Final answer:
If encountering attributeerror: module 'tensorflow' has no attribute 'placeholder' error, update tensorflow to version 2.x and replace placeholder with the function decorator.
Step-by-step explanation:
Encountering the "attributeerror: module 'tensorflow' has no attribute 'placeholder'" error signals the use of an outdated tensorflow version.
This issue arises due to the removal of the placeholder functionality in tensorflow 2.0, replaced by the function decorator.
In tensorflow 1x, the placeholder function defined data input points for the graph, but this is obsolete in tensorflow 2x.
To resolve this error, ensure we have updated tensorflow to version 2x.
Instead of using placeholder, integrate the function decorator into your code, transforming it into a graph-like function.
Directly pass input arguments to this decorated function, eliminating the need for the placeholder.
This solution aligns with tensorflow evolution, allowing seamless compatibility with the updated version's features while resolving the attributeerrror associated with outdated coding practices.