Update CUDA python requirements with onnxruntime 1.19 update

.github/workflows/build-executable.yml

@@ -83,6 +83,11 @@ jobs:
       run: cp ./server/{force_gpu_clocks.bat,reset_gpu_clocks.bat} ./server/dist/
       shell: bash
       if: matrix.os == 'windows-latest' && matrix.backend == 'cuda'
+    - name: Add CUDA library symlinks
+      run: ln -svf nvidia/*/lib/*.so* .
+      shell: bash
+      if: matrix.os == 'ubuntu-20.04' && matrix.backend == 'cuda'
+      working-directory: ./server/dist/MMVCServerSIO/_internal
     - name: Pack artifact
       shell: bash
       run: |

.github/workflows/make-release.yml

@@ -122,6 +122,11 @@ jobs:
       run: cp ./server/{force_gpu_clocks.bat,reset_gpu_clocks.bat} ./server/dist/
       shell: bash
       if: matrix.os == 'windows-latest' && matrix.backend == 'cuda'
+    - name: Add CUDA library symlinks
+      run: ln -svf nvidia/*/lib/*.so* .
+      shell: bash
+      if: matrix.os == 'ubuntu-20.04' && matrix.backend == 'cuda'
+      working-directory: ./server/dist/MMVCServerSIO/_internal
     - name: Pack artifact
       shell: bash
       run: |

server/app.py

@@ -9,6 +9,7 @@
 # Reset CUDA_PATH since all libraries are already bundled.
 # Existing CUDA installations may be incompatible with PyTorch or ONNX runtime
 os.environ['CUDA_PATH'] = ''
+os.environ['CUDNN_PATH'] = ''
 # Fix high CPU usage caused by faiss-cpu for AMD CPUs.
 # https://github.com/facebookresearch/faiss/issues/53#issuecomment-288351188
 os.environ['OMP_WAIT_POLICY'] = 'PASSIVE'

server/requirements-cuda.txt

@@ -3,10 +3,9 @@
 # # wget https://repo.anaconda.com/archive/Anaconda3-2022.10-Linux-x86_64.sh
 # # bash Anaconda3-2022.10-Linux-x86_64.sh
 
-# PyPI onnxruntime-gpu is compiled with CUDA 11.x
---extra-index-url https://download.pytorch.org/whl/cu118
-# torch 2.4.0 has problems with Linux builds
-torch==2.3.1
+# PyPI onnxruntime-gpu>=1.19 is compiled with CUDA 12.x and cuDNN 9.x
+--extra-index-url https://download.pytorch.org/whl/cu121
+torch>=2.4.0
 torchaudio
 faiss-cpu==1.8.0; sys_platform!='linux'
 faiss-gpu; sys_platform=='linux'

server/requirements-dml.txt

@@ -3,7 +3,7 @@
 # # wget https://repo.anaconda.com/archive/Anaconda3-2022.10-Linux-x86_64.sh
 # # bash Anaconda3-2022.10-Linux-x86_64.sh
 
-torch==2.3.1 # torch-directml-0.2.2.dev240614 supports up to to 2.3.1
+torch==2.3.1 # torch-directml-0.2.4.dev240815 supports torch up to to 2.3.1
 torchaudio
 torch-directml
 faiss-cpu==1.8.0

server/voice_changer/RVC/pitchExtractor/CrepeOnnxPitchExtractor.py

@@ -1,9 +1,9 @@
 import numpy as np
 import torch
+import onnxruntime
 from const import PitchExtractorType, F0_MIN, F0_MAX
 from voice_changer.common.deviceManager.DeviceManager import DeviceManager
 from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
-import onnxruntime
 from voice_changer.RVC.pitchExtractor import onnxcrepe
 
 

server/voice_changer/RVC/pitchExtractor/FcpeOnnxPitchExtractor.py

@@ -1,6 +1,6 @@
 import numpy as np
-import onnxruntime
 import torch
+import onnxruntime
 from const import PitchExtractorType
 from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
 from voice_changer.common.deviceManager.DeviceManager import DeviceManager

server/voice_changer/RVC/pitchExtractor/RMVPEOnnxPitchExtractor.py

@@ -1,11 +1,11 @@
 import numpy as np
+import torch
+import onnxruntime
 from const import PitchExtractorType
 from voice_changer.common.OnnxLoader import load_onnx_model
 from voice_changer.RVC.pitchExtractor.PitchExtractor import PitchExtractor
 from voice_changer.common.deviceManager.DeviceManager import DeviceManager
 from voice_changer.common.MelExtractor import MelSpectrogram
-import onnxruntime
-import torch
 
 class RMVPEOnnxPitchExtractor(PitchExtractor):