Fixed inconsistency vs tensor impl

torchvision/transforms/v2/functional/_geometry.py

@@ -604,14 +604,15 @@ def _compute_affine_output_size_python(matrix: List[float], w: int, h: int) -> T
     min_val_y = min(new_pts_y) + half_h
     max_val_y = max(new_pts_y) + half_h
 
-    # Truncate precision to 1e-4 to avoid ceil of Xe-15 to 1.0
+    # Truncate precision to 1e-4 to avoid ceil of Xe-15 to 1.0 instead of 0.0
+    # Adding +1 in int(min_val * inv_tol + 1) to avoid floor of X.9999 to X instead of X+1
     tol = 1e-4
     inv_tol = 1.0 / tol
 
     cmax_x = math.ceil(int(max_val_x * inv_tol) * tol)
     cmax_y = math.ceil(int(max_val_y * inv_tol) * tol)
-    cmin_x = math.floor(int(min_val_x * inv_tol) * tol)
-    cmin_y = math.floor(int(min_val_y * inv_tol) * tol)
+    cmin_x = math.floor(int(min_val_x * inv_tol + 1) * tol)
+    cmin_y = math.floor(int(min_val_y * inv_tol + 1) * tol)
 
     size_x = cmax_x - cmin_x
     size_y = cmax_y - cmin_y