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| # Copyright (c) 2024 Alibaba Inc (authors: Chong Zhang) | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| import os | |
| os.system('nvidia-smi') | |
| os.system('apt update -y && apt-get install -y apt-utils && apt install -y unzip') | |
| os.environ['PYTHONPATH'] = 'third_party/Matcha-TTS' | |
| # os.system('pip install flash-attn --no-build-isolation') | |
| # os.system('git submodule update --init --recursive') | |
| # os.system('git clone https://github.com/shivammehta25/Matcha-TTS.git third_party/') | |
| # os.system('mkdir pretrained_models && cd pretrained_models && git clone https://huggingface.co/FunAudioLLM/InspireMusic-Base.git &&git clone https://huggingface.co/FunAudioLLM/InspireMusic-1.5B-Long.git &&git clone https://huggingface.co/FunAudioLLM/InspireMusic-1.5B.git &&git clone https://huggingface.co/FunAudioLLM/InspireMusic-1.5B-24kHz.git &&git clone https://huggingface.co/FunAudioLLM/InspireMusic-Base-24kHz.git && for i in InspireMusic-Base InspireMusic-Base-24kHz InspireMusic-1.5B InspireMusic-1.5B-24kHz InspireMusic-1.5B-Long; do sed -i -e "s/\.\.\/\.\.\///g" ${i}/inspiremusic.yaml; done && cd ..') | |
| # os.system('mkdir pretrained_models && cd pretrained_models && git clone https://huggingface.co/FunAudioLLM/InspireMusic-Base.git && for i in InspireMusic-Base; do sed -i -e "s/\.\.\/\.\.\///g" ${i}/inspiremusic.yaml; done && cd ..') | |
| import sys | |
| import torch | |
| print(torch.backends.cudnn.version()) | |
| ROOT_DIR = os.path.dirname(os.path.abspath(__file__)) | |
| sys.path.append('{}/third_party/Matcha-TTS'.format(ROOT_DIR)) | |
| import spaces | |
| import gradio as gr | |
| from inspiremusic.cli.inference import InspireMusicUnified, set_env_variables | |
| import torchaudio | |
| import datetime | |
| import hashlib | |
| import importlib | |
| MODELS = ["InspireMusic-1.5B-Long", "InspireMusic-1.5B", "InspireMusic-1.5B-24kHz", "InspireMusic-Base", "InspireMusic-Base-24kHz"] | |
| def generate_filename(): | |
| hash_object = hashlib.sha256(str(int(datetime.datetime.now().timestamp())).encode()) | |
| hash_string = hash_object.hexdigest() | |
| return hash_string | |
| def get_args( | |
| task, text="", audio=None, model_name="InspireMusic-Base", | |
| chorus="intro", | |
| output_sample_rate=48000, max_generate_audio_seconds=30.0, time_start = 0.0, time_end=30.0, trim=False): | |
| if output_sample_rate == 24000: | |
| fast = True | |
| else: | |
| fast = False | |
| # This function constructs the arguments required for InspireMusic | |
| args = { | |
| "task" : task, | |
| "text" : text, | |
| "audio_prompt" : audio, | |
| "model_name" : model_name, | |
| "chorus" : chorus, | |
| "fast" : fast, | |
| "fade_out" : True, | |
| "trim" : trim, | |
| "output_sample_rate" : output_sample_rate, | |
| "min_generate_audio_seconds": 10.0, | |
| "max_generate_audio_seconds": max_generate_audio_seconds, | |
| "max_audio_prompt_length": 5.0, | |
| "model_dir" : os.path.join("pretrained_models", | |
| model_name), | |
| "result_dir" : "exp/inspiremusic", | |
| "output_fn" : generate_filename(), | |
| "format" : "wav", | |
| "time_start" : time_start, | |
| "time_end": time_end, | |
| "fade_out_duration": 1.0, | |
| } | |
| if args["time_start"] is None: | |
| args["time_start"] = 0.0 | |
| args["time_end"] = args["time_start"] + args["max_generate_audio_seconds"] | |
| print(args) | |
| return args | |
| def trim_audio(audio_file, cut_seconds=5): | |
| audio, sr = torchaudio.load(audio_file) | |
| num_samples = cut_seconds * sr | |
| cutted_audio = audio[:, :num_samples] | |
| output_path = os.path.join(os.getcwd(), "audio_prompt_" + generate_filename() + ".wav") | |
| torchaudio.save(output_path, cutted_audio, sr) | |
| return output_path | |
| def music_generation(args): | |
| set_env_variables() | |
| model = InspireMusicUnified( | |
| model_name=args["model_name"], | |
| model_dir=args["model_dir"], | |
| min_generate_audio_seconds=args["min_generate_audio_seconds"], | |
| max_generate_audio_seconds=args["max_generate_audio_seconds"], | |
| sample_rate=24000, | |
