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https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2025-04-04 03:38:58 +08:00
Add GPU specific pacakges to .toml and a python script to selectively uncomment those
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VSlobolinskyi
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0cbff69edf
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73
configure_gpu_deps.py
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73
configure_gpu_deps.py
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@ -0,0 +1,73 @@
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#!/usr/bin/env python3
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import sys
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import re
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def process_lines(lines, target_gpu):
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"""
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Process the lines of a file and uncomment the configuration block corresponding
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to target_gpu ('nvidia' or 'amd') while leaving the other block commented.
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"""
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output_lines = []
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current_block = None # None, "nvidia", or "amd"
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# Define regexes to detect the markers
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nvidia_marker = re.compile(r'---\s*NVIDIA GPU configuration\s*---', re.IGNORECASE)
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amd_marker = re.compile(r'---\s*AMD GPU configuration\s*---', re.IGNORECASE)
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separator = re.compile(r'^#\s*-{5,}') # a commented separator line (at least 5 dashes)
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for line in lines:
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stripped = line.lstrip()
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# Check for block start markers (they remain unchanged)
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if nvidia_marker.search(line):
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current_block = "nvidia"
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output_lines.append(line)
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continue
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elif amd_marker.search(line):
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current_block = "amd"
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output_lines.append(line)
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continue
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# End of block when encountering a separator line
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if separator.match(line):
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current_block = None
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output_lines.append(line)
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continue
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# If we're in a GPU configuration block and the line is commented, process it
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if current_block is not None and stripped.startswith("#"):
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# Remove the first '#' and any following space if we are in the target block.
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if current_block == target_gpu:
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# Uncomment by removing the first '#' (preserve indentation)
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# Using regex to remove a leading '#' with possible spaces
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uncommented = re.sub(r'^(?P<indent>\s*)#\s?', r'\g<indent>', line)
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output_lines.append(uncommented)
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else:
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# Leave the line commented for the non-target block
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output_lines.append(line)
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else:
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output_lines.append(line)
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return output_lines
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def main():
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if len(sys.argv) != 3:
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print("Usage: python configure_gpu_deps.py <pyproject.toml> <gpu_type>")
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print(" where <gpu_type> is either 'nvidia' or 'amd'")
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sys.exit(1)
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toml_path = sys.argv[1]
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gpu_type = sys.argv[2].lower()
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if gpu_type not in {"nvidia", "amd"}:
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print("gpu_type must be either 'nvidia' or 'amd'")
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sys.exit(1)
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with open(toml_path, "r", encoding="utf-8") as f:
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lines = f.readlines()
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new_lines = process_lines(lines, gpu_type)
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with open(toml_path, "w", encoding="utf-8") as f:
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f.writelines(new_lines)
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print(f"Updated {toml_path} for {gpu_type.upper()} GPU configuration.")
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if __name__ == "__main__":
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main()
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@ -8,30 +8,14 @@ package-mode = false
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[tool.poetry.dependencies]
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python = ">=3.11,<3.12"
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# GPU-specific installations for torch and torchaudio:
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# If AMD_GPU environment variable is set to "true", then use AMD-compatible packages.
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torch = [
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{ url = "https://download.pytorch.org/whl/cu118/torch-2.1.1%2Bcu118-cp311-cp311-win_amd64.whl#sha256=d99be44487d3ed0f7e6ef5d6689a37fb4a2f2821a9e7b59e7e04002a876a667a", markers = "sys_platform == 'win32' and platform_machine != 'AMD64'" },
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{ url = "https://download.pytorch.org/whl/cu118/torch-2.1.1%2Bcu118-cp311-cp311-linux_x86_64.whl#sha256=f3c0ba02b50d0021ff26f030e22d4c45965537cf91f322e52a65b8c58396f81c", markers = "sys_platform == 'linux' and platform_machine != 'AMD64'" },
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{ version = "^2.4.1", markers = "platform_machine == 'AMD64'" }
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]
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torchaudio = [
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{ url = "https://download.pytorch.org/whl/cu118/torchaudio-2.1.1%2Bcu118-cp311-cp311-win_amd64.whl#sha256=79b5afa556063be18de4a1964339242301fe04e782e1030a22695257dd9afbd2", markers = "sys_platform == 'win32' and platform_machine != 'AMD64'" },
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{ url = "https://download.pytorch.org/whl/cu118/torchaudio-2.1.1%2Bcu118-cp311-cp311-linux_x86_64.whl#sha256=2b077639f240176bb27e964e2e9b3a5c2a8d560a3a7bc1ffd0a024e81f2e10b4", markers = "sys_platform == 'linux' and platform_machine != 'AMD64'" },
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{ version = "2.4.1", markers = "platform_machine == 'AMD64'" }
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]
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# Additional dependency for AMD GPUs on Windows:
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torch-directml = { version = "^0.2.5.dev240914", markers = "platform_machine == 'AMD64'" }
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# Common dependencies (non GPU-specific):
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fairseq = { git = "https://github.com/One-sixth/fairseq.git" }
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joblib = ">=1.1.0"
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numba = "*"
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numpy = "*"
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scipy = "*"
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librosa = "==0.10.2"
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llvmlite = "*"
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fairseq = { git = "https://github.com/One-sixth/fairseq.git" }
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faiss-cpu = "*"
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gradio = "==3.34.0"
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Cython = "*"
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@ -65,7 +49,7 @@ uvicorn = ">=0.21.1"
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colorama = ">=0.4.5"
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pyworld = "==0.3.2"
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httpx = "*"
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onnxruntime = { version = "*", markers = "sys_platform == 'darwin'" }
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onnxruntime = { version = "*", markers = "sys_platform == 'darwin'" }
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onnxruntime-gpu = { version = "*", markers = "sys_platform != 'darwin'" }
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torchcrepe = "==0.0.23"
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fastapi = "==0.88"
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@ -74,6 +58,22 @@ ffmpy = "==0.3.1"
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python-dotenv = ">=1.0.0"
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av = "*"
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# ---------------------------------------------------------------------------
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# --- NVIDIA GPU configuration ---
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# torch = [
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# { url = "https://download.pytorch.org/whl/cu118/torch-2.1.1+cu118-cp311-cp311-win_amd64.whl#sha256=d99be44487d3ed0f7e6ef5d6689a37fb4a2f2821a9e7b59e7e04002a876a667a", markers = "sys_platform == 'win32'" },
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# { url = "https://download.pytorch.org/whl/cu118/torch-2.1.1+cu118-cp311-cp311-linux_x86_64.whl#sha256=f3c0ba02b50d0021ff26f030e22d4c45965537cf91f322e52a65b8c58396f81c", markers = "sys_platform == 'linux'" }
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# ]
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# torchaudio = [
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# { url = "https://download.pytorch.org/whl/cu118/torchaudio-2.1.1+cu118-cp311-cp311-win_amd64.whl#sha256=79b5afa556063be18de4a1964339242301fe04e782e1030a22695257dd9afbd2", markers = "sys_platform == 'win32'" },
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# { url = "https://download.pytorch.org/whl/cu118/torchaudio-2.1.1+cu118-cp311-cp311-linux_x86_64.whl#sha256=2b077639f240176bb27e964e2e9b3a5c2a8d560a3a7bc1ffd0a024e81f2e10b4", markers = "sys_platform == 'linux'" }
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# ]
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# --- AMD GPU configuration ---
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# torch = "2.4.1"
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# torchaudio = "2.4.1"
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# torch-directml = "^0.2.5.dev240914"
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# ---------------------------------------------------------------------------
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[tool.poetry.group.dev.dependencies]
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# Add any development dependencies here
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