上下文-我在保存/加载EfficientNetB 7时遇到错误，我看到的一篇文章建议安装tf-nightly。这真的让我的Google Colab崩溃了！我卸载了tf-nightly，重新启动了我的运行时，现在当我去运行导入单元格时，我得到了下面的错误。
我重新安装了tensorflow 2.6.0。

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-25-5d853ee59f92> in <module>()
     11 import tensorflow as tf
     12 from tensorflow import keras
---> 13 from tensorflow.keras import Model
     14 from tensorflow.keras.models import Sequential
     15 from tensorflow.keras.utils import to_categorical

11 frames
/usr/local/lib/python3.7/dist-packages/keras/layers/core/dropout.py in <module>()
     24 
     25 @keras_export('keras.layers.Dropout')
---> 26 class Dropout(base_layer.BaseRandomLayer):
     27   """Applies Dropout to the input.
     28 

AttributeError: module 'keras.engine.base_layer' has no attribute 'BaseRandomLayer'

我以前也遇到过此导入的问题：

from tensorflow.keras import backend as keras

以下是我的所有导入：

import os
import glob
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from skimage.io import imread
from skimage.transform import resize
from sklearn.preprocessing import OneHotEncoder
from sklearn.model_selection import train_test_split

import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import Model
from tensorflow.keras.models import Sequential
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.losses import categorical_crossentropy
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from tensorflow.keras.layers import Dense, Flatten, Conv2D, MaxPooling2D, Dropout, BatchNormalization

from tensorflow.keras.callbacks import ModelCheckpoint, LearningRateScheduler
from datetime import datetime

from sklearn.metrics import confusion_matrix, accuracy_score, f1_score, precision_score, recall_score

import skimage.io as io
import skimage.transform as trans
from tensorflow.keras import models
from tensorflow.keras import layers
from tensorflow.keras import optimizers
from tensorflow.keras.models import *
from tensorflow.keras.layers import *
from tensorflow.keras.optimizers import *
from tensorflow.keras.callbacks import ModelCheckpoint, LearningRateScheduler
from tensorflow.keras import backend as keras
from tensorflow.keras.preprocessing.image import ImageDataGenerator
from keras_preprocessing.image import ImageDataGenerator
from tensorflow.keras.optimizers.schedules import ExponentialDecay

import scipy.misc as sc
import h5py

from sklearn.semi_supervised import LabelSpreading
from sklearn.model_selection import GridSearchCV

from tensorflow.keras.applications import * #Efficient Net included here
import shutil
from sklearn import model_selection
from tqdm import tqdm

# import warnings
# warnings.filterwarnings("ignore", category=DeprecationWarning)