a hybrid deep neural network for fake news detection based on CSI paper
Hello,
I decided to open a new issue since it's a different bug and error. While running the training code, I get the following error, would you please upload a requirement.txt for python packages that you have used? e.g., python version, PyTorch version, etc.
File "/tmp/ipykernel_2468582/2857088609.py", line 62, in experiment
File "/home/user/Fake news mitigation/venv37/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 821, in validate
return self._call_and_handle_interrupt(self._validate_impl, model, dataloaders, ckpt_path, verbose, datamodule)
File "/home/user/Fake news mitigation/venv37/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 685, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "/home/user/Fake news mitigation/venv37/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 864, in _validate_impl
results = self._run(model, ckpt_path=self.validated_ckpt_path)
File "/home/user/Fake news mitigation/venv37/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1128, in _run
verify_loop_configurations(self)
File "/home/user/Fake news mitigation/venv37/lib/python3.7/site-packages/pytorch_lightning/trainer/configuration_validator.py", line 40, in verify_loop_configurations
__verify_eval_loop_configuration(trainer, model, "val")
File "/home/user/Fake news mitigation/venv37/lib/python3.7/site-packages/pytorch_lightning/trainer/configuration_validator.py", line 170, in __verify_eval_loop_configuration
has_step = is_overridden(step_name, model)
File "/home/user/Fake news mitigation/venv37/lib/python3.7/site-packages/pytorch_lightning/utilities/model_helpers.py", line 47, in is_overridden
raise ValueError("Expected a parent")
ValueError: Expected a parent
I have found this https://stackoverflow.com/questions/69526806/pytorch-model-heplers-py-in-is-overridden-raise-valueerror-expected-a-paren but in your code, I see class CSIModel(pl.LightningModule), so it should be fine but it's not!
Hi there,
Could you please provide the processed dataset so that I can run your code?
Many thanks.
0%| | 0/4232 [00:00<?, ?it/s] --------------------------------------------------------------------------- FileNotFoundError Traceback (most recent call last) in 33 for event in tqdm(eid_train+eid_test): 34 event_str = str(event) ---> 35 tweets = json.load(open(os.path.join(path,event_str+'.json'),"r",encoding='utf-8')) 36 timestamps = [] 37 uid = [] FileNotFoundError: [Errno 2] No such file or directory: 'Data/Weibo/3566276356194468.json'
I can run your code，but I can't achieve 95.3% accuracy in the paper
Hello,
I am trying to run your code but I get this error:
`
TypeError Traceback (most recent call last)
Input In [44], in <cell line: 4>()
2 os.makedirs(save_path, exist_ok=True)
4 for eid in tqdm(events):
----> 5 xc, xs, y = get_event_features(eid)
6 pickle.dump(
7 {'x_capture': xc, 'x_score':xs, 'label': y},
8 open(save_path + eid + '.pkl', 'wb')
9 )
Input In [42], in get_event_features(eid)
49 print(eid)
50 print(doc)
---> 51 X_text += [doc_vectorizer.infer_vector(
52 # jieba.lcut(doc)
53 doc
54 ).reshape(1,-1)]
55 X_text = np.concatenate(X_text, axis=0)
57 # stack all
File ~/Research_direction/Fake news mitigation multimodal/venv38/lib/python3.8/site-packages/gensim/models/doc2vec.py:620, in Doc2Vec.infer_vector(self, doc_words, alpha, min_alpha, epochs)
592 """Infer a vector for given post-bulk training document.
593
594 Notes
(...)
617
618 """
619 if isinstance(doc_words, str): # a common mistake; fail with a nicer error
--> 620 raise TypeError("Parameter doc_words of infer_vector() must be a list of strings (not a single string).")
622 alpha = alpha or self.alpha
623 min_alpha = min_alpha or self.min_alpha
TypeError: Parameter doc_words of infer_vector() must be a list of strings (not a single string).
`
What should I do?
Thanks!
Could you please provide the data set you used at that time, thank you very much！
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