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inference.py

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+# @title Imports
+from diffusers import DiffusionPipeline
+from riffusion.spectrogram_image_converter import SpectrogramImageConverter
+from riffusion.spectrogram_params import SpectrogramParams
+from io import BytesIO
+
+
+# @title Define a `predict` function
+
+params = SpectrogramParams()
+converter = SpectrogramImageConverter(params)
+
+
+def preprocess_function(text):
+    with open(text, "r", encoding="utf-8") as f:
+        data = f.read()
+    print(data)
+    # pass the textand the target tanguage to be translated separated by a ";" semicolon
+    # data = text_path.read().decode("utf-8")
+    prompt = data.split(";")[0]
+    negative_prompt = data.split(";")[1].strip()
+    print(negative_prompt.strip())
+    print(data)
+    return (prompt, negative_prompt)
+
+
+def predict_function(params, pipe):
+    prompt, negative_prompt = params
+    spec = pipe(
+        prompt,
+        negative_prompt=negative_prompt,
+        width=768,
+    ).images[0]
+
+    wav = converter.audio_from_spectrogram_image(image=spec)
+    wav.export("output.wav", format="wav")
+    return ("output.wav", spec)
+
+
+def model_load_function(model_path):
+    pipe = DiffusionPipeline.from_pretrained(model_path)
+    pipe = pipe.to("cuda")
+    return pipe
+
+
+def postprocess_function(audio_file, content_type=None):
+    audio = open(audio_file, "rb")
+    audio = audio.read()
+    print(type(audio))
+    audio_bytes = BytesIO(audio)
+    response = dict()
+    audio_bytes.seek(0)
+    response["output"] = {"data": audio_bytes, "ext": "wav"}
+    return response
+
+
+## Test the script
+"""
+if __name__ == '__main__':
+    text = ""
+    data = preprocess_function(text)
+    model_path = "./model_files"
+    path = model_load_function(model_path)
+    predictions = predict_function(data,path)
+    out = postprocess_function(audio_file)
+    print(out)
+"""

requirements.txt

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+accelerate
+argh
+dacite
+demucs
+diffusers
+numpy
+pillow
+plotly
+pydub
+pysoundfile
+scipy
+soundfile
+sox
+torch
+torchaudio
+torchvision
+transformers
+riffusion