ncnn settings

backend/src/api.py

@@ -12,10 +12,8 @@
     NewType,
     Optional,
     Tuple,
-    Type,
     TypedDict,
     TypeVar,
-    cast,
 )
 
 from sanic.log import logger
@@ -33,7 +31,7 @@
 from nodes.base_input import BaseInput
 from nodes.base_output import BaseOutput
 from nodes.group import Group, GroupId, NestedGroup, NestedIdGroup
-from nodes.utils.exec_options import PackageExecutionOptions, get_execution_options
+from nodes.utils.exec_options import get_execution_options
 
 KB = 1024**1
 MB = 1024**2

backend/src/nodes/impl/ncnn/session.py

@@ -16,9 +16,7 @@
 from .model import NcnnModelWrapper
 
 
-def create_ncnn_net(
-    model: NcnnModelWrapper, exec_options: ExecutionOptions
-) -> ncnn.Net:
+def create_ncnn_net(model: NcnnModelWrapper, gpu_index: int) -> ncnn.Net:
     net = ncnn.Net()
 
     if model.fp == "fp16":
@@ -33,7 +31,7 @@ def create_ncnn_net(
     if use_gpu:
         # Use vulkan compute
         net.opt.use_vulkan_compute = True
-        net.set_vulkan_device(exec_options.ncnn_gpu_index)
+        net.set_vulkan_device(gpu_index)
 
     # Load model param and bin
     if use_gpu:
@@ -56,9 +54,9 @@ def create_ncnn_net(
 __session_cache: WeakKeyDictionary[NcnnModelWrapper, ncnn.Net] = WeakKeyDictionary()
 
 
-def get_ncnn_net(model: NcnnModelWrapper, exec_options: ExecutionOptions) -> ncnn.Net:
+def get_ncnn_net(model: NcnnModelWrapper, gpu_index: int) -> ncnn.Net:
     cached = __session_cache.get(model)
     if cached is None:
-        cached = create_ncnn_net(model, exec_options)
+        cached = create_ncnn_net(model, gpu_index)
         __session_cache[model] = cached
     return cached

backend/src/packages/chaiNNer_ncnn/__init__.py

@@ -1,6 +1,6 @@
 from sanic.log import logger
 
-from api import MB, Dependency, DropdownSetting, add_package
+from api import MB, Dependency, add_package
 from system import is_arm_mac, is_mac
 
 general = "NCNN uses .bin/.param models to upscale images."
@@ -39,27 +39,6 @@
     color="#ED64A6",
 )
 
-if not is_arm_mac:
-    gpu_list = []
-    try:
-        from ncnn_vulkan import ncnn
-
-        for i in range(ncnn.get_gpu_count()):
-            gpu_list.append(ncnn.get_gpu_info(i).device_name())
-    except:
-        gpu_list.append("cpu")
-
-    package.add_setting(
-        DropdownSetting(
-            label="NCNN GPU",
-            key="gpu",
-            description="Which GPU to use for NCNN. This is only relevant if you have multiple GPUs.",
-            options=[{"label": x, "value": str(i)} for i, x in enumerate(gpu_list)],
-            default="0",
-            disabled=len(gpu_list) <= 1,
-        )
-    )
-
 ncnn_category = package.add_category(
     name="NCNN",
     description="Nodes for using the NCNN Neural Network Framework with images.",

backend/src/packages/chaiNNer_ncnn/ncnn/processing/upscale_image.py

@@ -27,10 +27,10 @@
 from nodes.impl.upscale.tiler import MaxTileSize
 from nodes.properties.inputs import ImageInput, NcnnModelInput, TileSizeDropdown
 from nodes.properties.outputs import ImageOutput
-from nodes.utils.exec_options import get_execution_options
 from nodes.utils.utils import get_h_w_c
 from system import is_mac
 
+from ...settings import get_settings
 from .. import processing_group
 
 
@@ -66,12 +66,12 @@ def upscale_impl(
     output_name: str,
     tile_size: TileSize,
 ):
-    exec_options = get_execution_options()
-    net = get_ncnn_net(model, exec_options)
+    settings = get_settings()
+    net = get_ncnn_net(model, settings.gpu_index)
     # Try/except block to catch errors
     try:
         if use_gpu:
-            vkdev = ncnn.get_gpu_device(exec_options.ncnn_gpu_index)
+            vkdev = ncnn.get_gpu_device(settings.gpu_index)
 
             def estimate_gpu():
                 if is_mac:

backend/src/packages/chaiNNer_ncnn/settings.py

@@ -0,0 +1,46 @@
+from dataclasses import dataclass
+
+try:
+    from ncnn_vulkan import ncnn
+
+    use_gpu = True
+except ImportError:
+    from ncnn import ncnn
+
+    use_gpu = False
+
+from api import DropdownSetting
+from system import is_arm_mac
+
+from . import package
+
+if not is_arm_mac and use_gpu:
+    try:
+        gpu_list = []
+        for i in range(ncnn.get_gpu_count()):
+            gpu_list.append(ncnn.get_gpu_info(i).device_name())
+
+        package.add_setting(
+            DropdownSetting(
+                label="GPU",
+                key="gpu_index",
+                description="Which GPU to use for NCNN. This is only relevant if you have multiple GPUs.",
+                options=[{"label": x, "value": str(i)} for i, x in enumerate(gpu_list)],
+                default="0",
+                disabled=len(gpu_list) <= 1,
+            )
+        )
+    except:
+        pass
+
+
+@dataclass
+class NcnnSettings:
+    gpu_index: int
+
+
+def get_settings() -> NcnnSettings:
+    raw = package.get_execution_settings()
+    return NcnnSettings(
+        gpu_index=int(raw.get("gpu_index", 0)),
+    )