Keras model.to_json()错误:"rawunicodeescape"编解码器无法解码位置94-98中的字节:截断的\ uXXXX [英] Keras model.to_json() error: 'rawunicodeescape' codec can't decode bytes in position 94-98: truncated \uXXXX

问题描述

model.to_json()

用于模型

____________________________________________________________________________________________________图层(类型)输出形状参数#
已连接到
================================================== ================================================== lambda_1(Lambda)(无，3、160、320)0
lambda_input_1 [0] [0]
____________________________________________________________________________________________________ convolution2d_1(Convolution2D)(无，1、40、16)327696
lambda_1 [0] [0]
____________________________________________________________________________________________________ elu_1(ELU)(无，1、40、16)0
convolution2d_1 [0] [0]
____________________________________________________________________________________________________ convolution2d_2(Convolution2D)(无，1、20、32)12832
elu_1 [0] [0]
____________________________________________________________________________________________________ elu_2(ELU)(无，1、20、32)0
convolution2d_2 [0] [0]
____________________________________________________________________________________________________ convolution2d_3(Convolution2D)(无，1、10、64)51264
elu_2 [0] [0]
____________________________________________________________________________________________________ flatten_1(Flatten)(无，640)0
convolution2d_3 [0] [0]
____________________________________________________________________________________________________ dropout_1(退出)(无，640)0
flatten_1 [0] [0]
____________________________________________________________________________________________________ elu_3(ELU)(无，640)0
dropout_1 [0] [0]
____________________________________________________________________________________________________ density_1(密集)(无，512)328192
elu_3 [0] [0]
____________________________________________________________________________________________________ dropout_2(Dropout)(None，512)0
density_1 [0] [0]
____________________________________________________________________________________________________ elu_4(ELU)(无，512)0
dropout_2 [0] [0]
____________________________________________________________________________________________________ density_2(密集)(无，1个)513
elu_4 [0] [0]
================================================== ==================================================总参数:720,497可训练参数:720,497非可训练参数: 0 ____________________________________________________________________________________________________无

____________________________________________________________________________________________________ Layer (type) Output Shape Param #
Connected to
==================================================================================================== lambda_1 (Lambda) (None, 3, 160, 320) 0
lambda_input_1[0][0]
____________________________________________________________________________________________________ convolution2d_1 (Convolution2D) (None, 1, 40, 16) 327696
lambda_1[0][0]
____________________________________________________________________________________________________ elu_1 (ELU) (None, 1, 40, 16) 0
convolution2d_1[0][0]
____________________________________________________________________________________________________ convolution2d_2 (Convolution2D) (None, 1, 20, 32) 12832
elu_1[0][0]
____________________________________________________________________________________________________ elu_2 (ELU) (None, 1, 20, 32) 0
convolution2d_2[0][0]
____________________________________________________________________________________________________ convolution2d_3 (Convolution2D) (None, 1, 10, 64) 51264
elu_2[0][0]
____________________________________________________________________________________________________ flatten_1 (Flatten) (None, 640) 0
convolution2d_3[0][0]
____________________________________________________________________________________________________ dropout_1 (Dropout) (None, 640) 0
flatten_1[0][0]
____________________________________________________________________________________________________ elu_3 (ELU) (None, 640) 0
dropout_1[0][0]
____________________________________________________________________________________________________ dense_1 (Dense) (None, 512) 328192
elu_3[0][0]
____________________________________________________________________________________________________ dropout_2 (Dropout) (None, 512) 0
dense_1[0][0]
____________________________________________________________________________________________________ elu_4 (ELU) (None, 512) 0
dropout_2[0][0]
____________________________________________________________________________________________________ dense_2 (Dense) (None, 1) 513
elu_4[0][0]
==================================================================================================== Total params: 720,497 Trainable params: 720,497 Non-trainable params: 0 ____________________________________________________________________________________________________ None

引发异常

'rawunicodeescape'编解码器无法解码位置94-98中的字节: 截断的\ uXXXX

'rawunicodeescape' codec can't decode bytes in position 94-98: truncated \uXXXX

可能是什么问题，我该如何解决?

What could be the problem and how can I solve it?

推荐答案

在使用带有tensorflow-gpu后端的keras 1.2.1时，我遇到了类似的问题.

I came across a similar problem when using keras 1.2.1 with a tensorflow-gpu backend.

我发现这是由于Windows 10周年纪念版在编码正斜杠字符时遇到问题.

I found out it was caused because windows 10 anniversary edition was having problems encoding the forward slash character.

使用Lambda层会使to_json()调用失败，但是切换到批处理规范化就可以了.

Using the Lambda layer makes the to_json() call fail but switching to batch normalization works just fine.

model = Sequential()

# model.add(Lambda(lambda x: x / 255. - .5, input_shape=INPUT_DIMENSIONS))
model.add(BatchNormalization(input_shape=INPUT_DIMENSIONS, axis=1))
. . . 
# POST PROCESSING, SAVE MODEL TO DISK
with open('model.json', 'w') as json_file:
    json_file.write(model.to_json())

这不是理想的解决方案，但希望以后对这一点有用的人.

Not an ideal solution but hopefully it works for someone looking at this in the future.

这篇关于Keras model.to_json()错误:"rawunicodeescape"编解码器无法解码位置94-98中的字节:截断的\ uXXXX的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！