transformers

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System Info

• transformers version: 4.43.3
• Platform: Linux-5.15.153.1-microsoft-standard-WSL2-x86_64-with-glibc2.35
• Python version: 3.10.12
• Huggingface_hub version: 0.23.2
• Safetensors version: 0.4.3
• Accelerate version: 0.30.1
• Accelerate config: not found
• PyTorch version (GPU?): 2.3.1+cu121 (True)
• Tensorflow version (GPU?): not installed (NA)
• Flax version (CPU?/GPU?/TPU?): not installed (NA)
• Jax version: not installed
• JaxLib version: not installed
• Using distributed or parallel set-up in script?: no
• Using GPU in script?: yes
• GPU type: NVIDIA GeForce RTX 4090 Laptop GPU

Who can help?

@sanchit-gandhi @kamilakesbi

Information

• [ ] The official example scripts
• [X] My own modified scripts

Tasks

• [ ] An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
• [X] My own task or dataset (give details below)

Reproduction

In generating short form output (<30 sec):

# inputs is from the processor
gen_kwargs = {
            "max_new_tokens": 400,
            "num_beams": 5,
            "temperature": None,
            "return_timestamps": False,
            "return_dict_in_generate": True,
            "num_return_sequences": 1,
            "output_scores": True,
            "language": "english"
        }
pred_ids = self.model.generate(inputs, **gen_kwargs)
print(pred_ids.__class__)
print(dict((k,type(v)) for k, v in vars(pred_ids).items()))

Expected behavior

GenerateBeamEncoderDecoderOutput seems to lose some fields in a recent version. (Maybe other output forms are also affected, haven't checked.)

Bisecting transformers versions, in 4.42.4 the output looked like:

<class 'transformers.generation.utils.GenerateBeamEncoderDecoderOutput'> {'sequences': <class 'torch.Tensor'>, 'sequences_scores': <class 'torch.Tensor'>, 'scores': <class 'tuple'>, 'logits': <class 'NoneType'>, 'beam_indices': <class 'torch.Tensor'>, 'encoder_attentions': <class 'NoneType'>, 'encoder_hidden_states': <class 'NoneType'>, 'decoder_attentions': <class 'NoneType'>, 'cross_attentions': <class 'NoneType'>, 'decoder_hidden_states': <class 'NoneType'>, 'past_key_values': <class 'tuple'>}

In 4.43.0 and after sequences_scores and beam_indices became None:

<class 'transformers.generation.utils.GenerateBeamEncoderDecoderOutput'> {'sequences': <class 'torch.Tensor'>, 'sequences_scores': <class 'NoneType'>, 'scores': <class 'tuple'>, 'logits': <class 'NoneType'>, 'beam_indices': <class 'NoneType'>, 'encoder_attentions': <class 'NoneType'>, 'encoder_hidden_states': <class 'NoneType'>, 'decoder_attentions': <class 'NoneType'>, 'cross_attentions': <class 'NoneType'>, 'decoder_hidden_states': <class 'NoneType'>, 'past_key_values': <class 'tuple'>}

It looks like these get removed in postprocessing, potential culprit in _stack_split_outputs at https://github.com/huggingface/transformers/blob/9451a385261b30e7319a2c93285ab76161e8c003/src/transformers/models/whisper/generation_whisper.py#L946

Which looks like it changed in https://github.com/huggingface/transformers/pull/30984.

Hacking in if key in ["sequences", "beam_indices", "sequences_scores"]:, for example, fixes it, although I'm not sure what's intended to be handled as tensors vs. tuples, so will defer as to the best way to fix.