NCA-GENM Exam Dumps | You are building a conditional GAN (cGAN) to generate images conditioned on text descriptions. The generator

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Question 32/192

You are building a conditional GAN (cGAN) to generate images conditioned on text descriptions. The generator takes a noise vector and a text embedding as input. Which of the following approaches would be most effective for combining the noise vector and text embedding before feeding them into the generator's first layer?

A. Concatenating the noise vector and text embedding directly.

B. Adding the noise vector and text embedding element-wise.

C. Applying a learned linear transformation to both the noise vector and text embedding, then concatenating the results.

D. Treating the text embedding as a set of attention weights applied to the noise vector.

E. Using a cross-attention mechanism where the noise vector attends to the text embedding.

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