相关疑难解决方法(0)

我正在使用最后一层中的一些tensorflow函数(reduce_sum和l2_normalize)在Keras中构建模型,同时遇到此问题.我已经搜索了一个解决方案,但所有这些都与"Keras tensor"有关.

这是我的代码:

import tensorflow as tf;
from tensorflow.python.keras import backend as K

vgg16_model = VGG16(weights = 'imagenet', include_top = False, input_shape = input_shape);

fire8 = extract_layer_from_model(vgg16_model, layer_name = 'block4_pool');

pool8 = MaxPooling2D((3,3), strides = (2,2), name = 'pool8')(fire8.output);

fc1 = Conv2D(64, (6,6), strides= (1, 1), padding = 'same', name = 'fc1')(pool8);

fc1 = Dropout(rate = 0.5)(fc1);

fc2 = Conv2D(3, (1, 1), strides = (1, 1), padding = 'same', name = 'fc2')(fc1);

fc2 = Activation('relu')(fc2);

fc2 = Conv2D(3, (15, 15), …