无法为变量赋值,VGG16
我正在使用Transfer_learning使用VGG16预处理的网络训练一个系统。如果我使用权重,它会给我一个错误,我不知道原因或如何解决。有建议吗?
input_shape = (60, 36, 3)
# Declaramos dos capas de Input
input_1 = Input(shape=input_shape)
input_2 = Input(shape=input_shape)
concate_input = Concatenate()([input_1, input_2])
input = layers.Conv2D(6,3, activation="relu") (concate_input)
base_model = applications.VGG16(weights= 'imagenet', include_top=False, input_tensor=
concate_input)
错误消息是:
ValueError: Cannot assign value to variable ' block1_conv1/kernel:0': Shape mismatch.The variable shape (3, 3, 6, 64), and the assigned value shape (64, 3, 3, 3) are incompatible.
非常感谢
I am training a system with two images using transfer_learning using the VGG16 pretrained network. If I use the weights it gives me an error, I don't know the reason or how to solve it. Any suggestion?
input_shape = (60, 36, 3)
# Declaramos dos capas de Input
input_1 = Input(shape=input_shape)
input_2 = Input(shape=input_shape)
concate_input = Concatenate()([input_1, input_2])
input = layers.Conv2D(6,3, activation="relu") (concate_input)
base_model = applications.VGG16(weights= 'imagenet', include_top=False, input_tensor=
concate_input)
The error message is:
ValueError: Cannot assign value to variable ' block1_conv1/kernel:0': Shape mismatch.The variable shape (3, 3, 6, 64), and the assigned value shape (64, 3, 3, 3) are incompatible.
Thanks a lot¡¡
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