tensorflow/models · error · ValueError

Activation {} not supported by DefaultNBitActivationQuantize

Error message

Activation {} not supported by DefaultNBitActivationQuantizeConfig.

What it means

Error "Activation {} not supported by DefaultNBitActivationQuantizeConfig." thrown in tensorflow/models.

Source

Thrown at official/projects/qat/vision/n_bit/configs.py:341

      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 '
                       'DefaultNBitActivationQuantizeConfig.'.format(
                           layer.activation))

    # This code is copied from TFMOT repo, but added relu6 to support mobilenet.
    if layer.activation.__name__ in ['relu', 'relu6', 'swish']:
      # 'relu' should generally get fused into the previous layer.
      return [tfmot.quantization.keras.quantizers.MovingAverageQuantizer(
          num_bits=self._num_bits_activation, per_axis=False,
          symmetric=False, narrow_range=False)]  # activation/output
    elif layer.activation.__name__ in ['linear', 'softmax', 'sigmoid']:
      return []

    raise ValueError('Activation {} not supported by '
                     'DefaultNBitActivationQuantizeConfig.'.format(
                         layer.activation))

  def get_config(self) -> Dict[str, Any]:
    """Get a config for this quantizer config."""

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/qat/vision/n_bit/configs.py:341 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/52f17597a17e2369. Report an issue: GitHub.