xiaohythu

And I just follow your training command: scripts/train/mac_flatqa.sh --data_dir $DATA/sqoop-variety_1-repeats_30000 --checkpoint_path model.pt\ --num_iterations 100000 and change only the feature dimension to [1024,14,14 ]

> How long have you been training the model? As my running command shows, num_iterations is 100000

> How long have you been training the model? The training procedure lasts about 10 hours

> OK, I will run this experiment later today myself. Thank you for your reply, waiting for your results

> I could not reproduce your issue. I have just trained 10 models, and they all worked fine. Can you please try running the experiment many times and tell me...

Still，I obtain the lower performance as I stated in the question. Maybe I need some detailed information about your training. Here my setup is CUDA10.1 and torch 1.3.1

Before running your MAC model，I utilize Resnet101 to extract features from Clevr dataset and convert them to . h5 file. Also I preprocess the questions. Is my way correct？

> I could not reproduce your issue. I have just trained 10 models, and they all worked fine. Can you please try running the experiment many times and tell me...

I have trained the MAC model in clevr dataset for more than 10 times. All the results are similar with what I mentioned in my question. I believe that you...

As I mentioned in this issue，An error occured: File "/home/xhy/systematic-generalization-sqoop-master/vr/programs.py", line 137, in get_num_inputs return self._vocab['program_token_arity'][f] KeyError: 'program_token_arity'. I guess the vocab.json of clevr is different from your sqoop dataset....