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/mobiledet.py:522
in_filters=in_filters,
out_filters=block_def.filters,
kernel_size=block_def.kernel_size,
strides=block_def.strides,
input_compression_ratio=block_def.input_compression_ratio,
output_compression_ratio=block_def.output_compression_ratio,
activation=block_def.activation,
use_residual=block_def.use_residual,
kernel_initializer=self._kernel_initializer,
kernel_regularizer=self._kernel_regularizer,
bias_regularizer=self._bias_regularizer,
use_sync_bn=self._use_sync_bn,
norm_momentum=self._norm_momentum,
norm_epsilon=self._norm_epsilon,
divisible_by=self._get_divisible_by()
)(net)
else:
raise ValueError('Unknown block type {} for layer {}'.format(
block_def.block_fn, i))
net = tf_keras.layers.Activation('linear', name=block_name)(net)
if block_def.is_output:
endpoints[str(endpoint_level)] = net
endpoint_level += 1
return net, endpoints, endpoint_level
def get_config(self):
config_dict = {
'model_id': self._model_id,
'filter_size_scale': self._filter_size_scale,
'min_depth': self._min_depth,
'divisible_by': self._divisible_by,
'regularize_depthwise': self._regularize_depthwise,
'kernel_initializer': self._kernel_initializer,View on GitHub (pinned to e006f5f0d5)
Solutions
- Set the block 'type' field for the reported layer to a supported type such as 'conv' or 'inverted_bottleneck'.
- 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/mobiledet.py:522 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/8150c64ddfb5211b.
Report an issue: GitHub.