Fixed hardware acceleration detection to not throw error on CUDA env,…

… improved README

README.md

@@ -18,24 +18,24 @@ The primary stem typically contains the instrumental part of the audio, while th
 
 ## Installation 🛠️
 
-You can install Audio Separator using pip, use one of the following depending on your device:
+You'll need `ffmpeg` and `libsndfile`, which should be easy to install on most platforms, e.g.:
 
-Nvidia GPU with CUDA support:
-`pip install audio-separator[gpu]`
+- Debian/Ubuntu: `apt-get update; apt-get install -y libsndfile1-dev ffmpeg`
+- macOS: `brew update; brew install libsndfile ffmpeg`
 
-Apple Silicon running macOS Sonoma+ with CoreML support: 
-`pip install audio-separator[silicon]`
+You can then install Audio Separator using pip, use one of the following to install the correct onnxruntime dependency for your device:
+
+### Nvidia GPU with CUDA acceleration:
 
-No specific hardware acceleration, CPU only, slow
-`pip install audio-separator`
+`pip install audio-separator[gpu]`
 
-### Requirements
+### Apple Silicon, macOS Sonoma+ with CoreML acceleration: 
 
-You'll need two other things installed on your system: `ffmpeg` and `libsndfile`.
-These should be easy to install on most platforms, e.g.
+`pip install audio-separator[silicon]`
 
-- Debian/Ubuntu: `apt-get update; apt-get install -y libsndfile1-dev ffmpeg`
-- macOS: `brew update; brew install libsndfile ffmpeg`
+### No hardware acceleration, CPU only:
+
+`pip install audio-separator[cpu]`
 
 
 ### GPU / CUDA specific steps 

audio_separator/separator.py

@@ -124,12 +124,7 @@ def __init__(
                 self.logger.warning("CUDAExecutionProvider not available in ONNXruntime, so acceleration will NOT be enabled")
                 self.logger.warning("If you expect CUDA to work with your GPU, try pip install --force-reinstall onnxruntime-gpu")
         else:
-            self.logger.debug(
-                "CUDA not available with Torch installation. If you have an Nvidia GPU and expect CUDA support to work, try: "
-            )
-            self.logger.debug(
-                "pip install --force-reinstall torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118"
-            )
+            self.logger.debug("CUDA not available in Torch installation. If you expect GPU/CUDA support to work, please see README")
 
         if hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
             self.logger.info("Apple Silicon MPS/CoreML is available in Torch, setting Torch device to MPS")
@@ -149,9 +144,7 @@ def __init__(
                 self.logger.warning("CoreMLExecutionProvider not available in ONNXruntime, so acceleration will NOT be enabled")
                 self.logger.warning("If you expect MPS/CoreML to work with your Mac, try pip install --force-reinstall onnxruntime-silicon")
         else:
-            raise Exception(
-                "Apple Silicon CoreML / MPS requested but not available with current Torch installation. Do you have an Apple Silicon GPU?"
-            )
+            self.logger.debug("Apple Silicon MPS/CoreML not available in Torch installation. If you expect this to work, please see README")
 
         if not hardware_acceleration_enabled:
             self.logger.info("No hardware acceleration could be configured, running in CPU mode")

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "audio-separator"
-version = "0.9.0"
+version = "0.9.1"
 description = "Easy to use vocal separation on CLI or as a python package, using the amazing MDX-Net models from UVR trained by @Anjok07"
 authors = ["Andrew Beveridge <[email protected]>"]
 license = "MIT"
@@ -19,11 +19,12 @@ librosa = ">=0.9"
 torch = ">=2"
 wget = ">=3"
 six = ">=1.16"
-onnxruntime = ">=1.15"
+onnxruntime = { version = ">=1.15", optional = true }
 onnxruntime-gpu = { version = ">=1.15", optional = true }
 onnxruntime-silicon = { version = ">=1.15", optional = true }
 
 [tool.poetry.extras]
+cpu = ["onnxruntime"]
 gpu = ["onnxruntime-gpu"]
 silicon = ["onnxruntime-silicon"]