OS Platform and Distribution (e.g., Linux Ubuntu 16.04): MacOS, 8GB RAM
TensorFlow/Keras version: 1.11/2.2.4
Python version: 3.6.7
Describe the problem
I have trained Entity Extraction model using Elmo embeddings (as described in elmo_example.py). Now I am trying to make prediction on new sentences. Elmo is taking lot of time to transform sentences into vectors.
Elmo is taking 4-5 sec to transform 15 sentence into vector. Average sentence length 15-20 words.
How can I make it faster, can I use GPU instead of using CPU for fast prediction?
Source code / logs
I have made some changes in ElmoTransformer class but it is giving me error, here is the code
Here is the error I am getting when cuda_device==0 and I am using GPU:
expected object of backend cpu but got backend cuda
It would be great if someone will help me. Thanks
System information
Describe the problem
I have trained Entity Extraction model using Elmo embeddings (as described in elmo_example.py). Now I am trying to make prediction on new sentences. Elmo is taking lot of time to transform sentences into vectors.
Elmo is taking 4-5 sec to transform 15 sentence into vector. Average sentence length 15-20 words.
How can I make it faster, can I use GPU instead of using CPU for fast prediction?
Source code / logs
I have made some changes in ElmoTransformer class but it is giving me error, here is the code
Here is the error I am getting when cuda_device==0 and I am using GPU:
expected object of backend cpu but got backend cuda
It would be great if someone will help me. Thanks