#contiguous

Multi-head attention ends by merging the heads back into one dimension:

b, num_tokens, num_heads, head_dim = 2, 6, 3, 4
context = torch.randn(b, num_heads, num_tokens, head_dim)   # attn_weights @ values
out = context.transpose(1, 2).view(b, num_tokens, num_heads * head_dim)

What happens on the last line?