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@ -19,7 +19,7 @@ class EmptyLatentAudio:
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "generate"
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CATEGORY = "_for_testing/audio"
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CATEGORY = "latent/audio"
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def generate(self, seconds):
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batch_size = 1
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@ -34,7 +34,7 @@ class VAEEncodeAudio:
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RETURN_TYPES = ("LATENT",)
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FUNCTION = "encode"
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CATEGORY = "_for_testing/audio"
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CATEGORY = "latent/audio"
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def encode(self, vae, audio):
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sample_rate = audio["sample_rate"]
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@ -53,7 +53,7 @@ class VAEDecodeAudio:
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RETURN_TYPES = ("AUDIO",)
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FUNCTION = "decode"
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CATEGORY = "_for_testing/audio"
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CATEGORY = "latent/audio"
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def decode(self, vae, samples):
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audio = vae.decode(samples["samples"]).movedim(-1, 1)
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@ -132,7 +132,7 @@ class SaveAudio:
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OUTPUT_NODE = True
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CATEGORY = "_for_testing/audio"
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CATEGORY = "audio"
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def save_audio(self, audio, filename_prefix="ComfyUI", prompt=None, extra_pnginfo=None):
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filename_prefix += self.prefix_append
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@ -195,7 +195,7 @@ class LoadAudio:
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]
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return {"required": {"audio": (sorted(files), {"audio_upload": True})}}
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CATEGORY = "_for_testing/audio"
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CATEGORY = "audio"
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RETURN_TYPES = ("AUDIO", )
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FUNCTION = "load"
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@ -203,7 +203,6 @@ class LoadAudio:
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def load(self, audio):
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audio_path = folder_paths.get_annotated_filepath(audio)
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waveform, sample_rate = torchaudio.load(audio_path)
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multiplier = 1.0
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audio = {"waveform": waveform.unsqueeze(0), "sample_rate": sample_rate}
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return (audio, )
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