Hi,
We are using your brilliant project for working on the Japanese BERT model with Sentence Piece.
https://github.com/yoheikikuta/bert-japanese
We are trying to use the convert to to convert below TF BERT model to PyTorch.
https://drive.google.com/drive/folders/1Zsm9DD40lrUVu6iAnIuTH2ODIkh-WM-O
But we see error logs:
Traceback (most recent call last):
File "/Users/weicheng.zhu/PycharmProjects/pytorch-pretrained-BERT-master/pytorch_pretrained_bert/convert_tf_checkpoint_to_pytorch.py", line 66, in
args.pytorch_dump_path)
File "/Users/weicheng.zhu/PycharmProjects/pytorch-pretrained-BERT-master/pytorch_pretrained_bert/convert_tf_checkpoint_to_pytorch.py", line 37, in convert_tf_checkpoint_to_pytorch
load_tf_weights_in_bert(model, tf_checkpoint_path)
File "/Users/weicheng.zhu/PycharmProjects/pytorch-pretrained-BERT-master/pytorch_pretrained_bert/modeling.py", line 95, in load_tf_weights_in_bert
pointer = getattr(pointer, l[0])
File "/usr/local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 535, in __getattr__
type(self).__name__, name))
AttributeError: 'BertForPreTraining' object has no attribute 'global_step'
Could you kindly help with how we can avoid this?
Thank you so much!
I resolved this issue by adding the global_step to the skipping list. I think global_step is not required for using pretrained model. Please correct me if I am wrong.
Is Pytorch requires a TF check point converted? am finding hard to load the checkpoint I generated.BTW is it safe to convert TF checkpoint ?
I resolved this issue by adding the global_step to the skipping list. I think global_step is not required for using pretrained model. Please correct me if I am wrong.
can you explain me what is skipping list?
In the file modeling.py add it to the list at:
if any(n in ["adam_v", "adam_m"] for n in name):
Is it possible to load Tensorflow checkpoint using pytorch and do fine tunning?
I can load pytorch_model.bin and finding hard to load my TF checkpoint.Documentation says it can load a archive with bert_config.json and model.chkpt but I have bert_model_ckpt.data-0000-of-00001 in my TF checkpoint folder so am confused. Is there specific example how to do this?


There is a conversion script to convert a tf checkpoint to pytorch: https://github.com/huggingface/pytorch-pretrained-BERT/blob/master/pytorch_pretrained_bert/convert_tf_checkpoint_to_pytorch.py
In the file
modeling.pyadd it to the list at:
if any(n in ["adam_v", "adam_m"] for n in name):
added global_step in skipping list but still getting same issue.

@naga-dsalgo Is it fixed? I too added "global_step" to the list. But still get the error
Yes it is fixed for me ... I edited installed version not the downloaded
git version ..
On Tue, Apr 2, 2019 at 4:37 AM Shivam Akhauri notifications@github.com
wrote:
@naga-dsalgo https://github.com/naga-dsalgo Is it fixed? I too added
"global_step" to the list. But still get the error—
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Most helpful comment
I resolved this issue by adding the global_step to the skipping list. I think global_step is not required for using pretrained model. Please correct me if I am wrong.