| output_sample_rate=args["output_sample_rate"], | |
| load_jit=True, | |
| load_onnx=False, | |
| fast=args["fast"], | |
| result_dir=args["result_dir"]) | |
| output_path = model.inference( | |
| task=args["task"], | |
| text=args["text"], | |
| audio_prompt=args["audio_prompt"], | |
| chorus=args["chorus"], | |
| time_start=args["time_start"], | |
| time_end=args["time_end"], | |
| output_fn=args["output_fn"], | |
| max_audio_prompt_length=args["max_audio_prompt_length"], | |
| fade_out_duration=args["fade_out_duration"], | |
| output_format=args["format"], | |
| fade_out_mode=args["fade_out"], | |
| trim=args["trim"]) | |
| return output_path | |
| # @spaces.GPU(duration=120) | |
| def demo_inspiremusic_t2m(text, model_name, chorus, | |
| output_sample_rate, max_generate_audio_seconds): | |
| args = get_args( | |
| task='text-to-music', text=text, audio=None, | |
| model_name=model_name, chorus=chorus, | |
| output_sample_rate=output_sample_rate, | |
| max_generate_audio_seconds=max_generate_audio_seconds) | |
| return music_generation(args) | |
| # @spaces.GPU(duration=120) | |
| def demo_inspiremusic_con(text, audio, model_name, chorus, | |
| output_sample_rate, max_generate_audio_seconds): | |
| args = get_args( | |
| task='continuation', text=text, audio=trim_audio(audio, cut_seconds=5), | |
| model_name=model_name, chorus=chorus, | |
| output_sample_rate=output_sample_rate, | |
| max_generate_audio_seconds=max_generate_audio_seconds) | |
| return music_generation(args) | |
| # @spaces.GPU(duration=120) | |
| def main(): | |
| with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
| gr.Markdown(""" | |
| # InspireMusic | |
| - Support text-to-music, music continuation, audio super-resolution, audio reconstruction tasks with high audio quality, with available sampling rates of 24kHz, 48kHz. | |
| - Support long audio generation in multiple output audio formats, i.e., wav, flac, mp3, m4a. | |
| - Open-source [InspireMusic-Base](https://modelscope.cn/models/iic/InspireMusic/summary), [InspireMusic-Base-24kHz](https://modelscope.cn/models/iic/InspireMusic-Base-24kHz/summary), [InspireMusic-1.5B](https://modelscope.cn/models/iic/InspireMusic-1.5B/summary), [InspireMusic-1.5B-24kHz](https://modelscope.cn/models/iic/InspireMusic-1.5B-24kHz/summary), [InspireMusic-1.5B-Long](https://modelscope.cn/models/iic/InspireMusic-1.5B-Long/summary) models for music generation. | |
| - Currently only support English text prompts. | |
| This page is for demo purpose, if you want to generate long form music, please try to deploy locally. Thank you for your support. | |
| """) | |
| with gr.Row(equal_height=True): | |
| model_name = gr.Dropdown(MODELS, label="Select Model Name", value="InspireMusic-1.5B-Long") | |
| chorus = gr.Dropdown(["intro", "verse", "chorus", "outro"], | |
| label="Chorus Mode", value="intro") | |
| output_sample_rate = gr.Dropdown([48000, 24000], | |
| label="Output Audio Sample Rate (Hz)", | |
| value=48000) | |
| max_generate_audio_seconds = gr.Slider(10, 30, | |
| label="Generate Audio Length (s)", | |
| value=30) | |
| # with gr.Row(equal_height=True): | |
| text_input = gr.Textbox(label="Input Text (For Text-to-Music Task)", value="Experience soothing and sensual instrumental jazz with a touch of Bossa Nova, perfect for a relaxing restaurant or spa ambiance.") | |
| music_output = gr.Audio(label="Text to Music Output", type="filepath") | |
| button = gr.Button("Text to Music") | |
| button.click(demo_inspiremusic_t2m, | |
| inputs=[text_input, model_name, | |
| chorus, | |
| output_sample_rate, | |
| max_generate_audio_seconds], | |
| outputs=music_output) | |
| audio_input = gr.Audio(label="Input Audio Prompt (For Music Continuation Task)", | |
| type="filepath") | |
| music_con_output = gr.Audio(label="Music Continuation Output", type="filepath") | |
| generate_button = gr.Button("Music Continuation") | |
| generate_button.click(demo_inspiremusic_con, | |
| inputs=[text_input, audio_input, model_name, | |
| chorus, | |
| output_sample_rate, | |
| max_generate_audio_seconds], | |
| outputs=music_con_output) | |
| demo.launch() | |
| if __name__ == '__main__': | |
| main() |