I tried to install tensorflow_federated in google colab. I used
pip install --quiet tensorflow-federated-nightly
import tensorflow-federated as tff
and it worked. but now when I try to import it get this error:
AttributeError: module 'keras.api._v2.keras.experimental' has no attribute 'PeepholeLSTMCell'
I don't know why I get this error, because I didn't have any problem before.
I also used the following code to install tensorflow-federated:
pip install --upgrade tensorflow-federated-nightly
but I get the same error.
How do I fix it?
My versions are:
tensorflow 2.8.0,
keras 2.8.0,
tensorflow-federated-nightly 0.19.0.dev20220218
To use TensorFlow Federated with TensorFlow 2.8.0, please try the newly released version of TFF 0.20.0 pypi, github.
The tensorflow-federated-nightly package depends on the nightly versions of TensorFlow (tf-nightly), Keras (keras-nightly) and so on.
Trying import of initial libraries related to tensorflow_quantum:
import tensorflow as tf
import tensorflow_quantum as tfq
import cirq
import sympy
import numpy as np
Getting error in 2nd line:
File "Path_to_anaconda_site_packages\tensorflow_core\python\framework\load_library.py", line 61, in load_op_library
lib_handle = py_tf.TF_LoadLibrary(library_filename)
NotFoundError: Path_To_Tensorflow_Quantum\core\ops\_tfq_simulate_ops.so not found
This is the solution provided by the Tensorflow team, it worked for me.
!pip install tensorflow-gpu==2.1.0
!pip install cirq==0.7.0 pathos==0.2.5 tensorflow-quantum==0.2.0
Do following steps:
!pip uninstall tensorflow
!pip install tensorflow
then restart runtime to import the packages.It works.
This might be something that would be worth raising as an issue on the TensorFlow Quantum Github here (https://github.com/tensorflow/quantum/issues). Without much information on the platform your are using or even what python version you have it might be hard to diagnose the problem here, but a quick fix you could try might be that you have an older version of TensorFlow installed. TensorFlow Quantum requires tf == 2.1.0.
pip install --upgrade pip
pip install --upgrade tensorflow
If that doesn't do it, then it might be worth opening an issue on github and giving a few more details on there :)
then i type import tflearn i got the error below, i follow the guide here: https://www.youtube.com/watch?v=ViO56ASqeks
what can i use tflearn, or shall i use another code?
i got the error below.
import tflearn
File "/usr/local/lib/python3.5/dist-packages/tflearn/__init__.py", line 4, in <module>
from . import config
File "/usr/local/lib/python3.5/dist-packages/tflearn/config.py", line 5, in <module>
from .variables import variable
File "/usr/local/lib/python3.5/dist-packages/tflearn/variables.py", line 7, in <module>
from tensorflow.contrib.framework.python.ops import add_arg_scope as contrib_add_arg_scope
ImportError: No module named 'tensorflow.contrib.framework
can someone help me ?
20/08-2019: Edit 20.35
pip list:
tensorflow 2.0.0rc0
I had a similar problem and I solved it by:-
1) upgrading python to 3.6
2) pip uninstall tflearn
3) pip install git+https://github.com/tflearn/tflearn.git
4) As suggested in another solution tensorflow 2.0.0 does not support tflearn so I installed tensorflow==1.14.0
I found the solution here:-
Issue Link/
If you use an conda environment (and not only, but I advise you to use it), then the solution will be to use a lower version of tensorflow pip uninstall tensorflow pip install tensorflow==1.14.0.
And it is possible to use the script to fix all errors(i used it before downgrade tf):
tf_upgrade_v2 \
--intree my_project/ \
--outtree my_project_v2/ \
--reportfile report.txt
It works for me
You need to have tensorflow installed before you can use tflearn.
From the tflearn github page:
TensorFlow Installation
TFLearn requires Tensorflow (version 1.0+) to be installed.
To install tensorflow:
pip install tensorflow
The tutorial that you are watching uses tensorflow version 0.9 or something, current version is 2.0. The tutorial is 3 years old. You should watch updated video.
However, you can try.
pip install tensorflow==1.0
pip install tflearn
if you're using a virtual environment, make sure you have activated it.
You can use keras instead of tflearn.
tensorflow.contrib is being removed in version 2.0, you therefore need version <= 1.14 to operate tflearn (see here).
I am trying to run a script, but I struggle already at the imports.
This import
from keras.preprocessing.image import save_img
raises the following error:
AttributeError: module 'tensorflow' has no attribute 'name_scope'.
