From f3708f8449739fdc9d3a4194ffdd561f48b6ec17 Mon Sep 17 00:00:00 2001
From: Antoine Jacquin <lidar@arkel.fr>
Date: Fri, 18 Sep 2026 21:23:39 +0200
Subject: [PATCH] Journaliser les replis CPU du GPU et retirer une copie VRAM
 inutile

---
 lidar_pipeline/gpu.py            | 17 ++++++++++++-----
 lidar_pipeline/visualizations.py |  3 ++-
 2 files changed, 14 insertions(+), 6 deletions(-)

diff --git a/lidar_pipeline/gpu.py b/lidar_pipeline/gpu.py
index 88c6b92..50c2efa 100644
--- a/lidar_pipeline/gpu.py
+++ b/lidar_pipeline/gpu.py
@@ -355,7 +355,10 @@ def to_gpu(arr):
     if _gpu_available():
         try:
             return _cp.asarray(arr.astype(np.float32))
-        except Exception:
+        except Exception as e:
+            # L'erreur d'origine (souvent OOM) ne doit pas être avalée :
+            # sans elle, un repli CPU est indissociable d'un simple bug.
+            logger.warning(f"Transfert GPU échoué ({e}) — repli CPU pour ce calcul")
             disable_gpu()
     return arr.astype(np.float32)
 
@@ -386,7 +389,8 @@ def xp_gaussian_filter(arr, sigma):
     if _cp is not None and isinstance(arr, _cp.ndarray):
         try:
             return _cp_ndimage.gaussian_filter(arr, sigma)
-        except Exception:
+        except Exception as e:
+            logger.warning(f"Filtre gaussien GPU échoué ({e}) — repli CPU")
             arr = to_cpu(arr)
     return ndimage.gaussian_filter(arr, sigma)
 
@@ -395,7 +399,8 @@ def xp_uniform_filter(arr, size):
     if _cp is not None and isinstance(arr, _cp.ndarray):
         try:
             return _cp_ndimage.uniform_filter(arr, size)
-        except Exception:
+        except Exception as e:
+            logger.warning(f"Filtre uniform GPU échoué ({e}) — repli CPU")
             arr = to_cpu(arr)
     return ndimage.uniform_filter(arr, size)
 
@@ -404,7 +409,8 @@ def xp_minimum_filter(arr, footprint=None, size=None):
     if _cp is not None and isinstance(arr, _cp.ndarray):
         try:
             return _cp_ndimage.minimum_filter(arr, footprint=footprint, size=size)
-        except Exception:
+        except Exception as e:
+            logger.warning(f"Filtre minimum GPU échoué ({e}) — repli CPU")
             arr = to_cpu(arr)
     return ndimage.minimum_filter(arr, footprint=footprint, size=size)
 
@@ -413,7 +419,8 @@ def xp_maximum_filter(arr, footprint=None, size=None):
     if _cp is not None and isinstance(arr, _cp.ndarray):
         try:
             return _cp_ndimage.maximum_filter(arr, footprint=footprint, size=size)
-        except Exception:
+        except Exception as e:
+            logger.warning(f"Filtre maximum GPU échoué ({e}) — repli CPU")
             arr = to_cpu(arr)
     return ndimage.maximum_filter(arr, footprint=footprint, size=size)
 
diff --git a/lidar_pipeline/visualizations.py b/lidar_pipeline/visualizations.py
index 7daaa83..7470d5c 100644
--- a/lidar_pipeline/visualizations.py
+++ b/lidar_pipeline/visualizations.py
@@ -460,7 +460,8 @@ def generate_hillshade(dem_file, basename, vis_dir, resolution, shared=None):
         if shared:
             transform = shared.transform
             crs = shared.crs
-            dem = to_gpu(shared.dem_np)
+            # Pas de copie GPU du DEM brut ici : seuls gradient/pente/aspect
+            # servent (déjà partagés) — ~100 Mo de VRAM économisés par dalle
             dy = to_gpu(shared.dy) if _gpu_mod.HAS_GPU else shared.dy
             dx = to_gpu(shared.dx) if _gpu_mod.HAS_GPU else shared.dx
             slope = to_gpu(shared.slope_rad) if _gpu_mod.HAS_GPU else shared.slope_rad