tensorflow/models · error · ValueError
reuse_attention_scores cannot be None when reuse_attention !
Error message
reuse_attention_scores cannot be None when reuse_attention != 0.
What it means
Error "reuse_attention_scores cannot be None when reuse_attention != 0." thrown in tensorflow/models.
Source
Thrown at official/nlp/modeling/layers/reuse_transformer.py:307
Attention scores if return_attention_scores is true.
"""
if isinstance(inputs, (list, tuple)):
if len(inputs) == 2:
input_tensor, attention_mask = inputs
reuse_attention_scores = None
elif len(inputs) == 3:
input_tensor, attention_mask, reuse_attention_scores = inputs
else:
raise ValueError("Unexpected inputs to %s with length at %d" %
(self.__class__, len(inputs)))
else:
input_tensor, attention_mask, reuse_attention_scores = (inputs, None,
None)
key_value = None
if self._reuse_attention != 0 and reuse_attention_scores is None:
raise ValueError(
"reuse_attention_scores cannot be None when reuse_attention != 0.")
if self._output_range:
if self._norm_first:
source_tensor = input_tensor[:, 0:self._output_range, :]
input_tensor = self._attention_layer_norm(input_tensor)
if key_value is not None:
key_value = self._attention_layer_norm(key_value)
target_tensor = input_tensor[:, 0:self._output_range, :]
if attention_mask is not None:
attention_mask = attention_mask[:, 0:self._output_range, :]
if reuse_attention_scores is not None:
reuse_attention_scores = reuse_attention_scores[:, :,
0:self._output_range, :]
else:
if self._norm_first:
source_tensor = input_tensor
input_tensor = self._attention_layer_norm(input_tensor)View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/nlp/modeling/layers/reuse_transformer.py:307 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/eaff775d4aaecd46.
Report an issue: GitHub.