<jupyter_start><jupyter_text>python3 main_nmt.py一个简单的序列到序列的模型实现，完成英语到法语的翻译任务。<jupyter_code>!pip install ipykernel
!python3 main_nmt.py<jupyter_output>{'dataset': None, 'task': None, 'decoder': None, 'hidden': None, 'batch': None, 'learn': None, 'drop': None, 'unk_mask': 1, 'layer': None, 'limit': -10000, 'path': None, 'test': None, 'sample': None, 'useKB': 1, 'entPtr': 0, 'evalp': 2, 'addName': ''}
04-19 14:28 Reading lines from data/eng-fra.txt
04-19 14:29 Pointer percentace= 0.1438264022393819 
04-19 14:29 Max responce Len: 60
04-19 14:29 Max Input Len: 52
04-19 14:29 Sample: Eng = go . $$$$, Fre = va !, Ptr = [2, 2]
04-19 14:29 Read 142222 sentence pairs train
04-19 14:29 Max len Input 52 
04-19 14:29 Vocab_size 39234 
04-19 14:29 USE_CUDA=False
04-19 14:29 Epoch:0
  0%|                                                  | 0/4445 [00:00<?, ?it/s]/home/xuehp/git/Mem2Seq/models/Mem2Seq_NMT.py:153: UserWarning: torch.nn.utils.clip_grad_norm is now deprecated in favor of torch.nn.utils.clip_grad_norm_.
  ec = torch.nn.utils.clip_grad_norm(self.encoder.parameters(), clip)
/home/xuehp/git/Mem2Seq/models/Mem2Seq_NMT.py:154: UserWarning: t[...]
{'fraction_non_alphanumeric': 0.16017316017316016, 'fraction_numerical': 0.12813852813852813, 'mean_word_length': 4.092511013215859, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '439617', 'license': 'MIT', 'n_tokens_mistral': 566, 'n_tokens_neox': 474, 'n_words': 113, 'path': '1-run-main_nmt.ipynb', 'repo_name': 'xuehuiping/Mem2Seq', 'size': '1155'}