Error occurred in the Named Entity Recognition using Transformers example
Closed this issue · 6 comments
Issue Type
Bug
Source
source
Keras Version
Keras 3.1.0.dev2024031303
Custom Code
No
OS Platform and Distribution
No response
Python version
No response
GPU model and memory
Colab T4
Current Behavior?
A bug happened in the ner_model.fit part!
ner_model.compile(optimizer="adam", loss=loss)
ner_model.fit(train_dataset, epochs=10)
def tokenize_and_convert_to_ids(text):
tokens = text.split()
return lowercase_and_convert_to_ids(tokens)
# Sample inference using the trained model
sample_input = tokenize_and_convert_to_ids(
"eu rejects german call to boycott british lamb"
)
sample_input = tf.reshape(sample_input, shape=[1, -1])
print(sample_input)
output = ner_model.predict(sample_input)
prediction = np.argmax(output, axis=-1)[0]
prediction = [mapping[i] for i in prediction]
# eu -> B-ORG, german -> B-MISC, british -> B-MISC
print(prediction)
Output showing like this
OperatorNotAllowedInGraphError: Exception encountered when calling Softmax.call().
Using a symbolic `tf.Tensor` as a Python `bool` is not allowed. You can attempt the following resolutions to the problem: If you are running in Graph mode, use Eager execution mode or decorate this function with @tf.function. If you are using AutoGraph, you can try decorating this function with @tf.function. If that does not work, then you may be using an unsupported feature or your source code may not be visible to AutoGraph. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/g3doc/reference/limitations.md#access-to-source-code for more information.
Arguments received by Softmax.call():
• inputs=tf.Tensor(shape=(None, 4, None, None), dtype=float32)
• mask=None
For model training, I anticipate that model.fit will function properly and error-free. But the error happened.
Standalone code to reproduce the issue or tutorial link
Here is an executable Colab link to reproduce the error: https://colab.research.google.com/drive/1WtG-3b78mJHppCptt_GwNKR97KiR_FwU?usp=sharingRelevant log output
OperatorNotAllowedInGraphError: Exception encountered when calling Softmax.call().
Using a symbolic `tf.Tensor` as a Python `bool` is not allowed. You can attempt the following resolutions to the problem: If you are running in Graph mode, use Eager execution mode or decorate this function with @tf.function. If you are using AutoGraph, you can try decorating this function with @tf.function. If that does not work, then you may be using an unsupported feature or your source code may not be visible to AutoGraph. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/autograph/g3doc/reference/limitations.md#access-to-source-code for more information.
Arguments received by Softmax.call():
• inputs=tf.Tensor(shape=(None, 4, None, None), dtype=float32)
• mask=NoneSo my goal with the example is to replace some TF ops with Keras ops, and then the error occurred. Although now it is running well with adding code tf.config.run_functions_eagerly(True) that's the eager mode. Here is the notebook link: https://colab.research.google.com/drive/10cfqKFFs0Fy9VilbV7CRGLOcD8tTpqf-?usp=sharing
If it is okay, then can I make a PR with these changes?
@sitamgithub-MSIT , Please go ahead and make the changes.
@sitamgithub-MSIT , Please go ahead and make the changes.
Okay, I will submit a PR shortly!
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.
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