I am using the following packages.
Keras 2.2.2,
Keras-Applications 1.0.4,
Keras-Preprocessing 1.0.2,
tensorflow 1.9.0,
tensorflow-gpu 1.9.0
I was unable to reproduce with the same versions of the keras and tensorflow, reinstalling keras and tensorflow, may solve the issue, please use commands below:
pip install --upgrade pip setuptools wheel
pip install -I tensorflow
pip install -I keras
NOTE: The -I parameter stands for ignore installed package.
For everyone who use Tensorflow 2.0 and stumble upon this question with the same error, like I did: I solved it by changing the imports from keras.xxx to tensorflow.keras.xxx
I also encountered this same problem when I stopped my IDE while executing. Restarting my IDE works for me. Just save your program and restart IDE. Hope it will work for you as well.
As Andriy Ivaneyko mentioned above, reinstalling tensorflow helps. I'm not sure why, but installing tensorflow-serving-api breaks something somewhere along the way. We solved this by running:
pip install --force-reinstall tensorflow
Note that this applies to both tensorflow and tensorflow-gpu installations. Specifically, the above command will fix this problem in situations where you're specifically using tensorlfow-gpu. tensorflow-serving-api installs regular tensorflow if it's not already installed.
I encountered this same bug and reinstalling tensorflow made no difference, and this caused me some headscratching.
Eventually I noticed that my IDE autocomplete had added the following line to my code:
from tensorflow_core.python.keras.callbacks import EarlyStopping
It seems that directly referencing tensorflow_core.python will break tensorflow.
Replacing this with the normal tensorflow import solved the problem!
from tensorflow.keras.callbacks import EarlyStopping
My IDE offered me two different import paths
keras
or
tensorflow_core.python.keras
In my example I could either import like this:
from keras.layers import Dense, Dropout, LSTM, Input, Activation
from keras import optimizers, Model
or like that:
from tensorflow_core.python.keras import Input, Model, optimizers
from tensorflow_core.python.keras.layers import LSTM, Dropout, Dense
Mixing up tensorflow_core.python.keras and plain keras led to the problem in my case. After I imported everything directly from keras and keras.layers, it worked for me.
My tensorflow version is 2.1, and I found my tensorflow-estimator version is 2.2
My fix is to downgrade the estimator to the same version
I've been trying to use tensorflow for two days now installing and reinstalling it over and over again in python2.7 and 3.4. No matter what I do, I get this error message when trying to use tensorflow.placeholder()
It's very boilerplate code:
tf_in = tf.placeholder("float", [None, A]) # Features
No matter what I do I always get the trace back:
Traceback (most recent call last):
File "/home/willim/PycharmProjects/tensorflow/tensorflow.py", line 2, in <module>
import tensorflow as tf
File "/home/willim/PycharmProjects/tensorflow/tensorflow.py", line 53, in <module>
tf_in = tf.placeholder("float", [None, A]) # Features
AttributeError: 'module' object has no attribute 'placeholder'
Anyone know how I can fix this?
If you have this error after an upgrade to TensorFlow 2.0, you can still use 1.X API by replacing:
import tensorflow as tf
by
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
Solution: Do not use "tensorflow" as your filename.
Notice that you use tensorflow.py as your filename. And I guess you write code like:
import tensorflow as tf
Then you are actually importing the script file "tensorflow.py" that is under your current working directory, rather than the "real" tensorflow module from Google.
Here is the order in which a module will be searched when importing:
The directory containing the input script (or the current directory when no file is specified).
PYTHONPATH (a list of directory names,
with the same syntax as the shell variable PATH).
The installation-dependent default.
It happened to me too. I had tensorflow and it was working pretty well, but when I install tensorflow-gpu along side the previous tensorflow this error arose then I did these 3 steps and it started working with no problem:
I removed tensorflow-gpu, tensorflow, tensorflow-base packages from Anaconda. Using.
conda remove tensorflow-gpu tensorflow tensorflow-base
re-installed tensorflow. Using
conda install tensorflow
Instead of tf.placeholder(shape=[None, 2], dtype=tf.float32) use something like
tf.compat.v1.placeholder(shape=[None, 2], dtype=tf.float32) if you don't want to disable v2 completely.
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
works.
I am using Python 3.7 and tensorflow 2.0.
It appears that .placeholder() , .reset_default_graph() , and others were removed with version 2. I ran into this issue using Docker image: tensorflow/tensorflow:latest-gpu-py3 which automatically pulls the latest version. I was working in 1.13.1 and was 'upgraded to 2' automatically and started getting the error messages. I fixed this by being more specific with my image: tensorflow/tensorflow:1.13.1-gpu-py3.
