/Python/Keras functional api embedding layer

Keras functional api embedding layer

max_seq_length=100 #i.e., sentence has a max of 100 words 
word_weight_matrix = ... #this has a shape of 9825, 300, i.e., the vocabulary has 9825 words and each is a 300 dimension vector 
deep_inputs = Input(shape=(max_seq_length,))
embedding = Embedding(9826, 300, input_length=max_seq_length,
                      weights=[word_weight_matrix], trainable=False)(deep_inputs) # line A
hidden = Dense(targets, activation="softmax")(embedding)
model = Model(inputs=deep_inputs, outputs=hidden)

Source: stackoverflow.com

Similar codes

0 vote206 views1 answer
Django date grater
Python Django
1 vote203 views2 answers
Git help
Python
2 votes269 views4 answers
Show pandas all data
Python
0 vote179 views2 answers
Remove unicode from string python
Python
6 votes184 views5 answers
Python weekday
Python
4 votes178 views4 answers
How to create a calculator in python
Python
0 vote212 views1 answer
How to convert csv columns to text python
Python
0 vote213 views1 answer
Solidity compiler for python
Python
8 votes185 views3 answers
Python datetime to unix timestamp
Python
0 vote217 views2 answers
Createview django
Python Django