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Related Questions
- How do self-attention mechanisms allow for parallelization of different input elements, and how does this impact the computational efficiency of the model?
- What are the key differences in parallelization strategies between self-attention and CNNs, and how do they affect the performance of each model?
- How does the sequential processing of CNNs impact its parallelization capabilities compared to self-attention mechanisms?
- Can you explain the concept of 'independence' in self-attention and how it relates to parallelization?
- What are the implications of parallelization on the training time and computational resources required for each model?
- How do the parallelization strategies of self-attention and CNNs influence the model's ability to generalize to new, unseen data?
- What are some common techniques used to optimize the parallelization of self-attention and CNNs, and how do they improve model performance?
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