如何在seq2seq生成任务中使用AllenNLP实现解码器？

pip install allennlp

{
  "dataset_reader": {
    "type": "seq2seq",
    "source_tokenizer": {
      "type": "word"
    },
    "target_tokenizer": {
      "type": "word"
    }
  },
  "model": {
    "type": "simple_seq2seq",
    "encoder": {
      "type": "gru",
      "hidden_size": 256,
      "num_layers": 2
    },
    "decoder": {
      "type": "gru",
      "hidden_size": 256,
      "num_layers": 2
    }
  },
  "iterator": {
    "type": "bucket",
    "sorting_keys": [["source_tokens", "num_tokens"]],
    "batch_size": 32
  },
  "trainer": {
    "optimizer": {
      "type": "adam"
    },
    "num_epochs": 10,
    "cuda_device": 0
  }
}

from allennlp.commands import train

config_file = "path/to/model_config.json"
serialization_dir = "path/to/serialization_dir"

train.run(config_file, serialization_dir)

python train_script.py

from allennlp.models import load_archive

archive_file = "path/to/model_archive.tar.gz"
input_sequence = "input sequence"

archive = load_archive(archive_file)
model = archive.model
output_sequence = model.decode(input_sequence)
print(output_sequence)