tensorflow/models · error · ValueError

Unsupported activation `{}`.

Error message

Unsupported activation `{}`.

What it means

Error "Unsupported activation `{}`." thrown in tensorflow/models.

Source

Thrown at official/legacy/detection/modeling/architecture/heads.py:323

      self._conv2d_op = functools.partial(
          tf_keras.layers.SeparableConv2D,
          depth_multiplier=1,
          bias_initializer=tf.zeros_initializer())
    else:
      self._conv2d_op = functools.partial(
          tf_keras.layers.Conv2D,
          kernel_initializer=tf_keras.initializers.VarianceScaling(
              scale=2, mode='fan_out', distribution='untruncated_normal'),
          bias_initializer=tf.zeros_initializer())

    self._num_fcs = num_fcs
    self._fc_dims = fc_dims
    if activation == 'relu':
      self._activation_op = tf.nn.relu
    elif activation == 'swish':
      self._activation_op = tf.nn.swish
    else:
      raise ValueError('Unsupported activation `{}`.'.format(activation))
    self._use_batch_norm = use_batch_norm
    self._norm_activation = norm_activation

    self._conv_ops = []
    self._conv_bn_ops = []
    for i in range(self._num_convs):
      self._conv_ops.append(
          self._conv2d_op(
              self._num_filters,
              kernel_size=(3, 3),
              strides=(1, 1),
              padding='same',
              dilation_rate=(1, 1),
              activation=(None
                          if self._use_batch_norm else self._activation_op),
              name='conv_{}'.format(i)))
      if self._use_batch_norm:
        self._conv_bn_ops.append(self._norm_activation())

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/legacy/detection/modeling/architecture/heads.py:323 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/e36ad9daf7984d0d. Report an issue: GitHub.