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Leer Challenge: Implementing Positional Encoding | Section
Transformer Architecture

bookChallenge: Implementing Positional Encoding

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Task

Implement get_positional_encoding — a function that precomputes the full positional encoding matrix for a given sequence length and embedding dimension.

The function should:

  1. Accept seq_len and d_model as arguments;
  2. Return a tensor of shape (seq_len, d_model) where each row is the encoding for one position;
  3. Apply sin to even indices and cos to odd indices using the sinusoidal formula from the previous chapter.

Run it with seq_len=10 and d_model=16, print the resulting tensor, and inspect how the values change across positions and dimensions. Then create a random embedding tensor of shape (10, 16) and add the positional encoding to it to confirm the shapes are compatible.

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