fix(synthesis): handle 3-D DEM from _read_dem_patch (it returns (1,H,W))

The 400 from /v1/terramind on synthesis came from the wire shape being
(1,1,1,224,224) 5-D instead of (1,1,224,224) 4-D. Root cause: HF's
_read_dem_patch returns a 3-D (1, H, W) array (it interpolates via
torch.functional.interpolate then .squeeze(0).numpy()), and the
synthesis remote-call site assumed it was 2-D and added two leading
dims via dem[None, None, :, :].

Branch on dem_arr.ndim and add exactly the dim(s) we need to reach
4-D (B, C, H, W). Also leave the debug log on the droplet so any
future dim-shape mismatch surfaces in container logs.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app/context/terramind_synthesis.py

@@ -294,7 +294,22 @@ def fetch(lat: float, lon: float, timeout_s: float = 60.0) -> dict[str, Any]:
                 # layer unpacks `B, C, H, W = x.shape` (verified against
                 # terratorch_terramind_v1_base_generate). DEM has C=1, so
                 # the on-the-wire shape is (1, 1, H, W) 4-D.
-                dem_remote = dem[None, None, :, :].astype("float32")
+                # `_read_dem_patch` returns a 3-D (1, H, W) array (it
+                # interpolates to CHIP_PX×CHIP_PX through a 4-D
+                # torch.functional.interpolate then squeezes the batch),
+                # so we add only the batch dim — not two.
+                import numpy as _np_local
+                dem_arr = _np_local.asarray(dem, dtype="float32")
+                if dem_arr.ndim == 2:                # (H, W)
+                    dem_remote = dem_arr[None, None, :, :]
+                elif dem_arr.ndim == 3:              # (1, H, W)
+                    dem_remote = dem_arr[None, :, :, :]
+                elif dem_arr.ndim == 4:              # already (1, 1, H, W)
+                    dem_remote = dem_arr
+                else:
+                    raise ValueError(
+                        f"unexpected DEM shape {dem_arr.shape}; "
+                        "expected 2/3/4-D")
                 remote = _inf.terramind("synthesis", None, None, dem_remote,
                                           timeout=timeout_s)
                 if remote.get("ok"):

services/riprap-models/main.py

@@ -379,7 +379,13 @@ def _terramind_synthesis_inference(payload: TerramindIn) -> dict[str, Any]:
     DEM tensor, and emits a class-logit raster keyed by the ESRI
     2020 LULC tokenizer codebook."""
     t0 = time.time()
+    log.info("terramind/synthesis: payload dem=%s dem_shape=%s s2=%s",
+             "set" if payload.dem else "None",
+             payload.dem_shape,
+             "set" if payload.s2 else "None")
     if not payload.dem or not payload.dem_shape:
+        log.warning("terramind/synthesis: missing dem (dem=%s, shape=%s)",
+                    bool(payload.dem), payload.dem_shape)
         raise HTTPException(status_code=400,
                             detail="synthesis requires `dem` + `dem_shape`")
     model = _load_terramind_synthesis()