You can design a NAS pipeline to optimize the Transformer block for text generation by searching over architectural variants using a controller model and reinforcement learning.
Here is the code snippet below:

In the above code, we are using the following key points:
- 
search_space defines different Transformer configurations. 
- 
sample_architecture picks random combinations for exploration. 
- 
evaluate_architecture provides a placeholder for model training and scoring. 
Hence, this pipeline helps automatically discover efficient Transformer designs tailored for text generation.