!keras_retinanet/bin/train.py --freeze-backbone --random-transform --weights {PRETRAINED_MODEL} --batch-size 8 --steps 500 --epochs 10 csv annotations.csv classes.csv
Traceback (most recent call last):
File "keras_retinanet/bin/train.py", line 540, in
main()
File "keras_retinanet/bin/train.py", line 500, in main
config=args.config
File "keras_retinanet/bin/train.py", line 114, in create_models
model = model_with_weights(backbone_retinanet(num_classes, num_anchors=num_anchors, modifier=modifier), weights=weights, skip_mismatch=True)
File "keras_retinanet/bin/../../keras_retinanet/models/resnet.py", line 38, in retinanet
return resnet_retinanet(*args, backbone=self.backbone, **kwargs)
File "keras_retinanet/bin/../../keras_retinanet/models/resnet.py", line 99, in resnet_retinanet
resnet = keras_resnet.models.ResNet50(inputs, include_top=False, freeze_bn=True)
File "/usr/local/lib/python3.6/dist-packages/keras_resnet/models/_2d.py", line 188, in ResNet50
return ResNet(inputs, blocks, numerical_names=numerical_names, block=keras_resnet.blocks.bottleneck_2d, include_top=include_top, classes=classes, *args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/keras_resnet/models/_2d.py", line 66, in ResNet
x = keras_resnet.layers.BatchNormalization(axis=axis, epsilon=1e-5, freeze=freeze_bn, name="bn_conv1")(x)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/base_layer.py", line 922, in call
outputs = call_fn(cast_inputs, *args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/autograph/impl/api.py", line 265, in wrapper
raise e.ag_error_metadata.to_exception(e)
TypeError: in user code:
/usr/local/lib/python3.6/dist-packages/keras_resnet/layers/_batch_normalization.py:17 call *
return super(BatchNormalization, self).call(training=(not self.freeze), *args, **kwargs)
TypeError: type object got multiple values for keyword argument 'training'