tensorflow/models · error · ValueError

Block fn `{}` is not supported.

Error message

Block fn `{}` is not supported.

What it means

Error "Block fn `{}` is not supported." thrown in tensorflow/models.

Source

Thrown at official/vision/modeling/backbones/revnet.py:122

        kernel_size=7, strides=2, use_bias=False, padding='same',
        kernel_initializer=self._kernel_initializer,
        kernel_regularizer=self._kernel_regularizer)(inputs)
    x = self._norm(
        axis=axis,
        momentum=norm_momentum,
        epsilon=norm_epsilon,
        synchronized=use_sync_bn)(x)
    x = tf_utils.get_activation(activation)(x)
    x = tf_keras.layers.MaxPool2D(pool_size=3, strides=2, padding='same')(x)

    endpoints = {}
    for i, spec in enumerate(REVNET_SPECS[model_id]):
      if spec[0] == 'residual':
        inner_block_fn = nn_blocks.ResidualInner
      elif spec[0] == 'bottleneck':
        inner_block_fn = nn_blocks.BottleneckResidualInner
      else:
        raise ValueError('Block fn `{}` is not supported.'.format(spec[0]))

      if spec[1] % 2 != 0:
        raise ValueError('Number of output filters must be even to ensure '
                         'splitting in channel dimension for reversible blocks')

      x = self._block_group(
          inputs=x,
          filters=spec[1],
          strides=(1 if i == 0 else 2),
          inner_block_fn=inner_block_fn,
          block_repeats=spec[2],
          batch_norm_first=(i != 0),  # Only skip on first block
          name='revblock_group_{}'.format(i + 2))
      endpoints[str(i + 2)] = x

    self._output_specs = {l: endpoints[l].get_shape() for l in endpoints}

    super(RevNet, self).__init__(inputs=inputs, outputs=endpoints, **kwargs)

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Use a supported RevNet block_fn: 'bottleneck' or 'basic'.
2. Check the block_fn value in the RevNet backbone config for typos.

When it happens

Trigger: Thrown at official/vision/modeling/backbones/revnet.py:122 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/b3804656e1442a33. Report an issue: GitHub.