feat: harden local runtime and verification

installer/scripts/setup.sh

@@ -0,0 +1,38 @@
+#!/usr/bin/env bash
+set -euo pipefail
+set +x
+
+cd "$(dirname "${BASH_SOURCE[0]}")/../.."
+
+uv sync --locked --extra spaces --extra dev --no-editable
+
+enable_cuda="${ENABLE_CUDA:-auto}"
+if [[ "$enable_cuda" != "false" ]] && command -v nvidia-smi >/dev/null 2>&1; then
+  torch_version="$(.venv/bin/python -c 'import torch; print(torch.__version__.split("+", 1)[0])')"
+  UV_TORCH_BACKEND=cu130 uv pip install \
+    --python .venv/bin/python \
+    --reinstall-package torch \
+    "torch==$torch_version"
+fi
+
+uv pip check --python .venv/bin/python
+.venv/bin/python - <<'PY'
+import shutil
+import torch
+
+if torch.cuda.is_available():
+    probe = torch.arange(16, device="cuda", dtype=torch.float32).square().sum()
+    assert probe.device.type == "cuda"
+    torch.backends.cudnn.enabled = False
+    torch.backends.cuda.enable_cudnn_sdp(False)
+    conv_input = torch.randn(1, 8, 32, device="cuda", dtype=torch.float16)
+    conv_weight = torch.randn(8, 8, 3, device="cuda", dtype=torch.float16)
+    convolution = torch.nn.functional.conv1d(conv_input, conv_weight)
+    q = torch.randn(1, 2, 32, 16, device="cuda", dtype=torch.float16)
+    attention = torch.nn.functional.scaled_dot_product_attention(q, q, q, is_causal=True)
+    torch.cuda.synchronize()
+    assert convolution.device.type == "cuda" and torch.isfinite(convolution).all()
+    assert attention.device.type == "cuda" and torch.isfinite(attention).all()
+elif shutil.which("nvidia-smi"):
+    raise SystemExit("NVIDIA hardware detected but the installed PyTorch runtime cannot use CUDA")
+PY