/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

2 votes151 views1 answer
Python copy a 2D list
Python
2 votes165 views1 answer
Tk.destroy arguments
Python
0 vote166 views1 answer
Quick way to find the factor of a number python
Python
11 votes168 views2 answers
How to import a module in python
Python
0 vote171 views1 answer
Python button graphics.py
Python
0 vote171 views1 answer
How to recover a list from string in python
Python
0 vote178 views1 answer
Selenium ways of finding
Python
-1 vote157 views1 answer
How to know if a string is valid file path python
Python
1 vote167 views1 answer
Python print how long it takes to run
Python
0 vote179 views1 answer
Python with braces
Python