"KeyError: 'program_parsed'" when running the program

[dlshu]

Hi. I tried to test the pretrained model using the test data from CLEVR dataset but had a error 'KeyError: 'program_parsed''. The command I typed in is as follows.

jac-crun 0 scripts/main.py --mode run-experiment --task CLEVR --model VCML --experiment synonym_generalization --log_dir ../data/log --data_dir ../data/ --pretrained --in_epoch test

and the error message shown is as follows.

0:00:52.63 | => epoch 0 |
0:00:52.85 | -----> Testing Traceback (most recent call last):
File "scripts/main.py", line 44, in main() File "scripts/main.py", line 34, in main run_experiment.run(args) File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/scripts/run_experiment.py", line 181, in run processes[0]._target(*processes[0]._args) File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/scripts/run_experiment.py", line 151, in ready_go train(coach, args) File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/scripts/utils/train.py", line 223, in train run_epoch(coach, args, coach.epoch) File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/scripts/utils/train.py", line 192, in run_epoch True, False File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/scripts/utils/train.py", line 142, in any_epoch inner() File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/scripts/utils/train.py", line 128, in inner loss, outputs = run_batch(data, model, args) File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/scripts/utils/train.py", line 82, in run_batch losses, outputs, debugs, objects = model(data) File "/home/dule/anaconda3/envs/VCML/lib/python3.6/site-packages/torch/nn/modules/module.py", line 547, in call result = self.forward(*input, **kwargs) File "/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/models/model/vcml_model.py", line 87, in forward program = data['program_parsed'] KeyError: 'program_parsed'

/home/dule/Desktop/NN/AAAI_21/nuero-symbolic_ai/VCML/models/model/vcml_model.py(87)forward() 85 program_encoded = data['program_encoded'] 86 else: ---> 87 program = data['program_parsed'] 88 program_encoded = data['program_parsed_encoded'] 89

ipdb>

Any suggestions how to fix this issue? Thank you very much!

[anette123]

Getting the same error. If I modify 'inner()' function in train.py when 'is_train=False' to estimate 'program parsed' and 'program_parsed_encoded' just like when 'is_train=True' , the code will proceed further, but will fail as the downloaded parser cannot parse test questions. That is, the first 10 questions from the test set:

# Out[93]: TEST QUESTIONS
# ['Is small a synonym of small?',
#  'Is sphere a synonym of sphere?',
#  'Is shiny a synonym of shiny?',
#  'Is sphere a synonym of shiny?',
#  'Is sphere a synonym of small?',
#  'Is shiny a synonym of shiny?',
#  'Is shiny a synonym of sphere?',
#  'Is small a synonym of shiny?',
#  'Is shiny a synonym of small?',
#  'Is small a synonym of small?']

And the parser will process them in the following way (showing the first two):

# Out[96]:
# [[{'operation': '<END>', 'argument': 'small'},
#   {'operation': '<END>', 'argument': 'small'},
#   {'operation': '<END>', 'argument': '<END>'},
#   {'operation': '<END>', 'argument': '<END>'},
#   {'operation': '<END>', 'argument': '<END>'}],
#  [{'operation': '<END>', 'argument': 'sphere'},
#   {'operation': '<END>', 'argument': 'sphere'},
#   {'operation': '<END>', 'argument': '<END>'},
#   {'operation': '<END>', 'argument': '<END>'},
#   {'operation': '<END>', 'argument': '<END>'}],

Could you please have a look at this? I suspect the parser provided cannot process meta concept words like 'synonym'..

[anette123]

Update to my previous comment: have been testing the parser separately, and while in parser.tools.operation.records it contains 'synonym', it is always predicting '10' for operation, which is '<END>' for the test questions. Below listing parser operatons.

['select_concept',
 'synonym',
 'isinstanceof',
 'samekind',
 'select_object',
 'filter',
 'exist',
 'classify',
 '<NULL>',
 '<START>',
 '<END>',
 '<UNK>']

[coldmanck]

Same issue here. @anette123 may I know if you have solved this problem?

[coldmanck]

I'd also like to call for the authors' attention to this issue @vacancy @Glaciohound