Remove hardcoded torch.cuda references from the webui backend code

ui/easydiffusion/backends/webui/__init__.py

@@ -10,6 +10,8 @@ import shutil
 from easydiffusion.app import ROOT_DIR, getConfig
 from easydiffusion.model_manager import get_model_dirs
 from easydiffusion.utils import log
+from torchruntime.utils import get_device, get_device_name, get_installed_torch_platform
+from sdkit.utils import is_cpu_device
 
 from . import impl
 from .impl import (
@@ -93,7 +95,9 @@ def install_backend():
 
     # install cpu-only torch if the PC doesn't have a graphics card (for Windows and Linux).
     # this avoids WebUI installing a CUDA version and trying to activate it
-    if OS_NAME in ("Windows", "Linux") and not has_discrete_graphics_card():
+
+    torch_platform_name = get_installed_torch_platform()[0]
+    if OS_NAME in ("Windows", "Linux") and is_cpu_device(torch_platform_name):
         run_in_conda(["python", "-m", "pip", "install", "torch", "torchvision"], cwd=WEBUI_DIR, env=env)
 
 
@@ -296,7 +300,8 @@ def create_context():
     context = local()
 
     # temp hack, throws an attribute not found error otherwise
-    context.device = "cuda:0"
+    context.torch_device = get_device(0)
+    context.device = f"{context.torch_device.type}:{context.torch_device.index}"
     context.half_precision = True
     context.vram_usage_level = None
 
@@ -379,17 +384,16 @@ def get_env():
         else:
             env_entries["TORCH_COMMAND"] = ["pip install torch==2.3.1 torchvision==0.18.1"]
     else:
-        import torch
+        from easydiffusion.device_manager import needs_to_force_full_precision
-        from easydiffusion.device_manager import needs_to_force_full_precision, is_cuda_available
+
+        torch_platform_name = get_installed_torch_platform()[0]
 
         vram_usage_level = config.get("vram_usage_level", "balanced")
-        if config.get("render_devices", "auto") == "cpu" or not has_discrete_graphics_card() or not is_cuda_available():
+        if config.get("render_devices", "auto") == "cpu" or is_cpu_device(torch_platform_name):
             env_entries["COMMANDLINE_ARGS"][0] += " --always-cpu"
         else:
-            c = local()
+            device = get_device(0)
-            c.device_name = torch.cuda.get_device_name()
+            if needs_to_force_full_precision(get_device_name(device)):
-
-            if needs_to_force_full_precision(c):
                 env_entries["COMMANDLINE_ARGS"][0] += " --no-half --precision full"
 
             if vram_usage_level == "low":
@@ -407,48 +411,6 @@ def get_env():
     return env
 
 
-def has_discrete_graphics_card():
-    system = OS_NAME
-
-    if system == "Windows":
-        try:
-            env = dict(os.environ)
-            env["PATH"] += os.pathsep + "C:/Windows/System32/WindowsPowerShell/v1.0".replace("/", os.path.sep)
-
-            # PowerShell command to get the names of graphics cards
-            command = [
-                "powershell",
-                "-Command",
-                "(Get-WmiObject Win32_VideoController).Name",
-            ]
-            # Run the command and decode the output
-            output = subprocess.check_output(command, universal_newlines=True, stderr=subprocess.STDOUT, env=env)
-            # Filter for discrete graphics cards (NVIDIA, AMD, etc.)
-            discrete_gpus = ["NVIDIA", "AMD", "ATI"]
-            return any(gpu in output for gpu in discrete_gpus)
-        except subprocess.CalledProcessError:
-            return False
-
-    elif system == "Linux":
-        try:
-            output = subprocess.check_output(["lspci"], stderr=subprocess.STDOUT)
-            # Check for discrete GPUs (NVIDIA, AMD)
-            discrete_gpus = ["NVIDIA", "AMD", "Advanced Micro Devices"]
-            return any(gpu in line for line in output.decode().splitlines() for gpu in discrete_gpus)
-        except subprocess.CalledProcessError:
-            return False
-
-    elif system == "Darwin":  # macOS
-        try:
-            output = subprocess.check_output(["system_profiler", "SPDisplaysDataType"], stderr=subprocess.STDOUT)
-            # Check for discrete GPU in the output
-            return "NVIDIA" in output.decode() or "AMD" in output.decode()
-        except subprocess.CalledProcessError:
-            return False
-
-    return False
-
-
 # https://stackoverflow.com/a/25134985
 def kill(proc_pid):
     process = psutil.Process(proc_pid)