tensorflow/models · error · ValueError
{self.__class__} does not support `output_range` argument.
Error message
{self.__class__} does not support `output_range` argument. What it means
Error "{self.__class__} does not support `output_range` argument." thrown in tensorflow/models.
Source
Thrown at official/nlp/modeling/layers/pack_optimization.py:142
inner_output = self._inner_dropout_layer(inner_output)
layer_output = self._output_dense(inner_output)
layer_output = self._output_dropout(layer_output)
if self._norm_first:
return source_attention_output + layer_output # pyrefly: ignore[unbound-name]
layer_output = tf.cast(layer_output, tf.float32)
return self._output_layer_norm(layer_output + attention_output)
@tf_keras.utils.register_keras_serializable(package='Text')
class StridedReZeroTransformer(rezero_transformer.ReZeroTransformer):
"""ReZeroTransformer for packing optimization to stride over inputs."""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
if self._output_range is not None:
raise ValueError(f'{self.__class__} does not '
'support `output_range` argument.')
# TODO(b/337888023): Support block sparse attention with strided inputs.
if self._src_block_size is not None:
raise ValueError(f'{self.__class__} does not '
'support block sparse attention.')
def call(self, inputs, stride: tf.Tensor):
if isinstance(inputs, (list, tuple)):
if len(inputs) == 2:
input_tensor, attention_mask = inputs
key_value = None
elif len(inputs) == 3:
input_tensor, key_value, attention_mask = inputs
else:
raise ValueError(f'Unexpected inputs to {self.__class__} with '
f'length at {len(inputs)}.')
else:
input_tensor, key_value, attention_mask = (inputs, None, None)View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/nlp/modeling/layers/pack_optimization.py:142 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/67edfce45867eb08.
Report an issue: GitHub.