TF: use the correct config with (...)EncoderDecoder models
#18097
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gante
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gante
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(...)EncoderDecoder models
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I believe they are -- going to give it a go afterwards if @ydshieh also agrees :) |
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I have limited connection at this moment in the mountain, so feel free to merge if you prefer. Regarding the common mixin, good for me. I see there are a few little things to address, like the input names (input_ids, pixel values etc). Thank you for the fix, @gante |
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@ydshieh can I have a review plz 🙏 |
| unpacked_inputs = input_processing(func, self.config, main_input, **fn_args_and_kwargs) | ||
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| # Encoder Decoder models delegate the application of the configuration options to their inner models. | ||
| if "encoder_decoder" in str(self).lower(): |
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Just a nit, no need to feel strong:
I would personally prefer to use self.__name__ instead of str and test against EncoderDecoder. If I understand correctly, str gives the full path, which includes the module name like encoder_decoder or vision_encoder_decoder, right?
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I was trying self.__name__ on this line, and it seems like it isn't defined in some cases -- e.g. in tests/models/vision_encoder_decoder/test_modeling_tf_vision_encoder_decoder.py::TFViT2GPT2EncoderDecoderModelTest::test_encoder_decoder_model, it throws *** AttributeError: 'TFVisionEncoderDecoderModel' object has no attribute '__name__'
str(self) here includes the full import path for the object, like you wrote, which contains the class name -- '<transformers.models.vision_encoder_decoder.modeling_tf_vision_encoder_decoder.TFVisionEncoderDecoderModel object at 0x7fc7783b8a60>'
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Maybe we can update in the future, but since it is working for now I'm going with it :D
| if use_cache: | ||
| past_key_values = decoder_outputs[1] | ||
| # The starting index of the remaining elements in `decoder_outputs` | ||
| start_index = sum([1 if x is not None else 0 for x in (loss, logits, past_key_values)]) |
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Thanks for the improvement / cleanup!
| decoder_attention_mask = decoder_attention_mask[:, :-1] | ||
| encoder_model, decoder_model = self.get_encoder_decoder_model(config, decoder_config) | ||
| enc_dec_model = EncoderDecoderModel(encoder=encoder_model, decoder=decoder_model) | ||
| enc_dec_model.config.output_attentions = True # model config -> won't work |
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@ydshieh rebased with main and reran tests -- all working 👍 |
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What does this PR do?
Fixes #18071
Modifies
unpack_inputsto ignore the config file for(...)EncoderDecodermodels, mimicking the behavior in PT. If we don't ignore it, then unset options will get set with the config's default (Falsefor most of them), causing the inner models to ignore their own config files.EncoderDecodermodels. I then noticed that other(...)EncoderFecodertests have copy/pasted their ownEncoderDecoderMixin, so I've left the other classes for a follow-up PR with the following question: should a commonEncoderDecoderMixinbe defined and shared across(...)EncoderDecodertests, or should I add a similar test to all other classes individually?