tensorflow/models · error · ValueError

Unknown block type {} for layer {}

Error message

Unknown block type {} for layer {}

What it means

Error "Unknown block type {} for layer {}" thrown in tensorflow/models.

Source

Thrown at official/vision/modeling/backbones/mobilenet.py:1540

          args.update({
              'middle_dw_downsample': block_def.middle_dw_downsample,
              'start_dw_kernel_size': block_def.start_dw_kernel_size,
              'middle_dw_kernel_size': block_def.middle_dw_kernel_size,
              'end_dw_kernel_size': block_def.end_dw_kernel_size,
              'use_layer_scale': block_def.use_layer_scale,
          })
          block = nn_blocks.UniversalInvertedBottleneckBlock(**args)

        if self._output_intermediate_endpoints:
          net, intermediate_endpoints = block(net)
        else:
          net = block(net)

      elif block_def.block_fn == 'gpooling':
        net = layers.GlobalAveragePooling2D(keepdims=True)(net)

      else:
        raise ValueError(
            'Unknown block type {} for layer {}'.format(
                block_def.block_fn, block_idx
            )
        )

      net = tf_keras.layers.Activation('linear', name=block_name)(net)

      if block_def.is_output:
        endpoints[str(endpoint_level)] = net
        for key, tensor in intermediate_endpoints.items():
          endpoints[str(endpoint_level) + '/' + key] = tensor
        if current_stride != self._output_stride:
          endpoint_level += 1

    if str(endpoint_level) in endpoints:
      endpoint_level += 1
    return net, endpoints, endpoint_level

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Set the block 'type' field for the reported layer to a supported type such as 'conv' or 'inverted_bottleneck'.
2. Check the block spec dict at the reported layer for a typo in the 'type' key.

When it happens

Trigger: Thrown at official/vision/modeling/backbones/mobilenet.py:1540 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/6d70e0d1c7714631. Report an issue: GitHub.