keras.callbacks中的Tensorboard导入错误

我正在跟踪与Keras在神经网络上的senddex视频。

我的tensorflow版本是2.0.0。

我在Windows 10上并在Anaconda Jupyter环境中运行此代码。

我尝试搜索或出现此错误，但没有结果。

代码：

import tensorflow as tf
from tensorflow.keras.datasets import cifar10
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
from tensorflow.keras.layers import Conv2D, MaxPooling2D
from tensorflow.keras.callbacks import Tensorboard

import pickle
import numpy as np
import os
import time

os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'

NAME = "CATS-VS-DOGS-CNN-{}".format(int(time.time()))

tensorboard = TensorBoard(log_dir="logs/{}".format(NAME))

pickle_in = open("X.pickle","rb")
X = pickle.load(pickle_in)

pickle_in = open("y.pickle","rb")
y = pickle.load(pickle_in)

X = X/255.0

model = Sequential()

model.add(Conv2D(256, (3, 3), input_shape=X.shape[1:]))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Conv2D(256, (3, 3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Flatten())  # this converts our 3D feature maps to 1D feature vectors

model.add(Dense(64))
model.add(Activation('relu'))

model.add(Dense(1))
model.add(Activation('sigmoid'))

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

model.fit(X, y, batch_size=8, epochs=10, validation_split=0.3, callbacks = [tensorboard])

错误：

ImportError                               Traceback (most recent call last)
<ipython-input-2-a32bf5fe83d7> in <module>
      5 from tensorflow.keras.layers import Dense, Dropout, Activation, Flatten
      6 from tensorflow.keras.layers import Conv2D, MaxPooling2D
----> 7 from tensorflow.keras.callbacks import Tensorboard
      8 
      9 import pickle

ImportError: cannot import name 'Tensorboard' from 'tensorflow.keras.callbacks' (C:\Users\anves\Anaconda3\lib\site-packages\tensorflow_core\python\keras\api\_v2\keras\callbacks\__init__.py)