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:
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search_space defines different Transformer configurations.
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sample_architecture picks random combinations for exploration.
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evaluate_architecture provides a placeholder for model training and scoring.
Hence, this pipeline helps automatically discover efficient Transformer designs tailored for text generation.