How to extract the encoded data of feed & forward layer in tfbertmodel?
env：tf2.2

model：TFBertModel.from_pretrained('hfl/chinese-bert-wwm-ext')

i'm working on an information extraction project. First, I predict the “**subject**” through Bert CRF, then **tf. Gather ()** the coding layer of shared Bert and the location information corresponding to the “**subject**”, and then predict the “**object**“, but I can't extract the **feed & forward** layer of Bert now

I want to extract the output of the **feed & forward** layer of the Bert model as the shared coding layer, but I can't find the corresponding method. I want to obtain the output similar to the following:

# Tensor("Transformer-11-FeedForward-Add/add:0", shape=(None, None, 768), dtype=float32)

I tried through ”**model.trainable_weights[- 5]**”layer, but the extracted output is obviously not what I need, and I don't want to directly use "model (ids, masks, tokens) [0]", because Bert's last layer is processed by "layerNormal"

Hello, thanks for opening an issue! We try to keep the github issues for bugs/feature requests.
Could you ask your question on the [forum](https://discuss.huggingface.co) instead?

Thanks!

cc @Rocketknight1 <|||||>I asked questions where you said, but no one replied to me. I hope you can tell me the answer to this question. Thank you！
https://discuss.huggingface.co/t/how-to-extract-the-encoded-data-of-feed-forward-layer-in-tfbertmodel/9320<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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