"""Frozen render protocol values shared by active benchmark entrypoints.""" STANDARD_IMAGE_SIZE = 320 STANDARD_DISPLAY_SIZE = (STANDARD_IMAGE_SIZE, STANDARD_IMAGE_SIZE) STANDARD_POINT_BATCH_SIZE = 100_000 STANDARD_CANDIDATE_BATCH_SIZE = 256 STANDARD_PANEL_SEPARATOR = 6 STANDARD_PANEL_SEPARATOR_VALUE = 12 RENDER_PARAMETER_SCHEMA = { "image_size": [STANDARD_IMAGE_SIZE, STANDARD_IMAGE_SIZE], "projection_scale_reference": 64.0, "geometry_point_sampling": { "svg_max_points_per_icon": 90000, "cuda_point_batch_size": STANDARD_POINT_BATCH_SIZE, "beam_candidate_batch_size": STANDARD_CANDIDATE_BATCH_SIZE, }, "accelerated_mask_fill": "solid_geometry_disk_splat", "python_fallback_display_fill_holes": False, "python_fallback_evaluation_fill_holes": True, "mask_morphology": { "operation": "MORPH_CLOSE", "kernel": "ELLIPSE", "kernel_size": [3, 3], "iterations": 1, }, "oblique_blur": {"operation": "GaussianBlur", "kernel_size": [3, 3], "passes": 2}, "renderer_backend_policy": "cuda_then_existing_cpu_fallback", "formal_entrypoint_backend_requirement": "cuda", "panel_separator_pixels": STANDARD_PANEL_SEPARATOR, "panel_separator_value": STANDARD_PANEL_SEPARATOR_VALUE, } def require_standard_square_size(value, *, name="image_size"): """Reject protocol drift instead of silently rendering a different size.""" if isinstance(value, (tuple, list)): actual = tuple(int(item) for item in value) expected = STANDARD_DISPLAY_SIZE else: actual = int(value) expected = STANDARD_IMAGE_SIZE if actual != expected: raise ValueError(f"{name} is frozen at 320x320; got {actual!r}") return value def require_cuda_backend(actual_backend, *, context="formal renderer"): if actual_backend != "cuda": raise RuntimeError( f"{context} requires CUDA rendering; actual backend={actual_backend!r}. " "Run with the proj environment and a CUDA-capable GPU." )