Ann Live Com [cracked] — Julia

# ---------------------------------------------------- # 1. Define a simple model (GPU‑aware) # ---------------------------------------------------- model = Chain( Dense(128, 64, relu), Dense(64, 10), # 10‑class output ) |> gpu # move parameters to the GPU

# ---------------------------------------------------- # 2. Inference function # ---------------------------------------------------- function predict(json_msg::String) # Expect: "x": [0.1, 0.2, …, 0.128] payload = JSON.parse(json_msg) x = Float32.(payload["x"]) |> gpu y = model(x) # GPU forward pass prob = softmax(y) |> cpu # back to CPU for serialization return JSON.json(Dict("prob" => vec(prob))) end julia ann live com

# ---------------------------------------------------- # 4. Start the server (in a background task) # ---------------------------------------------------- @async run_ws(8081) # ---------------------------------------------------- # 1