AttributeError: 'Sequential'对象没有属性'run_eagerly'。

Question

我想使用这个模型来训练石头、剪刀、布的图片，但它只用1800张图片进行过训练，准确率只有30-40%。接着我尝试使用TensorBoard来查看情况，但标题中出现了错误。

from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
from tensorflow.python.keras.callbacks import TensorBoard

model = Sequential()
model.add(Conv2D(256, kernel_size=(4, 4),
            activation='relu',
            input_shape=(64,64,3)))
model.add(Conv2D(196, (4, 4), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Conv2D(196, (4, 4), activation='relu'))
model.add(Conv2D(196, (4, 4), activation='relu'))
model.add(Dropout(0.25))

model.add(Conv2D(128, (4, 4), activation='relu'))
model.add(Conv2D(128, (4, 4), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))
model.add(Dropout(0.25))

model.add(Conv2D(96, (4, 4), activation='relu'))
model.add(Conv2D(96, (4, 4), activation='relu'))
model.add(Dropout(0.25))

model.add(Flatten())
model.add(Dense(128, activation='relu'))
model.add(Dropout(0.5))

model.add(Dense(3, activation='softmax'))

''' here it instantiates the tensorboard '''
tensorboard = TensorBoard(log_dir="C:/Users/bamla/Desktop/RPS project/Logs")

model.compile(loss="sparse_categorical_crossentropy",
        optimizer="SGD",
        metrics=['accuracy'])

model.summary()

''' Here its fitting the model '''
model.fit(x_train, y_train, batch_size=50, epochs = 3, callbacks= 
[tensorboard])

这将输出：

Traceback (most recent call last):

File "c:/Users/bamla/Desktop/RPS project/Testing.py", line 82, in <module>
model.fit(x_train, y_train, batch_size=50, epochs = 3, callbacks= 
[tensorboard])

File "C:\Users\bamla\AppData\Local\Programs\Python\Python37\lib\site- 
packages\keras\engine\training.py", line 1178, in fit
validation_freq=validation_freq)

File "C:\Users\bamla\AppData\Local\Programs\Python\Python37\lib\site- 
 packages\keras\engine\training_arrays.py", line 125, in fit_loop
callbacks.set_model(callback_model)

 File "C:\Users\bamla\AppData\Local\Programs\Python\Python37\lib\site- 
packages\keras\callbacks.py", line 68, in set_model
callback.set_model(model)

File "C:\Users\bamla\AppData\Local\Programs\Python\Python37\lib\site- 
packages\tensorflow\python\keras\callbacks.py", line 1509, in set_model
if not model.run_eagerly:

AttributeError: 'Sequential' object has no attribute 'run_eagerly'

此外，如果您有任何关于如何提高准确性的技巧，我们将不胜感激！

- B T

---

可能是重复的问题 https://dev59.com/zrXna4cB1Zd3GeqPJFat ? - user3486184

Answer 1

问题出在这里：

from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten
from keras.layers import Conv2D, MaxPooling2D
from tensorflow.python.keras.callbacks import TensorBoard

不要混用keras和tf.keras的导入，它们不兼容，并会产生一些奇怪的错误，就像你正在看到的那些错误一样。

- Dr. Snoopy

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在这种情况下，我应该使用Keras还是tf.keras？ - B T

@BT 这取决于你。 - Dr. Snoopy

使用 from keras.callbacks import TensorBoard 从 https://keras.io/callbacks/。 - LYu

Answer 2

我将 from tensorflow.python.keras.callbacks import TensorBoard 改为 from keras.callbacks import TensorBoard 后，它对我起作用了。

- HAMID LAFREDI

Answer 3

看起来你在混合使用 keras 和 tensorflow.keras 的导入（后者更受推荐）。

https://www.pyimagesearch.com/2019/10/21/keras-vs-tf-keras-whats-the-difference-in-tensorflow-2-0/

最重要的是，未来所有深度学习从业者都应该将他们的代码转换到TensorFlow 2.0和tf.keras包。原始的keras包仍将接收错误修复，但是在未来，您应该使用tf.keras。

import tensorflow
Conv2D = tensorflow.keras.layers.Conv2D
MaxPooling2D = tensorflow.keras.layers.MaxPooling2D
Dense = tensorflow.keras.layers.Dense
Flatten = tensorflow.keras.layers.Flatten
Dropout = tensorflow.keras.layers.Dropout
TensorBoard = tensorflow.keras.callbacks.TensorBoard
model = tensorflow.keras.Sequential()

- Rocío García Luque

Answer 4

对我来说，这个做了它的工作：

from tensorflow.keras import datasets, layers, models
from tensorflow import keras

- Maikefer