The number of grammar rules (94) is inconsistent with the pre-trained model (97)

[lzw-pku]

I find that the number of the grammar rules is 94 when I follow the instructions to preprocess the data (with the hyper-parameter fs=2). But the size of rule_embedding in the pre-trained model is 97.

Traceback (most recent call last):
File "run.py", line 104, in
main()
File "run.py", line 83, in main
infer.main(infer_config)
File "/home/yuhao/zhenwen/repair_model/gap-text2sql-main/rat-sql-gap/seq2struct/commands/infer.py", line 239, in main
model = inferer.load_model(args.logdir, args.step)
File "/home/yuhao/zhenwen/repair_model/gap-text2sql-main/rat-sql-gap/seq2struct/commands/infer.py", line 48, in load_model
last_step = saver.restore(logdir, step=step, map_location=self.device, item_keys=["model"])
File "/home/yuhao/zhenwen/repair_model/gap-text2sql-main/rat-sql-gap/seq2struct/utils/saver.py", line 122, in restore
items2restore, model_dir, map_location, step)
File "/home/yuhao/zhenwen/repair_model/gap-text2sql-main/rat-sql-gap/seq2struct/utils/saver.py", line 40, in load_checkpoint
item_dict[item_name].load_state_dict(checkpoint[item_name])
File "/home/yuhao/.conda/envs/zhenwen/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1407, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for EncDecModel:
Unexpected key(s) in state_dict: "decoder.state_update._input_dropout_mask", "decoder.state_update._h_dropout_mask".
size mismatch for decoder.rule_logits.2.weight: copying a param with shape torch.Size([97, 128]) from checkpoint, the shape in current model is torch.Size([94, 128]).
size mismatch for decoder.rule_logits.2.bias: copying a param with shape torch.Size([97]) from checkpoint, the shape in current model is torch.Size([94]).
size mismatch for decoder.rule_embedding.weight: copying a param with shape torch.Size([97, 128]) from checkpoint, the shape in current model is torch.Size([94, 128])

[fduzhuruisi]

Can you solve this problem? I had the same problem like yours:

Traceback (most recent call last):
File "run.py", line 104, in
main()
File "run.py", line 66, in main
train.main(train_config)
File "/home/zrs/gap-text2sql/rat-sql-gap/seq2struct/commands/train.py", line 270, in main
trainer.train(config, modeldir=args.logdir)
File "/home/zrs/gap-text2sql/rat-sql-gap/seq2struct/commands/train.py", line 135, in train
last_step = saver.restore(modeldir, map_location=self.device)
File "/home/zrs/gap-text2sql/rat-sql-gap/seq2struct/utils/saver.py", line 122, in restore
items2restore, model_dir, map_location, step)
File "/home/zrs/gap-text2sql/rat-sql-gap/seq2struct/utils/saver.py", line 40, in load_checkpoint
item_dict[item_name].load_state_dict(checkpoint[item_name], False)
File "/home/zrs/anaconda3/envs/gap-text2sql/lib/python3.7/site-packages/torch/nn/modules/module.py", line 847, in load_state_dict
self.class.name, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for EncDecModel:
size mismatch for encoder.question_encoder.0.embedding.weight: copying a param with shape torch.Size([1580, 300]) from checkpoint, the shape in current model is torch.Size([164, 300]).
size mismatch for encoder.column_encoder.0.embedding.weight: copying a param with shape torch.Size([1580, 300]) from checkpoint, the shape in current model is torch.Size([164, 300]).
size mismatch for encoder.table_encoder.0.embedding.weight: copying a param with shape torch.Size([1580, 300]) from checkpoint, the shape in current model is torch.Size([164, 300]).
size mismatch for decoder.rule_logits.2.weight: copying a param with shape torch.Size([97, 128]) from checkpoint, the shape in current model is torch.Size([75, 128]).
size mismatch for decoder.rule_logits.2.bias: copying a param with shape torch.Size([97]) from checkpoint, the shape in current model is torch.Size([75]).
size mismatch for decoder.rule_embedding.weight: copying a param with shape torch.Size([97, 128]) from checkpoint, the shape in current model is torch.Size([75, 128]).
size mismatch for decoder.node_type_embedding.weight: copying a param with shape torch.Size([55, 64]) from checkpoint, the shape in current model is torch.Size([49, 64]).

Looking forward to the reply.