| | import gradio as gr |
| | import subprocess |
| | import os |
| | import re |
| | import shutil |
| | import tempfile |
| |
|
| | is_shared_ui = True if "fffiloni/YuE" in os.environ['SPACE_ID'] else False |
| |
|
| | |
| | def install_flash_attn(): |
| | try: |
| | print("Installing flash-attn...") |
| | subprocess.run( |
| | ["pip", "install", "flash-attn", "--no-build-isolation"], |
| | check=True |
| | ) |
| | print("flash-attn installed successfully!") |
| | except subprocess.CalledProcessError as e: |
| | print(f"Failed to install flash-attn: {e}") |
| | exit(1) |
| |
|
| | |
| | install_flash_attn() |
| |
|
| | from huggingface_hub import snapshot_download |
| |
|
| | |
| | folder_path = './inference/xcodec_mini_infer' |
| |
|
| | |
| | if not os.path.exists(folder_path): |
| | os.mkdir(folder_path) |
| | print(f"Folder created at: {folder_path}") |
| | else: |
| | print(f"Folder already exists at: {folder_path}") |
| |
|
| | snapshot_download( |
| | repo_id = "m-a-p/xcodec_mini_infer", |
| | local_dir = "./inference/xcodec_mini_infer" |
| | ) |
| |
|
| | |
| | inference_dir = "./inference" |
| | try: |
| | os.chdir(inference_dir) |
| | print(f"Changed working directory to: {os.getcwd()}") |
| | except FileNotFoundError: |
| | print(f"Directory not found: {inference_dir}") |
| | exit(1) |
| |
|
| | def empty_output_folder(output_dir): |
| | |
| | files = os.listdir(output_dir) |
| | |
| | |
| | for file in files: |
| | file_path = os.path.join(output_dir, file) |
| | try: |
| | if os.path.isdir(file_path): |
| | |
| | shutil.rmtree(file_path) |
| | else: |
| | |
| | os.remove(file_path) |
| | except Exception as e: |
| | print(f"Error deleting file {file_path}: {e}") |
| |
|
| | |
| | def create_temp_file(content, prefix, suffix=".txt"): |
| | temp_file = tempfile.NamedTemporaryFile(delete=False, mode="w", prefix=prefix, suffix=suffix) |
| | content = content.strip() + "\n\n" |
| | content = content.replace("\r\n", "\n").replace("\r", "\n") |
| | temp_file.write(content) |
| | temp_file.close() |
| | |
| | |
| | print(f"\nContent written to {prefix}{suffix}:") |
| | print(content) |
| | print("---") |
| | |
| | return temp_file.name |
| |
|
| | def get_last_mp3_file(output_dir): |
| | |
| | files = os.listdir(output_dir) |
| | |
| | |
| | mp3_files = [file for file in files if file.endswith('.mp3')] |
| | |
| | if not mp3_files: |
| | print("No .mp3 files found in the output folder.") |
| | return None |
| | |
| | |
| | mp3_files_with_path = [os.path.join(output_dir, file) for file in mp3_files] |
| | |
| | |
| | mp3_files_with_path.sort(key=lambda x: os.path.getmtime(x), reverse=True) |
| | |
| | |
| | return mp3_files_with_path[0] |
| |
|
| | def infer(genre_txt_content, lyrics_txt_content, num_segments, max_new_tokens): |
| | |
| | genre_txt_path = create_temp_file(genre_txt_content, prefix="genre_") |
| | lyrics_txt_path = create_temp_file(lyrics_txt_content, prefix="lyrics_") |
| |
|
| | print(f"Genre TXT path: {genre_txt_path}") |
| | print(f"Lyrics TXT path: {lyrics_txt_path}") |
| |
|
| | |
| | output_dir = "./output" |
| | os.makedirs(output_dir, exist_ok=True) |
| | print(f"Output folder ensured at: {output_dir}") |
| |
|
| | empty_output_folder(output_dir) |
| | |
| | |
| | command = [ |
| | "python", "infer.py", |
| | "--stage1_model", "m-a-p/YuE-s1-7B-anneal-en-cot", |
| | "--stage2_model", "m-a-p/YuE-s2-1B-general", |
| | "--genre_txt", f"{genre_txt_path}", |
| | "--lyrics_txt", f"{lyrics_txt_path}", |
| | "--run_n_segments", str(num_segments), |
| | "--stage2_batch_size", "16", |
| | "--output_dir", f"{output_dir}", |
| | "--cuda_idx", "0", |
| | "--max_new_tokens", str(max_new_tokens) |
| | ] |
| |
|
| | |
| | env = os.environ.copy() |
| | env.update({ |
| | "CUDA_VISIBLE_DEVICES": "0", |
| | "CUDA_HOME": "/usr/local/cuda", |
| | "PATH": f"/usr/local/cuda/bin:{env.get('PATH', '')}", |
| | "LD_LIBRARY_PATH": f"/usr/local/cuda/lib64:{env.get('LD_LIBRARY_PATH', '')}" |
| | }) |
| | |
| | |
| | try: |
| | subprocess.run(command, check=True, env=env) |
| | print("Command executed successfully!") |
| | |
| | |
| | output_files = os.listdir(output_dir) |
| | if output_files: |
| | print("Output folder contents:") |
| | for file in output_files: |
| | print(f"- {file}") |
| |
|
| | last_mp3 = get_last_mp3_file(output_dir) |
| |
|
| | if last_mp3: |
| | print("Last .mp3 file:", last_mp3) |
| | instrumental_mp3_path = "./output/vocoder/stems/instrumental.mp3" |
| | vocal_mp3_path = "./output/vocoder/stems/vocal.mp3" |
| | return last_mp3, instrumental_mp3_path, vocal_mp3_path |
| | else: |
| | return None, None, None |
| | else: |
| | print("Output folder is empty.") |
| | raise gr.Error(f"Error occurred: Output folder is empty.") |
| | except subprocess.CalledProcessError as e: |
| | print(f"Error occurred: {e}") |
| | raise gr.Error(f"Error occurred: {e}") |
| | finally: |
| | |
| | os.remove(genre_txt_path) |
| | os.remove(lyrics_txt_path) |
| | print("Temporary files deleted.") |
