如何在keras/tensorflow中为占位符提供值

Question

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense,Dropout,Activation,Flatten, Conv2D, MaxPooling2D
import pickle
import keras as ks


x1 =pickle.load(open("dX.pickle","rb"))
y2 =pickle.load(open("dY.pickle","rb"))
nx = x1/255.0


model = Sequential()

model.add(Conv2D(64,(3,3),input_shape = nx.shape[1:]))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Conv2D(64,3,3))
model.add(Activation("relu"))
model.add(MaxPooling2D(pool_size = (2,2)))



model.add(Flatten())
model.add(Dense(64))
model.add(Dense(1))  

model.add(Activation('sigmoid'))
model.compile(loss = "binary_crossentropy", optimizer ="adam", metrics = ['accuracy'])


model.fit((nx,y2), batch_size = 20, validation_split =0.1,epochs=1)


img = image.load_img(r'img.png', target_size=(224,224))
prediction = model.prediction(img)
print(prediction)

我遵循了一个教程https://www.youtube.com/watch?v=cAICT4Al5Ow&t=89s，它向你展示了如何建立一个简单的神经网络。但当我运行代码时它会说。

tensorflow.python.framework.errors_impl.InvalidArgumentError: 


    You must feed a value for placeholder tensor 'activation_2_target' with dtype float and shape [?,?]


         [[{{node activation_2_target}}]]

我很困惑这个数字是从哪里来的，因为教程从来没有给它命名。我假设它是被某个类抽象出来的。我在哪里定义它？

Answer 1

更改此行

model.fit((nx,y2), batch_size=20, validation_split=0.1, epochs=1)

到这个

model.fit(nx, y2, batch_size=20, validation_split=0.1, epochs=1)

您只提供了元组(nx, y2)形式的训练数据，没有标签。