refactor: Remove try-catch
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@@ -30,47 +30,35 @@ def generate_random_audio_name():
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def get_image_url(image):
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try:
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image = image.squeeze(0)
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image = image.permute(2, 0, 1)
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image = transforms.ToPILImage()(image)
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image = image.squeeze(0)
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image = image.permute(2, 0, 1)
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image = transforms.ToPILImage()(image)
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image_name = generate_random_image_name()
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save_path = os.path.join(folder_paths.get_output_directory, image_name)
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torchvision.utils.save_image(image, save_path)
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image_name = generate_random_image_name()
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save_path = os.path.join(folder_paths.get_output_directory, image_name)
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torchvision.utils.save_image(image, save_path)
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if os.path.exists(image_name):
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os.remove(image_name)
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return image_name
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if os.path.exists(image_name):
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os.remove(image_name)
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except Exception as e:
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if os.path.exists(image_name):
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os.remove(image_name)
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raise RuntimeError(f"处理图片失败: {str(e)}")
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return image_name
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def get_audio_url(audio):
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try:
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waveform = audio["waveform"]
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sample_rate = audio["sample_rate"]
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waveform = audio["waveform"]
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sample_rate = audio["sample_rate"]
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if waveform.dim() == 3:
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waveform = waveform.squeeze(0)
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if waveform.dim() == 3:
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waveform = waveform.squeeze(0)
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audio_name = generate_random_audio_name()
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save_path = os.path.join(folder_paths.get_output_directory, audio_name)
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torchaudio.save(save_path, waveform, sample_rate, format="wav")
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audio_name = generate_random_audio_name()
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save_path = os.path.join(folder_paths.get_output_directory, audio_name)
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torchaudio.save(save_path, waveform, sample_rate, format="wav")
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if os.path.exists(audio_name):
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os.remove(audio_name)
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if os.path.exists(audio_name):
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os.remove(audio_name)
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return audio_name
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except Exception as e:
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if os.path.exists(audio_name):
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os.remove(audio_name)
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raise RuntimeError(f"处理音频失败: {str(e)}")
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return audio_name
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def get_model_versions(model_type: str) -> list[str]:
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