A highway layer combines the two ideas: a nonlinear transform, and a learned gate that decides between transforming and carrying the input. Stacking many such layers trains as easily as a shallow network, which is the paper's main point.
Implement highway_layer(x, W_h, b_h, W_t, b_t), which computes H(x) with tanh, the gate T(x) with the sigmoid, and returns the blended output.
W_h and W_t are (D, D).x.Build the transform and gate with the same affine maps as before, then reuse the blend formula.
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