tensorflow/models · error · RuntimeError

Default8BitActivationQuantizeConfig can only be used with `k

Error message

Default8BitActivationQuantizeConfig can only be used with `keras.layers.Activation`.

What it means

Error "Default8BitActivationQuantizeConfig can only be used with `keras.layers.Activation`." thrown in tensorflow/models.

Source

Thrown at official/projects/qat/vision/quantization/configs.py:265

               activation_attrs: Sequence[str],
               quantize_output: bool):
    """Initializes default 8bit quantization config for the conv layer."""
    super().__init__(weight_attrs, activation_attrs, quantize_output)

    self.weight_quantizer = Default8BitConvWeightsQuantizer()


class Default8BitActivationQuantizeConfig(
    tfmot.quantization.keras.QuantizeConfig):
  """QuantizeConfig for keras.layers.Activation.

  `keras.layers.Activation` needs a separate `QuantizeConfig` since the
  decision to quantize depends on the specific activation type.
  """

  def _assert_activation_layer(self, layer: Layer):
    if not isinstance(layer, tf_keras.layers.Activation):
      raise RuntimeError(
          'Default8BitActivationQuantizeConfig can only be used with '
          '`keras.layers.Activation`.')

  def get_weights_and_quantizers(
      self, layer: Layer) -> Sequence[WeightAndQuantizer]:
    """See base class."""
    self._assert_activation_layer(layer)
    return []

  def get_activations_and_quantizers(
      self, layer: Layer) -> Sequence[ActivationAndQuantizer]:
    """See base class."""
    self._assert_activation_layer(layer)
    return []

  def set_quantize_weights(
      self,
      layer: Layer,

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/qat/vision/quantization/configs.py:265 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/c400e74911007e65. Report an issue: GitHub.