More info can be found here: https://www.tensorflow.org/alpha/guide/effective_tf2
Avoid using the below striked out statement in tensorflow=2.0
i̶m̶p̶o̶r̶t̶ ̶t̶e̶n̶s̶o̶r̶f̶l̶o̶w̶ ̶a̶s̶ ̶t̶f̶ ̶x̶ ̶=̶ ̶t̶f̶.̶p̶l̶a̶c̶e̶h̶o̶l̶d̶e̶r̶(̶s̶h̶a̶p̶e̶=̶[̶N̶o̶n̶e̶,̶ ̶2̶]̶,̶ ̶d̶t̶y̶p̶e̶=̶t̶f̶.̶f̶l̶o̶a̶t̶3̶2̶)̶
You can disable the v2 behavior by using the following code
This one is perfectly working for me.
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
x = tf.placeholder(shape=[None, 2], dtype=tf.float32)
I also got the same error. May be because of the version of tensorflow.
After installing tensorflow 1.4.0, I got relief from the error.
pip install tensorflow==1.4.0
If you are using TensorFlow 2.0, then some code developed for tf 1.x may not code work. Either you can follow the link : https://www.tensorflow.org/guide/migrate
or you can install a previous version of tf by
pip3 install tensorflow==version
Import the old version of tensorflow instead of the new version
[https://inneka.com/ml/tf/tensorflow-module-object-has-no-attribute-placeholder/][1]
import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()
You need to use the keras model with tensorflow 2, as here
import tensorflow as tf
from tensorflow.python.keras.layers import Input, Embedding, Dot, Reshape, Dense
from tensorflow.python.keras.models import Model
Recent version 2.0 does not support placeholder.
I uninstalled 2.0 using command: conda remove tensorflow.
then I installed 1.15.0 using command: conda install -c conda-forge tensorflow=1.15.0.
1.15 is latest in version 1 series. You can change as per you wish and requirement.
For seeing all version, use command: conda search tensorflow.
It worked for Anaconda3 in Windows.
Try this:
pip install tensorflow==1.14
or this (if you have GPU):
pip install tensorflow-gpu==1.14
Please take a look at the Migrate your TensorFlow 1 code to TensorFlow 2.
These codes:
import tensorflow as tf
tf_in = tf.placeholder("float", [None, A]) # Features
need to be migrated in TensorFlow 2 as below:
import tensorflow as tf
import tensorflow.compat.v1 as v1
tf_in = vi.placeholder("float", [None, A]) # Features
If you get this on tensorflow 2.0.0+, it's very likely because the code isn't compatible with the newer version of tensorflow.
To fix this, run the tf_upgrade_v2 script.
tf_upgrade_v2 --infile=YOUR_SCRIPT.py --outfile=YOUR_SCRIPT.py
Faced same issue on Ubuntu 16LTS when tensor flow was installed over existing python installation.
Workaround:
1.)Uninstall tensorflow from pip and pip3
sudo pip uninstall tensorflow
sudo pip3 uninstall tensorflow
2.)Uninstall python & python3
sudo apt-get remove python-dev python3-dev python-pip python3-pip
3.)Install only a single version of python(I used python 3)
sudo apt-get install python3-dev python3-pip
4.)Install tensorflow to python3
sudo pip3 install --upgrade pip
for non GPU tensorflow, run this command
sudo pip3 install --upgrade tensorflow
for GPU tensorflow, run below command
sudo pip3 install --upgrade tensorflow-gpu
Suggest not to install GPU and vanilla version of tensorflow
The error shows up because we are using tensorflow version 2 and the command is from version 1. So if we use:
tf.compat.v1.summary.(method_name)
It'll work
Because you cant use placeholder in tensflow2.0version, so you need to use tensflow1*, or you need to change your code to fix tensflow2.0
I had the same problem before after tried to upgrade tensorflow, I solved it by reinstalling Tensorflow and Keras.
pip uninstall tensorflow
pip uninstall keras
Then:
pip install tensorflow
pip install keras
The problem is with TensorFlow version; the one you are running is 2.0 or something above 1.5, while placeholder can only work with 1.4.
So simply uninstall TensorFlow, then install it again with version 1.4 and everything will work.
It may be the typo if you incorrectly wrote the placeholder word.
In my case I misspelled it as placehoder and got the error like this:
AttributeError: 'module' object has no attribute 'placehoder'