Add unit tests for generation models #3018
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guoshengCS
reviewed
Aug 19, 2022
| unk_token=unk_token, | ||
| pad_token=pad_token, | ||
| mask_token=mask_token, | ||
| **kwargs) |
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170--813 这段不用加，会有hook处理
| bos_token=bos_token, | ||
| eos_token=eos_token, | ||
| eol_token=eol_token, | ||
| **kwargs) |
guoshengCS
reviewed
Aug 22, 2022
| import json | ||
| import jieba | ||
| import shutil | ||
| import sentencepiece as spm |
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这里是否需要jieba和sentencepiece
| generated_summaries = tok.batch_decode( | ||
| hypotheses_batch.tolist(), | ||
| clean_up_tokenization_spaces=True, | ||
| skip_special_tokens=True) |
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这里是否要对生成的结果来check下，看HF的会有这个的判断
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这里是因为 bart-large 生成出来的结果是乱的，无意义的句子，因此暂时去掉了 assert，待单测全部搞完之后，需要对模型权重本身做验证
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| decoder_start_token_id = ( | ||
| decoder_start_token_id if decoder_start_token_id is not None else | ||
| getattr(self, pretrained_model_name).config.get( |
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pretrained_model_name是从model获取的吗，这个又是在哪里设置的呢，感觉作为model的attr不太合适
| input_ids_clone = input_ids.repeat_interleave(beam_scorer.num_beams, | ||
| axis=0) | ||
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| kwargs["use_cache"] = True |
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上面_sample_generate那些不需要设置这个吗
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这里和 hf 对齐设置，有的单测跑 use_cache 为 True，而有的为 False，能同时兼顾到不同配置的情况
guoshengCS
approved these changes
Aug 22, 2022
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Description
Add unit tests for generation models.
Done:
Unit tests:
test_tokenizer_common.pyto support morefrom_pretrained_filterFunctions:
TODO: