tensorflow/models · error · ValueError
Activation {} not supported by Default8BitActivationQuantize
Error message
Activation {} not supported by Default8BitActivationQuantizeConfig. What it means
Error "Activation {} not supported by Default8BitActivationQuantizeConfig." thrown in tensorflow/models.
Source
Thrown at official/projects/qat/nlp/quantization/configs.py:259
self,
layer: Layer,
quantize_weights: Sequence[tf.Tensor]):
"""See base class."""
self._assert_activation_layer(layer)
def set_quantize_activations(
self,
layer: Layer,
quantize_activations: Sequence[Activation]):
"""See base class."""
self._assert_activation_layer(layer)
def get_output_quantizers(self, layer: Layer) -> Sequence[Quantizer]:
"""See base class."""
self._assert_activation_layer(layer)
if not hasattr(layer.activation, '__name__'):
raise ValueError('Activation {} not supported by '
'Default8BitActivationQuantizeConfig.'.format(
layer.activation))
# This code is copied from TFMOT repo, but added relu6 to support mobilenet.
if layer.activation.__name__ in ['relu', 'relu6']:
# 'relu' should generally get fused into the previous layer.
return [MovingAverageQuantizer(
num_bits=8, per_axis=False, symmetric=False, narrow_range=False)]
elif layer.activation.__name__ in ['linear', 'softmax', 'sigmoid']:
return []
raise ValueError('Activation {} not supported by '
'Default8BitActivationQuantizeConfig.'.format(
layer.activation))
def get_config(self) -> Dict[str, Any]:
"""Get a config for this quantizer config."""
return {}View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/qat/nlp/quantization/configs.py:259 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/556d27cc5d7b906f.
Report an issue: GitHub.