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

Question

我正在尝试使用此模型在剪刀石头布图片上进行训练。然而，它是在 1800 张图片上训练的，准确率只有 30-40%。然后我试图使用 TensorBoard 看看发生了什么，但出现了标题中的错误。

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提示，我们将不胜感激！

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 导入，它们 彼此不兼容 ，并且会产生您所看到的奇怪错误。

Answer 2

我改了from tensorflow.python.keras.callbacks import TensorBoard 到 from keras.callbacks import TensorBoard，它对我有用。

Answer 3

对我来说，这完成了工作：

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

Answer 4

您似乎在混合从 keras 和 tensorflow.keras 导入（最后一个是首选）。

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

And most importantly, going forward all deep learning practitioners should switch their code to TensorFlow 2.0 and the tf.keras package. The original keras package will still receive bug fixes, but moving forward, you should be using tf.keras.

试试：

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()

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

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

machine-learning

keras

tensorflow

tensorboard

python-3.7