解决keras.backend.reshape中的错误ValueError: Tried to convert 'shape' to a tensor and failed. Error: Cannot convert a partially known TensorShape to a Tensor
許多CNN網絡都有Fusion layer作為融合層,比如:
參考:https://arxiv.org/pdf/1712.03400.pdf
相關代碼:(https://github.com/baldassarreFe/deep-koalarization/blob/master/src/koalarization/fusion_layer.py)
class FusionLayer(Layer):
def call(self, inputs, mask=None):
imgs, embs = inputs
reshaped_shape = imgs.shape[:3].concatenate(embs.shape[1])
embs = K.repeat(embs, imgs.shape[1] * imgs.shape[2])
embs = K.reshape(embs, reshaped_shape)
return K.concatenate([imgs, embs], axis=3)
當我實際去做的時候,K.reshape 報錯:ValueError: Tried to convert 'shape' to a tensor and failed. Error: Cannot convert a partially known TensorShape to a Tensor
reshaped_shape = enco_loco.shape[:3].concatenate(enco_glob.shape[1])
fuse = K.repeat(enco_glob, enco_loco.shape[1]*enco_loco.shape[2])
fuse = K.reshape(fuse, (reshaped_shape))
fuse = K.concatenate([enco_loco, fuse], axis=3)
相關信息:
enco_loco:(None, 16, 16, 512)
enco_glob:(None, 512)
reshaped_shape:(None, 16, 16, 512)
enco_glob.shape:(None, 512)
fuse.shape:(None, 256, 512)
最后想把fuse從(None, 256, 512) 變成(None, 16, 16, 512) 就出現上述錯誤。
解決過程:
fuse = K.reshape(fuse, (-1, reshaped_shape[1], reshaped_shape[2], reshaped_shape[3]))
參考:https://github.com/matterport/Mask_RCNN/issues/1070
但又出現錯誤:AttributeError 'NoneType' object has no attribute '_inbound_nodes'
原來是因為:“只要使用Model,就必須保證該函數內全為layer而不能有其他函數,如果有其他函數必須用Lambda封裝為layer。”
參考:https://zhuanlan.zhihu.com/p/138075621
好吧,再改一下:
from keras.layers import RepeatVector, Reshape
from keras.layers.merge import concatenate
reshaped_shape = enco_loco.shape[:3].concatenate(enco_glob.shape[1])
fuse = RepeatVector(enco_loco.shape[1]*enco_loco.shape[2])(enco_glob)
fuse = Reshape(( reshaped_shape[1], reshaped_shape[2], reshaped_shape[3]))(fuse)
fuse = concatenate([enco_loco, fuse], axis=3)
注意這里的維度必須是( reshaped_shape[1], reshaped_shape[2], reshaped_shape[3]) 而不是( -1, reshaped_shape[1], reshaped_shape[2], reshaped_shape[3])
不然會出錯
總結
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