AttributeError: 'KerasTensor' object has no attribute '_id

[Sunxihang]

Hi , I am coding the 8-11 about 'gradient'，but I have some bug.

code:

from keras.applications import inception_v3
from keras import backend as K
import tensorflow as tf

K.set_learning_phase(0)

model = inception_v3.InceptionV3(weights='imagenet',include_top=False)
#设置deepdream配置
layer_contributions = {
    'mixed2':0.2,
    'mixed3':3.,
    'mixed4':2.,
    'mixed5':1.5,
}
#定义需要最大化损失
layer_dict = dict([(layer.name,layer) for layer in model.layers])
loss = K.variable(0.)
for layer_name in layer_contributions:
    coeff = layer_contributions[layer_name]
    activation = layer_dict[layer_name].output
    
    scaling = K.prod(K.cast(K.shape(activation),'float32'))
    loss = loss + coeff * K.sum(K.square(activation[:, 2 :-2, 2: -2, :])) / scaling
#梯度上升过程
dream = model.input


with tf.GradientTape() as gtape:
    grads = gtape.gradient(loss,dream)[0]

# grads = K.gradients(loss,dream)[0]
grads /= K.maximum(K.mean(K.abs(grads)),1e-7)
outputs = [loss,grads]
fetch_loss_and_grads = K.function([dream],outputs)

def eval_loss_and_grads(x):
    outs = fetch_loss_and_grads([x])
    loss_value = out[0]
    grad_value =outs[1]
    return loss_value,grad_values

def gradient_ascent(x,iterations,step,max_loss=None):
    for i in range(iterations):
        loss_value,gra_values = eval_loss_and_grads(x)
        if max_loss is not None and loss_value > max_loss:
            break
        print('...Loss value at',i,':',loss_value)
        x += step * grad_values
        return x

bug information:

AttributeError                            Traceback (most recent call last)
~\AppData\Local\Temp/ipykernel_40076/4006197052.py in <module>
     27 
     28 with tf.GradientTape() as gtape:
---> 29     grads = gtape.gradient(loss,dream)[0]
     30 
     31 # grads = K.gradients(loss,dream)[0]

E:\Users\48067\Anaconda3\envs\Tensorflow-Keras-GPU\lib\site-packages\tensorflow\python\eager\backprop.py in gradient(self, target, sources, output_gradients, unconnected_gradients)
   1078         output_gradients=output_gradients,
   1079         sources_raw=flat_sources_raw,
-> 1080         unconnected_gradients=unconnected_gradients)
   1081 
   1082     if not self._persistent:

E:\Users\48067\Anaconda3\envs\Tensorflow-Keras-GPU\lib\site-packages\tensorflow\python\eager\imperative_grad.py in imperative_grad(tape, target, sources, output_gradients, sources_raw, unconnected_gradients)
     75       output_gradients,
     76       sources_raw,
---> 77       compat.as_str(unconnected_gradients.value))

AttributeError: 'KerasTensor' object has no attribute '_id

And My tensorflow and keras version is :

tensorflow-gpu    2.5.0
keras    2.5.0

looking forwoard to your reply. Thank you very much!