tensorflow/models · error · ValueError
Backbone min level should be less or equal to FPN min level
Error message
Backbone min level should be less or equal to FPN min level
What it means
Error "Backbone min level should be less or equal to FPN min level" thrown in tensorflow/models.
Source
Thrown at official/vision/modeling/decoders/fpn.py:199
axis=bn_axis,
momentum=norm_momentum,
epsilon=norm_epsilon,
synchronized=use_sync_bn,
name=f'norm_{level}')(
feats[str(level)])
self._output_specs = {
str(level): feats[str(level)].get_shape()
for level in range(min_level, max_level + 1)
}
super().__init__(inputs=inputs, outputs=feats, **kwargs)
def _build_input_pyramid(self, input_specs: Mapping[str, tf.TensorShape],
min_level: int):
assert isinstance(input_specs, dict)
if min(input_specs.keys()) > str(min_level):
raise ValueError(
'Backbone min level should be less or equal to FPN min level')
inputs = {}
for level, spec in input_specs.items():
inputs[level] = tf_keras.Input(shape=spec[1:])
return inputs
def get_config(self) -> Mapping[str, Any]:
return self._config_dict
@classmethod
def from_config(cls, config, custom_objects=None):
return cls(**config)
@property
def output_specs(self) -> Mapping[str, tf.TensorShape]:
"""A dict of {level: TensorShape} pairs for the model output."""
return self._output_specsView on GitHub (pinned to e006f5f0d5)
Solutions
- Set the backbone min_level to a value less than or equal to the FPN min_level.
- Adjust the FPN min_level/max_level or the backbone levels so the ranges are compatible.
When it happens
Trigger: Thrown at official/vision/modeling/decoders/fpn.py:199 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/1caca25e6948a454.
Report an issue: GitHub.