TypeError: forward() got an unexpected keyword argument 'heterograph'

[FightingEveryDay0]

When testing, I encountered the following error and I suspect that the generate() function is missing. How can I resolve this?
Thank you very much!

LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0,1,2,3]
Testing: 0it [00:00, ?it/s]Traceback (most recent call last):
  File "hgsum.py", line 646, in <module>
    test(args)
  File "hgsum.py", line 558, in test
    trainer.test(model, test_dataloader)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 904, in test
    return self._call_and_handle_interrupt(self._test_impl, model, dataloaders, ckpt_path, verbose, datamodule)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 682, in _call_and_handle_interrupt
    return trainer_fn(*args, **kwargs)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 947, in _test_impl
    results = self._run(model, ckpt_path=self.tested_ckpt_path)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1193, in _run
    self._dispatch()
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1268, in _dispatch
    self.training_type_plugin.start_evaluating(self)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 206, in start_evaluating
    self._results = trainer.run_stage()
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1279, in run_stage
    return self._run_evaluate()
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/trainer/trainer.py", line 1327, in _run_evaluate
    eval_loop_results = self._evaluation_loop.run()
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/loops/base.py", line 145, in run
    self.advance(*args, **kwargs)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 109, in advance
    dl_outputs = self.epoch_loop.run(dataloader, dataloader_idx, dl_max_batches, self.num_dataloaders)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/loops/base.py", line 145, in run
    self.advance(*args, **kwargs)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 123, in advance
    output = self._evaluation_step(batch, batch_idx, dataloader_idx)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 211, in _evaluation_step
    output = self.trainer.accelerator.test_step(step_kwargs)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/accelerators/accelerator.py", line 244, in test_step
    return self.training_type_plugin.test_step(*step_kwargs.values())
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/pytorch_lightning/plugins/training_type/training_type_plugin.py", line 222, in test_step
    return self.model.test_step(*args, **kwargs)
  File "hgsum.py", line 438, in test_step
    return self.validation_step(batch, batch_idx)
  File "hgsum.py", line 364, in validation_step
    result_batch = self.compute_rouge_batch(input_ids_source, tgt, heterograph_source, words_positions_source,
  File "hgsum.py", line 251, in compute_rouge_batch
    generated_ids = self.model.generate(
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/transformers/generation_utils.py", line 1181, in generate
    model_kwargs = self._prepare_encoder_decoder_kwargs_for_generation(
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/transformers/generation_utils.py", line 525, in _prepare_encoder_decoder_kwargs_for_generation
    model_kwargs["encoder_outputs"]: ModelOutput = encoder(**encoder_kwargs)
  File "/home/wangyiting/anaconda3/envs/hgsum/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
    return forward_call(*args, **kwargs)
TypeError: forward() got an unexpected keyword argument 'heterograph'
Testing:   0%|          | 0/50 [00:04<?, ?it/s]

[liude12]

Hello, I also encountered the following problems in the training stage. Did you run through the training stage?

[liude12]

hello,I also have the same problem，Did you solve it?

[robot-2233]

wait,you guys fixed the 'utils' problem ?

I can't find that folder,how can I solve it?

[oaimli]

wait,you guys fixed the 'utils' problem ? I can't find that folder,how can I solve it?

Sorry about the confusion, utils have been uploaded.

[oaimli]

Sorry, I haven't encountered these problems. Please try with the same requirements.

[liude12]