| |
|
| | |
| |
|
| | with gr.Blocks() as demo: |
| | with gr.Column(): |
| | gr.Markdown("# YuE: Open Music Foundation Models for Full-Song Generation") |
| | gr.HTML(""" |
| | <div style="display:flex;column-gap:4px;"> |
| | <a href="https://github.com/multimodal-art-projection/YuE"> |
| | <img src='https://img.shields.io/badge/GitHub-Repo-blue'> |
| | </a> |
| | <a href="https://map-yue.github.io"> |
| | <img src='https://img.shields.io/badge/Project-Page-green'> |
| | </a> |
| | <a href="https://huggingface.co/spaces/fffiloni/YuE?duplicate=true"> |
| | <img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-sm.svg" alt="Duplicate this Space"> |
| | </a> |
| | </div> |
| | """) |
| | with gr.Row(): |
| | with gr.Column(): |
| | with gr.Accordion("Pro Tips", open=False): |
| | gr.Markdown(f""" |
| | **Tips:** |
| | 1. `genres` should include details like instruments, genre, mood, vocal timbre, and vocal gender. |
| | 2. The length of `lyrics` segments and the `--max_new_tokens` value should be matched. For example, if `--max_new_tokens` is set to 3000, the maximum duration for a segment is around 30 seconds. Ensure your lyrics fit this time frame. |
| | |
| | |
| | **Notice:** |
| | 1. A suitable [Genre] tag consists of five components: genre, instrument, mood, gender, and timbre. All five should be included if possible, separated by spaces. The values of timbre should include "vocal" (e.g., "bright vocal"). |
| | |
| | 2. Although our tags have an open vocabulary, we have provided the 200 most commonly used <a href="https://github.com/multimodal-art-projection/YuE/blob/main/top_200_tags.json" id="tags_link" target="_blank">tags</a>. It is recommended to select tags from this list for more stable results. |
| | |
| | 3. The order of the tags is flexible. For example, a stable genre control string might look like: "inspiring female uplifting pop airy vocal electronic bright vocal vocal." |
| | |
| | 4. Additionally, we have introduced the "Mandarin" and "Cantonese" tags to distinguish between Mandarin and Cantonese, as their lyrics often share similarities. |
| | """) |
| | genre_txt = gr.Textbox( |
| | label="Genre", |
| | placeholder="Example: inspiring female uplifting pop airy vocal...", |
| | info="Text containing genre tags that describe the musical style or characteristics (e.g., instrumental, genre, mood, vocal timbre, vocal gender). This is used as part of the generation prompt." |
| | ) |
| | lyrics_txt = gr.Textbox( |
| | label="Lyrics", lines=12, |
| | placeholder=""" |
| | Type the lyrics here... |
| | At least 2 segments, Annotate your segments with brackets, [verse] [chorus] [bridge]""", |
| | info="Text containing the lyrics for the music generation. These lyrics will be processed and split into structured segments to guide the generation process." |
| | ) |
| | |
| | with gr.Column(): |
| | |
| | num_segments = gr.Number(label="Number of Segments", value=2, interactive=False) |
| | max_new_tokens = gr.Slider(label="Max New Tokens", minimum=500, maximum="3000", step=500, value=1500, interactive=True) |
| | |
| | submit_btn = gr.Button("Submit") |
| | music_out = gr.Audio(label="Audio Result") |
| | with gr.Accordion("Vocal & Instrumental", open=False): |
| | instrumental = gr.Audio(label="Intrumental") |
| | vocal = gr.Audio(label="Vocal") |
| |
|
| | gr.Examples( |
| | examples = [ |
| | [ |
| | "female blues airy vocal bright vocal piano sad romantic guitar jazz", |
| | """[verse] |
| | In the quiet of the evening, shadows start to fall |
| | Whispers of the night wind echo through the hall |
| | Lost within the silence, I hear your gentle voice |
| | Guiding me back homeward, making my heart rejoice |
| | |
| | [chorus] |
| | Don't let this moment fade, hold me close tonight |
| | With you here beside me, everything's alright |
| | Can't imagine life alone, don't want to let you go |
| | Stay with me forever, let our love just flow""" |
| | ], |
| | [ |
| | "rap piano street tough piercing vocal hip-hop synthesizer clear vocal male", |
| | """[verse] |
| | Woke up in the morning, sun is shining bright |
| | Chasing all my dreams, gotta get my mind right |
| | City lights are fading, but my vision's clear |
| | Got my team beside me, no room for fear |
| | Walking through the streets, beats inside my head |
| | Every step I take, closer to the bread |
| | People passing by, they don't understand |
| | Building up my future with my own two hands |
| | |
| | [chorus] |
| | This is my life, and I'm aiming for the top |
| | Never gonna quit, no, I'm never gonna stop |
| | Through the highs and lows, I'mma keep it real |
| | Living out my dreams with this mic and a deal""" |
| | ] |
| | ], |
| | inputs = [genre_txt, lyrics_txt] |
| | ) |
| | |
| | submit_btn.click( |
| | fn = infer, |
| | inputs = [genre_txt, lyrics_txt, num_segments, max_new_tokens], |
| | outputs = [music_out, instrumental, vocal] |
| | ) |
| | demo.queue().launch(show_api=False, show_error=True) |