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.
I've updated the torch version in my SageMaker pytorch_36 kernel to torch version 1.0.0. I then tried running the example notebook pytorch_torchvision_neo.ipynb, also changing the framework_version to 1.0.0. Neo compilation then fails.
Any idea why it isn't working with 1.0.0? The console error message actually tells me to make sure I'm using 1.0.0, but the example notebook seems to only work with 0.4.0.
Sagemaker notebook has pytorch-1.1.0 pre-installed.
But Model Compilation service expects model saved by pytorch-0.4.0 or pytorch-1.0.1
Solution to the issue:
# 1. do not install `pytorch-cpu` and `torchvision-cpu`.
# 2. Downgrade pytorch version to 1.0.1
!conda install -y pytorch=1.0.1 -c pytorch
# 3. import pytorch and check that version is 1.0.1 (but not 1.1.0)
import torch
torch.__version__
Continue to run notebook steps: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/sagemaker_neo_compilation_jobs/pytorch_torchvision/pytorch_torchvision_neo.ipynb
I'm trying to run object detection API's object_detection_tutorial.ipynb and I was able to run it before and i trained some simple models for object detection. I think broke my installation. I'm using Anaconda+Windows and Tensorflow 1.4 installed on an environment called "neuralnets" here is pip list of this environment:
pip list
error:
error
if in your Python console you type:
import tensorflow as tf
tf.__Version__
What do you get? just to make sure try to reinstall with the --ignore-installed flag:
pip install --ignore-installed tensorflow=1.4
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'