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import os |
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import subprocess |
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import sys |
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from pathlib import Path |
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repo_dir = "VibeVoice" |
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if not os.path.exists(repo_dir): |
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print("Cloning the VibeVoice repository...") |
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try: |
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subprocess.run( |
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["git", "clone", "https://github.com/microsoft/VibeVoice.git"], |
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check=True, |
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capture_output=True, |
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text=True |
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) |
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print("Repository cloned successfully.") |
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except subprocess.CalledProcessError as e: |
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print(f"Error cloning repository: {e.stderr}") |
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sys.exit(1) |
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else: |
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print("Repository already exists. Skipping clone.") |
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os.chdir(repo_dir) |
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print(f"Changed directory to: {os.getcwd()}") |
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print("Installing the VibeVoice package...") |
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try: |
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subprocess.run( |
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[sys.executable, "-m", "pip", "install", "-e", "."], |
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check=True, |
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capture_output=True, |
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text=True |
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) |
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print("Package installed successfully.") |
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except subprocess.CalledProcessError as e: |
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print(f"Error installing package: {e.stderr}") |
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sys.exit(1) |
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demo_script_path = Path("demo/gradio_demo.py") |
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print(f"Modifying {demo_script_path} for CPU execution...") |
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try: |
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file_content = demo_script_path.read_text() |
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original_block = """ self.model = VibeVoiceForConditionalGenerationInference.from_pretrained( |
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self.model_path, |
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torch_dtype=torch.bfloat16, |
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device_map='cuda', |
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attn_implementation="flash_attention_2", |
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)""" |
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replacement_block = """ self.model = VibeVoiceForConditionalGenerationInference.from_pretrained( |
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self.model_path, |
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torch_dtype=torch.float32, # Use float32 for CPU |
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device_map="cpu", |
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)""" |
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if original_block in file_content: |
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modified_content = file_content.replace(original_block, replacement_block) |
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demo_script_path.write_text(modified_content) |
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print("Script modified successfully.") |
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else: |
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print("Warning: GPU-specific model loading block not found. The script might have been updated. Proceeding without modification.") |
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except Exception as e: |
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print(f"An error occurred while modifying the script: {e}") |
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sys.exit(1) |
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model_id = "microsoft/VibeVoice-1.5B" |
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command = [ |
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"python", |
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str(demo_script_path), |
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"--model_path", |
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model_id, |
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"--share" |
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] |
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print(f"Launching Gradio demo with command: {' '.join(command)}") |
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subprocess.run(command) |