Keras that does not support TensorFlow 2.0. We rec

问题:

I am having an error regarding (Keras that does not support TensorFlow 2.0. We recommend using tf.keras, or alternatively, downgrading to TensorFlow 1.14.) any recommendations.

thanks

import keras
#For building the Neural Network layer by layer
from keras.models import Sequential
#To randomly initialize the weights to small numbers close to 0(But not 0)
from keras.layers import Dense

classifier=tf.keras.Sequential()

classifier.add(Dense(output_dim = 6, init = 'uniform', activation = 'relu', input_dim = 11))




RuntimeError: It looks like you are trying to use a version of multi-backend Keras that does not support TensorFlow 2.0. We recommend using `tf.keras`, or alternatively, downgrading to TensorFlow 1.14.

回答1:

You should only have to change the imports at the top:

from tensorflow.python.keras.layers import Dense
from tensorflow.python.keras import Sequential

classifier = Sequential()
classifier.add(Dense(6, init = 'uniform', activation = 'relu', input_dim = 11))

回答2:

TensorFlow 2.0+ is only compatible with Keras 2.3.0+, so if you wish to use Keras 2.2.5-, you'll need TensorFlow 1.15.0-. Alternatively, yes, you can do from tensorflow.keras import ..., but that will not use your keras package at all and you might as well uninstall it.

回答3:

if you want to use tensorflow 2.0+ you must have keras 2.3+
try to upgrade your keras it works for me :

pip install -U keras

or you may specify the keras version to 2.3

回答4:

I ran into the same issue. Downgraded my TensorFlow to version 1.14 using the following:

!pip install tensorflow==1.14.0

Fixed the error.

回答5:

first, import tensorflow:

import tensorflow as tf

Next, in place of this,

classifier.add(Dense(output_dim = 6, init = 'uniform', activation = 'relu', input_dim = 11))

use:

classifier.add(tf.keras.layers.Dense(output_dim = 6, init = 'uniform', activation = 'relu', input_dim = 11))

Let me know if it works.

回答6:

this line of code on the first cell worked for me

%tensorflow_version 1.x

回答7:

I fixed the problem by running

pip install --ignore-installed --upgrade keras