Comments (3)
avivihadar
commented on May 21, 2024
Thank you again for this great work @wetherbeei, could you please advise how to extract the activations of the intermediate layers of BERT?
from patents-public-data.
wetherbeei
commented on May 21, 2024
from patents-public-data.
avivihadar
commented on May 21, 2024
Hi @robert-srebrovic, thanks for supporting this repo! my goal is to load the cls embeddings (including intermediate layers). So far I've attempted to use the bert-for-tf2 package. However, it seems like some of the layers defined here are missing from the target model when attempting to load it:
l_input_ids = keras.layers.Input(shape=(MAX_SEQ_LENGTH,), dtype='int32')
bert_params = bert.params_from_pretrained_ckpt(MODEL_DIR)
l_bert = bert.BertModelLayer.from_params(bert_params, name="bert")
output = l_bert(l_input_ids)
model_chk = keras.Model(inputs=l_input_ids, outputs=output)
model_chk.build(input_shape=(None, MAX_SEQ_LENGTH))
bert.load_bert_weights(l_bert, model_ckpt)
Specifically, the following weights are missing:
bert/pooler/dense/bias
bert/pooler/dense/kernel
cls/predictions/output_bias
cls/predictions/transform/LayerNorm/beta
cls/predictions/transform/LayerNorm/gamma
cls/predictions/transform/dense/bias
cls/predictions/transform/dense/kernel
cls/seq_relationship/output_bias
cls/seq_relationship/output_weights
Could you please advise what would be the best way to reintroduce the missing layers?
from patents-public-data.
Related Issues (20)
- BERT for Patents: unable to access hidden layers HOT 6
- embedding model is not found// Automated Patent Landscaping HOT 5
- Expiration date HOT 2
- BERT for Patents yields 1024 element array, but embedding_v1 is 64 element HOT 5
- ResourceExhaustedError while running Document_representation_from_BERT HOT 2
- Empty Tables in the Dataset
- Linking proteins and humangenes annotation preferred name to identifier HOT 9
- Converting Tensorflow Bert for Patent saved model to keras.
- How to download HOT 5
- BERT-Base
- context tokens
- Generating new Document Embeddings
- Sklearn 1.1.1 Issue HOT 1
- Dataset lacking cited_by data even though its available on the website. HOT 4
- claim_text_extraction.ipynb df = pd.read_csv('./data/20k_G_and_H_publication_numbers.csv') workaround
- Lots of Patents in the latest patent dataset are missing a description
- Missing embedding HOT 1
- lack of "vocab"
- Description and claims are missing for JP patents data.
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