I use the same requirements, but still encounter these problems , I suspect the problem is the data, can you provide some data samples.
raceback (most recent call last): | 0/30 [00:00<?, ?it/s]
File "hgsum.py", line 573, in
train(args)
File "hgsum.py", line 456, in train
trainer.fit(model, train_dataloader, valid_dataloader)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 697, in fit
self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 650, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 735, in _fit_impl
results = self._run(model, ckpt_path=self.ckpt_path)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1166, in _run
results = self._run_stage()
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1252, in _run_stage
return self._run_train()
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1283, in _run_train
self.fit_loop.run()
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
self.advance(*args, **kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/fit_loop.py", line 271, in advance
self._outputs = self.epoch_loop.run(self._data_fetcher)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 201, in run
self.on_advance_end()
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 241, in on_advance_end
self._run_validation()
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 299, in _run_validation
self.val_loop.run()
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
self.advance(*args, **kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 155, in advance
dl_outputs = self.epoch_loop.run(self._data_fetcher, dl_max_batches, kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
self.advance(*args, **kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 143, in advance
output = self._evaluation_step(**kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 240, in _evaluation_step
output = self.trainer._call_strategy_hook(hook_name, *kwargs.values())
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1704, in _call_strategy_hook
output = fn(*args, **kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/strategies/strategy.py", line 370, in validation_step
return self.model.validation_step(*args, **kwargs)
File "hgsum.py", line 309, in validation_step
sents_positions_source, docs_positions_source, batch_idx)
File "hgsum.py", line 226, in compute_rouge_batch
docs_positions_source=docs_positions_source,
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/transformers/generation_utils.py", line 1340, in generate
inputs_tensor, model_kwargs, model_input_name
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/transformers/generation_utils.py", line 583, in _prepare_encoder_decoder_kwargs_for_generation
model_kwargs["encoder_outputs"]: ModelOutput = encoder(**encoder_kwargs)
File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
TypeError: forward() got an unexpected keyword argument 'heterograph'
Epoch 4: 100%|██████████| 30/30 [00:30<00:00, 1.00s/it, loss=3.8, v_num=3]

[robot-2233]

Sorry, I haven't encountered these problems. Please try with the same requirements.

Can you post the address of the download data, I can't find it
tks a lot

[yangjenhao]

@FightingEveryDay0 @liude12 @robot-2233
Hello, I also have the same problem.

TypeError: forward() got an unexpected keyword argument 'heterograph'

Did you solve it?

[robot-2233]

No, actually I gave up :(

[ashleydDeng]

您好，我在训练阶段也遇到了以下问题。训练阶段你跑完了吗？

I use the same requirements, but still encounter these problems , I suspect the problem is the data, can you provide some data samples. raceback (most recent call last): | 0/30 [00:00<?, ?it/s] File "hgsum.py", line 573, in train(args) File "hgsum.py", line 456, in train trainer.fit(model, train_dataloader, valid_dataloader) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 697, in fit self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 650, in _call_and_handle_interrupt return trainer_fn(*args, **kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 735, in _fit_impl results = self._run(model, ckpt_path=self.ckpt_path) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1166, in _run results = self._run_stage() File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1252, in _run_stage return self._run_train() File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1283, in _run_train self.fit_loop.run() File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run self.advance(*args, **kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/fit_loop.py", line 271, in advance self._outputs = self.epoch_loop.run(self._data_fetcher) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 201, in run self.on_advance_end() File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 241, in on_advance_end self._run_validation() File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 299, in _run_validation self.val_loop.run() File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run self.advance(*args, **kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 155, in advance dl_outputs = self.epoch_loop.run(self._data_fetcher, dl_max_batches, kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run self.advance(*args, **kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 143, in advance output = self._evaluation_step(**kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 240, in _evaluation_step output = self.trainer._call_strategy_hook(hook_name, *kwargs.values()) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1704, in _call_strategy_hook output = fn(*args, **kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/pytorch_lightning/strategies/strategy.py", line 370, in validation_step return self.model.validation_step(*args, **kwargs) File "hgsum.py", line 309, in validation_step sents_positions_source, docs_positions_source, batch_idx) File "hgsum.py", line 226, in compute_rouge_batch docs_positions_source=docs_positions_source, File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context return func(*args, **kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/transformers/generation_utils.py", line 1340, in generate inputs_tensor, model_kwargs, model_input_name File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/transformers/generation_utils.py", line 583, in _prepare_encoder_decoder_kwargs_for_generation model_kwargs["encoder_outputs"]: ModelOutput = encoder(**encoder_kwargs) File "/home/tankaiwen/anaconda3/envs/hgsum12/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl return forward_call(*input, **kwargs) TypeError: forward() got an unexpected keyword argument 'heterograph' Epoch 4: 100%|██████████| 30/30 [00:30<00:00, 1.00s/it, loss=3.8, v_num=3]

Have you successfully reproduced it? I am a beginner and am very interested in this field. May I ask you for the details of the reproduction? Thank you!