Test problem

[CrystalWLH]

I have trained the model using given command, when I use the given command of testing, I have encountered the following problem. AttributeError: 'collections.OrderedDict' object has no attribute 'embeddings'

[kedz]

Can you give me the whole error message and the exact command you are running? Thanks!

On Mon, Apr 29, 2019, 11:21 PM CrystalWLH [email protected] wrote:

I have trained the model using given command, when I use the given command of testing, I have encountered the following problem. AttributeError: 'collections.OrderedDict' object has no attribute 'embeddings'

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[CrystalWLH]

My training command is python script_bin/train_model.py \ --trainer --train-inputs 'data/inputs/train/' \ --train-labels 'data/labels/train/' \ --valid-inputs 'data/inputs/valid/' \ --valid-labels 'data/labels/valid/' \ --valid-refs 'data/human/valid/' \ --weight \ --epochs 50 \ --gpu 3 \ --model 'result/model' \ --results 'result/valid_score' \ --seed 12345678 \ --emb --embedding-size 200 \ --enc cnn \ --ext s2s --bidirectional My testing command is python script_bin/eval_model.py \ --inputs 'data/inputs/test/' \ --refs 'data/human/test/' \ --model 'result/model.pth' \ --results 'result/exp1/test_score' \ --summary-length 100 \ --batch-size 32

The error message is Loading model...Traceback (most recent call last): File "script_bin/eval_model.py", line 92, in <module> main() File "script_bin/eval_model.py", line 41, in main vocab = model.embeddings.vocab AttributeError: 'collections.OrderedDict' object has no attribute 'embeddings'

[kedz]

Thanks! Can you run the following commands and send me the output:

import torch
model = torch.load("result/model.pth", map_location=lambda storage, loc: storage)
print(model)

[markusdr]

The error comes because newer versions of ignite save model checkpoints as state_dict by default (see here).

To fix, change the nnsum code here from:

    checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func,
                                 require_empty=False, score_name=metric_name)

to

    checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func,
                                 require_empty=False, score_name=metric_name, 
                                 save_as_state_dict=False)

[tlifcen]

Hello, I used AMI dataset to test the code without GPU, and I met this problem:

INFO:root: Model parameter initialization finished.

INFO:ignite.engine.engine.Engine:Engine run starting with max_epochs=50.
INFO:ignite.engine.engine.Engine:Epoch[1] Complete. Time taken: 00:00:00
ERROR:ignite.engine.engine.Engine:Engine run is terminating due to exception: Loss must have at least one example before it can be computed.
Traceback (most recent call last):
  File "script_bin/train_model.py", line 79, in <module>
    main()
  File "script_bin/train_model.py", line 76, in main
    results_path=args["trainer"]["results"])
  File "/home/constant/anaconda3/lib/python3.7/site-packages/nnsum-1.0-py3.7.egg/nnsum/trainer/labels_mle_trainer.py", line 164, in labels_mle_trainer
  File "/home/constant/anaconda3/lib/python3.7/site-packages/ignite/engine/engine.py", line 359, in run
    self._handle_exception(e)
  File "/home/constant/anaconda3/lib/python3.7/site-packages/ignite/engine/engine.py", line 324, in _handle_exception
    raise e
  File "/home/constant/anaconda3/lib/python3.7/site-packages/ignite/engine/engine.py", line 350, in run
    self._fire_event(Events.EPOCH_COMPLETED)
  File "/home/constant/anaconda3/lib/python3.7/site-packages/ignite/engine/engine.py", line 259, in _fire_event
    func(self, *(event_args + args), **kwargs)
  File "/home/constant/anaconda3/lib/python3.7/site-packages/ignite/metrics/metric.py", line 68, in completed
    result = self.compute()
  File "/home/constant/anaconda3/lib/python3.7/site-packages/nnsum-1.0-py3.7.egg/nnsum/metrics/loss.py", line 21, in compute
ignite.exceptions.NotComputableError: Loss must have at least one example before it can be computed

Is it the problem caused by not using GPU? Thanks for your help!

