How to make individual predictions using the FNet example?
Closed this issue · 4 comments
Issue Type
Support
Source
source
Keras Version
Keras 2.14
Custom Code
Yes
OS Platform and Distribution
Linux Ubuntu
Python version
No response
GPU model and memory
No response
Current Behavior?
Once I have used the script for the creation of an FNet network, I want to make predictions on individual entries, however, doing it this way generates an array with several values and there should only be 2. How to make individual predictions using the predict method?
reference: https://keras.io/examples/nlp/fnet_classification_with_keras_nlp/
Standalone code to reproduce the issue or tutorial link
When I use predict, I got a vector with shape (32, 3)
fnet_classifier.predict(({"input_ids": [tokenizer("Hi, I'm Erick")]}))Relevant log output
No response
Using the same example when I predicted I got the shape 16,1
fnet_classifier.predict(({"input_ids": [tokenizer("Hi, I'm Erick")]})).shape
16/16 ━━━━━━━━━━━━━━━━━━━━ 0s 4ms/step
(16, 1)
This issue is stale because it has been open for 14 days with no activity. It will be closed if no further activity occurs. Thank you.
This issue was closed because it has been inactive for 28 days. Please reopen if you'd like to work on this further.