Attributeerror: Module ‘tensorflow’ has no attribute ‘placeholder’

In this TensorFlow tutorial, I will explain how to resolve the error Attributeerror: Module ‘tensorflow’ has no attribute ‘placeholder’.

When I upgraded my TensorFlow version from 1.x to 2.x, I got this error, so I have found two solutions to fix it. In this tutorial, I have explained both solutions to fix that error.

Attributeerror: Module ‘tensorflow’ has no attribute ‘placeholder’

The error ‘Attributeerror: Module ‘tensorflow’ has no attribute ‘placeholder” means you are trying to use the TensorFlow’s placeholder() function in Tensorflow version 2.x.x.

The placeholder() was used to declare inputs in the computational graph in Tensorflow version 1.x.x, but it has been removed in TensorFlow 2.x.x as part of the library move towards eager execution.

Let me show you an example of how this error can occur.

import tensorflow as tf

x = tf.placeholder(tf.float32, shape=(None, 224, 224, 3))
Attributeerror Module 'tensorflow' has no attribute 'placeholder'

Look, you get the error when you execute the above code using the tensorflow version 2.x.

The reason is that you have updated your tensorflow version to 2.xx something, and your code is using old ways to access the placeholder() function.

It has two solutions, which are shown in the following steps:

First, you can use tensorflow.compat.v1 and disable the behaviour of tensorflow version 2, as shown below.

import tensorflow.compat.v1 as tf
tf.disable_v2_behavior()

Here this line import tensorflow.compat.v1 as tf imports the tensorlfow version 1 module. Then tf.disable_v2_behavior() disables the tensorflow version 2 behaviour, enabling compatibility with Tensorflow version 1 within the current session.

By doing this, if you use the tensorflow version 1 API in your code, it will work.

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Then, use the placeholder() function, and it will work.

x = tf.placeholder(tf.float32, shape=(None, 224, 224, 3))
print(x)
First Solution to Attributeerror Module 'tensorflow' has no attribute 'placeholder'

Look now tf.placeholder() function works and creates a placeholder of type float32.

The second solution is to use the tf.Variable() instead of tf.placeholder(). That means creating an empty variable using the Variable() function of the tensorflow and later assigning value to it.

For example, use the code below to create an empty variable of type float32 containing a list of values.

x1 = tf.Variable([], dtype=tf.float32)

print(x1)
Second Solution to Attributeerror Module 'tensorflow' has no attribute 'placeholder'

Successfully created a variable x1 of type float32. Later, you can assign a value to this variable.

This is how to fix the error Attributeerror: Module ‘tensorflow’ has no attribute ‘placeholder’.

Conclusion

In this TensorFlow tutorial, you learned how to resolve the error Attributeerror: Module ‘tensorflow’ has no attribute ‘placeholder’.

While solving the error, you learned two methods. One was where you disabled the tensorflow version 2 behaviour and enabled the tensorflow version 1 in the current session.

second, where you learn how to use the tf.Variable() function instead of tf.placeholder() in tensorflow.

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