tensorflow/models · error · ValueError
"logits" cannot be None when likelihood={self.likelihood}
Error message
"logits" cannot be None when likelihood={self.likelihood} What it means
Error ""logits" cannot be None when likelihood={self.likelihood}" thrown in tensorflow/models.
Source
Thrown at official/nlp/modeling/layers/gaussian_process.py:339
self.precision_matrix = (
self.add_weight(
name='gp_precision_matrix',
shape=(gp_feature_dim, gp_feature_dim),
dtype=self.dtype,
initializer=tf_keras.initializers.Identity(self.ridge_penalty),
trainable=False,
aggregation=tf.VariableAggregation.ONLY_FIRST_REPLICA))
self.built = True
def make_precision_matrix_update_op(self,
gp_feature,
logits,
precision_matrix):
"""Defines update op for the precision matrix of feature weights."""
if self.likelihood != 'gaussian':
if logits is None:
raise ValueError(
f'"logits" cannot be None when likelihood={self.likelihood}')
if logits.shape[-1] != 1:
raise ValueError(
f'likelihood={self.likelihood} only support univariate logits.'
f'Got logits dimension: {logits.shape[-1]}')
batch_size = tf.shape(gp_feature)[0]
batch_size = tf.cast(batch_size, dtype=gp_feature.dtype)
# Computes batch-specific normalized precision matrix.
if self.likelihood == 'binary_logistic':
prob = tf.sigmoid(logits)
prob_multiplier = prob * (1. - prob)
elif self.likelihood == 'poisson':
prob_multiplier = tf.exp(logits)
else:
prob_multiplier = 1.View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/nlp/modeling/layers/gaussian_process.py:339 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/c122edd99ad67cc4.
Report an issue: GitHub.