CODEWITHSUNDEEP
pythontensorflowkeras
Tutku Doruk
Tutku Doruk

Reputation: 1

Deeplearning with Python Tensorflow,Keras

I am writing masters thesis about deeplearning and have a problem probably about library.

Below is the error:

AttributeError: module 'tensorflow.compat.v2' has no attribute '__internal__'

Model:

import tensorflow 
from tensorflow import  keras 
from keras import models  
from keras import layers  
model = models.Sequential()  
model.add(layers.Dense(32, input_shape=(784,)))  
model.add(layers.Dense(32))

Upvotes: 0

Views: 158

Answers (3)

Jonny_92
Jonny_92

Reputation: 159

I have run exactly your code, and it works.

Model: "sequential"
_________________________________________________________________
 Layer (type)                Output Shape              Param #
=================================================================
 dense (Dense)               (None, 32)                25120

 dense_1 (Dense)             (None, 32)                1056

=================================================================
Total params: 26,176
Trainable params: 26,176
Non-trainable params: 0
_________________________________________________________________

I am using tensorflow 2.12.0, on a Windows 10 DELL laptop. Please, indicate your tensorflow version. You can try removing both tensorflow and keras, and redoing the installation. I have performed my installation via pip, but, if you prefer, you can use also conda.

Upvotes: 0

Same123
Same123

Reputation: 1

most likely is the version of tensorflow you are using You just need to uninstall all keras and tensorflow packages and install the versions supported by Retinanet.

!pip uninstall keras -y !pip uninstall keras-nightly -y !pip uninstall keras-Preprocessing -y !pip uninstall keras-vis -y !pip uninstall tensorflow -y

!pip install tensorflow==2.3.0 !pip install keras==2.4

Just add this to the top of your colab notebook and restart your runtime once its completed and then you are good to go

Upvotes: 0

devilteo911
devilteo911

Reputation: 61

I think that the problem lies in the way you are importing the modules you need. Try to do this way:

import tensorflow  
from tensorflow.keras import models, layers  

model = models.Sequential()   
model.add(layers.Dense(32, input_shape=(784,)))   
model.add(layers.Dense(32))

model.summary()

If you get the summary of your network it means that everything is working fine, otherwise it could me that you haven't installed Tensorflow properly.

For reference this is the summary:

Layer (type)                 Output Shape              Param #
=================================================================
dense (Dense)                (None, 32)                25120
_________________________________________________________________
dense_1 (Dense)              (None, 32)                1056
=================================================================
Total params: 26,176
Trainable params: 26,176
Non-trainable params: 0
_________________________________________________________________

Upvotes: 1

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