[tlifcen]

The error comes because newer versions of ignite save model checkpoints as state_dict by default (see here).

To fix, change the nnsum code here from:

    checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func,
                                 require_empty=False, score_name=metric_name)

to

    checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func,
                                 require_empty=False, score_name=metric_name, 
                                 save_as_state_dict=False)

I changed the code as your suggestion, but the code does not work, either. There is still the following error: AttributeError: 'collections.OrderedDict' object has no attribute 'embeddings' Do you have other methods to solve the problem? Thanks for your reply!

[kedz]

Can you give me the versions of python, torch, and ignite that you are using, along with the commandline arguments you are using? I can't reproduce this error.

Thanks! Chris

On Tue, Sep 3, 2019 at 1:06 AM tlifcen [email protected] wrote:

The error comes because newer versions of ignite save model checkpoints as state_dict by default (see here https://github.com/pytorch/ignite/commit/79e5233438d46ebfd205b7942866ccdcd990efda#diff-18cd1a3c06de70b0e34b8fcf32940b30 ).

To fix, change the nnsum code here https://github.com/kedz/nnsum/blob/master/nnsum/trainer/labels_mle_trainer.py#L244 from:

checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func,
                             require_empty=False, score_name=metric_name)

to

checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func,
                             require_empty=False, score_name=metric_name,
                             save_as_state_dict=False)

I changed the code as your suggestion, but the code does not work, either. There is still the following error: AttributeError: 'collections.OrderedDict' object has no attribute 'embeddings' Do you have other methods to solve the problem? Thanks for your reply!

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-- Chris Kedzie PhD Student, Dept. of Computer Science Columbia University email: [email protected] web: www.cs.columbia.edu/~kedzie

[tlifcen]

Can you give me the versions of python, torch, and ignite that you are using, along with the commandline arguments you are using? I can't reproduce this error. Thanks! Chris … On Tue, Sep 3, 2019 at 1:06 AM tlifcen @.***> wrote: The error comes because newer versions of ignite save model checkpoints as state_dict by default (see here <pytorch/ignite@79e5233#diff-18cd1a3c06de70b0e34b8fcf32940b30> ). To fix, change the nnsum code here https://github.com/kedz/nnsum/blob/master/nnsum/trainer/labels_mle_trainer.py#L244 from: checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func, require_empty=False, score_name=metric_name) to checkpoint = ModelCheckpoint(dirname, prefix, score_function=_score_func, require_empty=False, score_name=metric_name, save_as_state_dict=False) I changed the code as your suggestion, but the code does not work, either. There is still the following error: AttributeError: 'collections.OrderedDict' object has no attribute 'embeddings' Do you have other methods to solve the problem? Thanks for your reply! — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#7?email_source=notifications&email_token=ABAZOM4PUXUSAJT4QUFUQH3QHXWDNA5CNFSM4HJIHGK2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD5XAVXQ#issuecomment-527305438>, or mute the thread https://github.com/notifications/unsubscribe-auth/ABAZOMZKVFULGHZTOLS3NPLQHXWDNANCNFSM4HJIHGKQ . -- Chris Kedzie PhD Student, Dept. of Computer Science Columbia University email: [email protected] web: www.cs.columbia.edu/~kedzie

I used python3.6.9, torch0.4.1 and ignite0.2.0. And the environment is Ubuntu 16.04 LTS. I used the following command to test the code:

python script_bin/eval_model.py \
  --inputs /home/constant/data/Constant-TL/dataset/summarization/nnsum/reddit/reddit/inputs/test \
  --refs /home/constant/data/Constant-TL/dataset/summarization/nnsum/reddit/reddit/human-extracts/test \
  --model ../dataset/summarization/nnsum/reddit_model_95_rouge-2=0.65826.pth \
  --results ../dataset/summarization/nnsum/reddit/test_score \
  --summary-length 100 

Thanks for your reply!