed,
          config_encoder=config_encoder,
          config_decoder=config_encoder,
          weight_tying_type="none",
      )
      model = sockeye.model.SockeyeModel(config=config)
      return model
  
file_path: sockeye/test/unit/test_params.py
imports: import glob
  import itertools
  import os.path
  import tempfile
  import pytest
  import torch
  import sockeye.constants
  import sockeye.encoder
  import sockeye.model
  import sockeye.training
label_desc: Use image node_id 3 for calling a global function with example usage: mock_model() and returns: model