fix circular imports

api/onnx_web/params.py

@@ -591,3 +591,20 @@ class HighresParams:
             method=coalesce(method, self.method),
             iterations=coalesce(iterations, self.iterations),
         )
+
+
+def get_size(val: Union[int, str, None]) -> Union[int, SizeChart]:
+    if val is None:
+        return SizeChart.auto
+
+    if type(val) is int:
+        return val
+
+    if type(val) is str:
+        for size in SizeChart:
+            if val == size.name:
+                return size
+
+        return int(val)
+
+    raise ValueError("invalid size")

api/onnx_web/utils.py

@@ -1,20 +1,15 @@
-import gc
 import importlib
 import json
-import threading
 from hashlib import sha256
 from json import JSONDecodeError
 from logging import getLogger
 from os import environ, path
 from platform import system
 from struct import pack
-from typing import Any, Dict, List, Optional, Sequence, TypeVar, Union
+from typing import Any, Dict, List, Optional, Sequence, TypeVar
 
-import torch
 from yaml import safe_load
 
-from .params import DeviceParams, Param, SizeChart
-
 logger = getLogger(__name__)
 
 SAFE_CHARS = "._-"
@@ -95,43 +90,14 @@ def get_not_empty(args: Any, key: str, default: TElem) -> TElem:
     return val
 
 
-def get_size(val: Union[int, str, None]) -> Union[int, SizeChart]:
-    if val is None:
-        return SizeChart.auto
+def run_gc(devices: Optional[List[Any]] = None):
+    """
+    Deprecated, use `onnx_web.device.run_gc` instead.
+    """
+    from .device import run_gc as run_gc_impl
 
-    if type(val) is int:
-        return val
-
-    if type(val) is str:
-        for size in SizeChart:
-            if val == size.name:
-                return size
-
-        return int(val)
-
-    raise ValueError("invalid size")
-
-
-def run_gc(devices: Optional[List[DeviceParams]] = None):
-    logger.debug(
-        "running garbage collection with %s active threads", threading.active_count()
-    )
-    gc.collect()
-
-    if torch.cuda.is_available() and devices is not None:
-        for device in [d for d in devices if d.device.startswith("cuda")]:
-            logger.debug("running Torch garbage collection for device: %s", device)
-            with torch.cuda.device(device.torch_str()):
-                torch.cuda.empty_cache()
-                torch.cuda.ipc_collect()
-                mem_free, mem_total = torch.cuda.mem_get_info()
-                mem_pct = (1 - (mem_free / mem_total)) * 100
-                logger.debug(
-                    "CUDA VRAM usage: %s of %s (%.2f%%)",
-                    (mem_total - mem_free),
-                    mem_total,
-                    mem_pct,
-                )
+    logger.debug("calling deprecated run_gc, please use onnx_web.device.run_gc instead")
+    run_gc_impl(devices)
 
 
 def sanitize_name(name):
@@ -238,9 +204,9 @@ def hash_file(name: str):
     return sha.hexdigest()
 
 
-def hash_value(sha, param: Optional[Param]):
+def hash_value(sha, param: Optional[Any]):
     if param is None:
-        return
+        return None
     elif isinstance(param, bool):
         sha.update(bytearray(pack("!B", param)))
     elif isinstance(param, float):