TensorFlow, "'module' object has no attribute 'placeholder'"

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:

1. The directory containing the input script (or the current directory when no file is specified).

2. PYTHONPATH (a list of directory names,
   with the same syntax as the shell variable PATH).

3. The installation-dependent default.

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

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'

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

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()

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

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

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

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.

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()

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.

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

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)

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

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.

Try this:

pip install tensorflow==1.14

or this (if you have GPU):

pip install tensorflow-gpu==1.14

import tensorflow.compat.v1 as tf

tf.disable_v2_behavior() 

works.
I am using Python 3.7 and tensorflow 2.0.

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

There have been many suggestions and some of them did work. But I would rather convert v1 tf project to v2 project for better maintenance. I am surprised no one suggested it here:

$tf_upgrade_v2 
--intree my_project/ 
--outtree my_project_v2/ 
--reportfile report.txt 

I copied pasted from this stack overflow answer: AttributeError: module ‘tensorflow’ has no attribute ‘get_variable’

You do need to inspect the report.txt and make sure it does what you would expect.

Different type of solution in the below URL,
https://www.datasciencelearner.com/attributeerror-module-tensorflow-has-no-attribute-placeholder/

It looks like you’re trying to use TensorFlow 2.x syntax with TensorFlow 1.x. The error message you’re encountering indicates that TensorFlow 2.13 doesn’t have a ‘placeholder’ attribute.

In TensorFlow 2.x, you should use the tf.Variable or tf.constant for creating tensors with specific values, and placeholders are not used anymore. Instead, you can use regular Python variables.

Here’s how you can modify your code to work with TensorFlow 2.x:

import tensorflow as tf
tf_in = tf.Variable( [None, A], dtype=tf.float32)