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/fpn.py:73
activation: the activation function.
use_batch_norm: 'bool', indicating whether batchnorm layers are added.
norm_activation: an operation that includes a normalization layer
followed by an optional activation layer.
"""
self._min_level = min_level
self._max_level = max_level
self._fpn_feat_dims = fpn_feat_dims
if use_separable_conv:
self._conv2d_op = functools.partial(
tf_keras.layers.SeparableConv2D, depth_multiplier=1)
else:
self._conv2d_op = tf_keras.layers.Conv2D
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._norm_activations = {}
self._lateral_conv2d_op = {}
self._post_hoc_conv2d_op = {}
self._coarse_conv2d_op = {}
for level in range(self._min_level, self._max_level + 1):
if self._use_batch_norm:
self._norm_activations[level] = norm_activation(
use_activation=False, name='p%d-bn' % level)
self._lateral_conv2d_op[level] = self._conv2d_op(
filters=self._fpn_feat_dims,
kernel_size=(1, 1),
padding='same',
name='l%d' % level)
self._post_hoc_conv2d_op[level] = self._conv2d_op(
filters=self._fpn_feat_dims,View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/legacy/detection/modeling/architecture/fpn.py:73 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/7d48995fa81d08dd.
Report an issue: GitHub.