tensorflow/models · error · ValueError
Unknown `output` value "%s". `output` can be either "logits"
Error message
Unknown `output` value "%s". `output` can be either "logits" or "predictions"
What it means
Error "Unknown `output` value "%s". `output` can be either "logits" or "predictions"" thrown in tensorflow/models.
Source
Thrown at official/nlp/modeling/models/bert_token_classifier.py:87
else:
sequence_output = outputs['sequence_output']
sequence_output = tf_keras.layers.Dropout(rate=dropout_rate)(
sequence_output)
classifier = tf_keras.layers.Dense(
num_classes,
activation=None,
kernel_initializer=initializer,
name='predictions/transform/logits')
logits = classifier(sequence_output)
if output == 'logits':
output_tensors = {'logits': logits}
elif output == 'predictions':
output_tensors = {
'predictions': tf_keras.layers.Activation(tf.nn.log_softmax)(logits)
}
else:
raise ValueError(
('Unknown `output` value "%s". `output` can be either "logits" or '
'"predictions"') % output)
if output_encoder_outputs:
output_tensors['encoder_outputs'] = sequence_output
# b/164516224
# Once we've created the network using the Functional API, we call
# super().__init__ as though we were invoking the Functional API Model
# constructor, resulting in this object having all the properties of a model
# created using the Functional API. Once super().__init__ is called, we
# can assign attributes to `self` - note that all `self` assignments are
# below this line.
super(BertTokenClassifier, self).__init__(
inputs=inputs, outputs=output_tensors, **kwargs)
self._network = network
config_dict = {View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/nlp/modeling/models/bert_token_classifier.py:87 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24).
Data as JSON: /api/errors/9b0c345f6731a25c.
Report an issue: GitHub.