FYI HuggingFace update (Transformers v4.46.3) appears to have made your default baseline Encoder Decoder Transformer demo non-functional ( https://github.com/frankaging/ReCOGS/blob/1b6eca8ff4dca5fd2fb284a7d470998af5083beb/README.md?plain=1#L75 ) (workaround: `pip install transformers==v4.45.2` first)

[willy-b]

Hey just FYI, a HuggingFace update (seeing this on Transformers v4.46.3) appears to have made your default baseline Encoder Decoder Transformer demo non-functional (though pip install transformers==v4.45.2 is enough to work around for now if one is on a more recent affected version like v4.46.3).

That is, if one does a clean clone and runs the recommended command in

ReCOGS/README.md

Line 75 in 1b6eca8

python run_cogs.py \

,

We only have a single training script `run_cogs.py`. You can use it to reproduce our Transformers result. Here is one example,

```bash
python run_cogs.py \
--model_name ende_transformer \
--gpu 1 \
--train_batch_size 128 \
--eval_batch_size 128 \
--lr 0.0001 \
--data_path ./cogs \
--output_dir ./results_cogs \
--lfs cogs \
--do_train \
--do_test \
--do_gen \
--max_seq_len 512 \
--output_json \
--epochs 300 \
--seeds "42;66;77;88;99"

it will currently fail after finishing training when it attempts to generate from the model, with:

Traceback (most recent call last):
  File "/content/ReCOGS/run_cogs.py", line 300, in <module>
    outputs = trainer.model.generate(
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context
    return func(*args, **kwargs)
  File "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py", line 2215, in generate
    result = self._sample(
  File "/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py", line 3199, in _sample
    model_inputs = self.prepare_inputs_for_generation(input_ids, **model_kwargs)
  File "/content/ReCOGS/model/encoder_decoder_hf.py", line 867, in prepare_inputs_for_generation
    "past_key_values": decoder_inputs["past_key_values"],
KeyError: 'past_key_values'

An example notebook showing this new behavior (in November on Google Colab I did not have this issue, which can be worked around by downgrading HF Transformers) is available at:
https://colab.research.google.com/drive/1pv4tqu4XunBMwyfPF43T8omkUhN3pkYB?usp=sharing

It can be worked around by reverting to an old version of HuggingFace Transformers v4.45.2,
for example:

!pip install transformers==v4.45.2 

is enough to avoid this.

I am trying to write a paper and am using the script as a baseline to compare a different model to and to predict the specific errors made by the baseline Transformer you provide based on an analysis of a Transformer-compatible rule based model.
This does not break my model (which does not depend on this or HuggingFace, just uses the ReCOGS dataset to show it can be done by a Transformer compatible model) but thought I would let you know as I think the baseline is extremely useful for comparison and studying Transformer behavior and people may want to reproduce the results of your excellent paper, https://arxiv.org/abs/2303.13716 . Not everyone may think to run pip install transformers==v4.45.2 to get around this, and the default version of Transformers on Google Colab will now break your script.

Thanks

[willy-b]

Updated issue description as one sentence suggested I had not yet confirmed downgrading HF Transformers to v4.45.2 was a workaround (it was confirmed while writing the issue). Thanks.