tensorflow/models · error · ValueError
Fusion type {} not supported.
Error message
Fusion type {} not supported. What it means
Error "Fusion type {} not supported." thrown in tensorflow/models.
Source
Thrown at official/projects/maskconver/modeling/fpn.py:169
feats = {str(backbone_max_level): feats_lateral[str(backbone_max_level)]}
for level in range(backbone_max_level - 1, min_level - 1, -1):
feat_a = spatial_transform_ops.nearest_upsampling(
feats[str(level + 1)], 2, use_keras_layer=use_keras_layer)
feat_b = feats_lateral[str(level)]
if fusion_type == 'sum':
if use_keras_layer:
feats[str(level)] = tf_keras.layers.Add()([feat_a, feat_b])
else:
feats[str(level)] = feat_a + feat_b
elif fusion_type == 'concat':
if use_keras_layer:
feats[str(level)] = tf_keras.layers.Concatenate(axis=-1)(
[feat_a, feat_b])
else:
feats[str(level)] = tf.concat([feat_a, feat_b], axis=-1)
else:
raise ValueError('Fusion type {} not supported.'.format(fusion_type))
# Build post-hoc 3x3 convolution kernel.
for level in range(min_level, backbone_max_level + 1):
feats[str(level)] = conv2d(
filters=num_filters,
strides=1,
kernel_size=depthwise_kernel_size if use_separable_conv else 3,
padding='same',
kernel_initializer=kernel_initializer,
kernel_regularizer=kernel_regularizer,
bias_regularizer=bias_regularizer)(
feats[str(level)])
# Build coarser FPN levels introduced for RetinaNet.
for level in range(backbone_max_level + 1, max_level + 1):
feats_in = feats[str(level - 1)]
if level > backbone_max_level + 1:
feats_in = activation_fn(feats_in)View on GitHub (pinned to e006f5f0d5)
When it happens
Trigger: Thrown at official/projects/maskconver/modeling/fpn.py:169 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/65a88c68a9e4e298.
Report an issue: GitHub.