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Questions - bilstm

Input 0 of layer "bidirectional_2" is incompatible with the layer: expected ndim=3, found ndim=2

I am trying to classify text with bi-lstm but while I run model.predict on new dataset it is giving me this error: Input 0 of layer "bidirectional_2" is incompatible with the layer: expected...
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Rubiya shoukat

python

tensorflow

classification

sentiment-analysis

bilstm

Votes: 0

Answers: 1

Latest Answer

you should use Reshape layer after Bidirectional layer This might works: model = Sequential() model.add(Embedding(len(word_index) + 1, embed_size, weights=[embedding_matrix])) model.add(Bidirectional(...
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Arman Asgharpoor

Bert embedding layer raises 'ValueError: A target array with shape ' with BiLSTM in keras tensorflow

I've problems integrating Bert Embedding Layer in a BiLSTM model for text classification task. My dataset is in the form where each row has 2 columns: text and polarity text = string/tweet polarity = ...
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user18630856

tensorflow

keras

bert-language-model

word-embedding

bilstm

Votes: 0

Answers: 1

Latest Answer

The loss function you specify especially binary, mean, logarithms, and other than Adam are calculated on the shape as well, you may try to change the loss fn but the target to solve the issues is the ...
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Jirayu Kaewprateep

What does Tensor[batch_mask, ...] do?

I saw this line of code in an implementation of BiLSTM: batch_output = batch_output[batch_mask, ...] I assume this is some kind of "masking" operation, but found little information on Googl...
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aLonelySheep

python

deep-learning

pytorch

lstm

bilstm

Votes: 0

Answers: 2

Latest Answer

This statement masks the first dimension of batch_output with the indices contained by batch_mask. In practice, this means you are selecting some of the elements from the batch. Here is a practical ex...
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Ivan

How bert is a bidirectional?

Bert encoder takes the input and goes for the multi-head attention model. But how do they maintain sequence? Since current words don't take sequence of previous words. Besides, why is it bidirectional...
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kowser66

nlp

lstm

bert-language-model

language-model

bilstm

Votes: 0

Answers: 1

Latest Answer

It is bidirectional because it uses context from both sides of the current word (instead of e.g. using just the previous few words it uses the whole sequence). It depends on how much you want to go in...
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ewz93

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