Evaluate the engineer's implementation against the standard design of the position-wise feed-forward network. Identify the two errors in how parameters are distributed across token positions and layers, and explain how the weights must actually be configured.
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Prep Sessions
Foundational Deep Learning Architectures: Transformers and Residual Networks @ University of Michigan - Ann Arbor
Ch.1 Transformer Architecture and Components - Foundational Deep Learning Architectures: Transformers and Residual Networks @ University of Michigan - Ann Arbor
Position-Wise Feed-Forward Networks - Foundational Deep Learning Architectures: Transformers and Residual Networks @ University of Michigan - Ann Arbor
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Match each architectural property or interpretation of the position-wise feed-forward network to its corresponding description.
Evaluate the engineer's implementation against the standard design of the position-wise feed-forward network. Identify the two errors in how parameters are distributed across token positions and layers, and explain how the weights must actually be configured.