tensorflow/models · error · ValueError
Backbone model `{}` is not supported.
Error message
Backbone model `{}` is not supported. What it means
Error "Backbone model `{}` is not supported." thrown in tensorflow/models.
Source
Thrown at official/legacy/detection/modeling/architecture/factory.py:50
epsilon=params.batch_norm_epsilon,
trainable=params.batch_norm_trainable,
activation=params.activation)
def backbone_generator(params):
"""Generator function for various backbone models."""
if params.architecture.backbone == 'resnet':
resnet_params = params.resnet
backbone_fn = resnet.Resnet(
resnet_depth=resnet_params.resnet_depth,
activation=params.norm_activation.activation,
norm_activation=norm_activation_generator(
params.norm_activation))
elif params.architecture.backbone == 'spinenet':
spinenet_params = params.spinenet
backbone_fn = spinenet.SpineNetBuilder(model_id=spinenet_params.model_id)
else:
raise ValueError('Backbone model `{}` is not supported.'
.format(params.architecture.backbone))
return backbone_fn
def multilevel_features_generator(params):
"""Generator function for various FPN models."""
if params.architecture.multilevel_features == 'fpn':
fpn_params = params.fpn
fpn_fn = fpn.Fpn(
min_level=params.architecture.min_level,
max_level=params.architecture.max_level,
fpn_feat_dims=fpn_params.fpn_feat_dims,
use_separable_conv=fpn_params.use_separable_conv,
activation=params.norm_activation.activation,
use_batch_norm=fpn_params.use_batch_norm,
norm_activation=norm_activation_generator(
params.norm_activation))View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/legacy/detection/modeling/architecture/factory.py:50 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/0b140cc501bca78c.
Report an issue: GitHub.