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| import os | |
| import sys | |
| import time | |
| import torch | |
| import requests | |
| import subprocess | |
| from tqdm import tqdm | |
| from huggingface_hub import snapshot_download | |
| TEMP_DIR = "./flagged" | |
| WEIGHTS_DIR = snapshot_download("monetjoe/EMelodyGen", cache_dir="./__pycache__") | |
| DEVICE = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |
| PATCH_LENGTH = 128 # Patch Length | |
| PATCH_SIZE = 32 # Patch Size | |
| PATCH_NUM_LAYERS = 9 # Number of layers in the encoder | |
| CHAR_NUM_LAYERS = 3 # Number of layers in the decoder | |
| PATCH_SAMPLING_BATCH_SIZE = 0 # Batch size for training patch, 0 for full context | |
| LOAD_FROM_CHECKPOINT = True # Whether to load weights from a checkpoint | |
| SHARE_WEIGHTS = False # Whether to share weights between the encoder and decoder | |
| def download(filename: str, url: str): | |
| try: | |
| response = requests.get(url, stream=True) | |
| total_size = int(response.headers.get("content-length", 0)) | |
| chunk_size = 1024 | |
| with open(filename, "wb") as file, tqdm( | |
| desc=f"Downloading {filename} from {url}...", | |
| total=total_size, | |
| unit="B", | |
| unit_scale=True, | |
| unit_divisor=1024, | |
| ) as bar: | |
| for data in response.iter_content(chunk_size=chunk_size): | |
| size = file.write(data) | |
| bar.update(size) | |
| except Exception as e: | |
| print(f"Error: {e}") | |
| time.sleep(10) | |
| download(filename, url) | |
| if sys.platform.startswith("linux"): | |
| apkname = "MuseScore.AppImage" | |
| extra_dir = "squashfs-root" | |
| download( | |
| filename=apkname, | |
| url="https://master.dl.sourceforge.net/project/musescore-linux-mirror/MuseScore.AppImage?viasf=1", | |
| ) | |
| if not os.path.exists(extra_dir): | |
| subprocess.run(["chmod", "+x", f"./{apkname}"]) | |
| subprocess.run([f"./{apkname}", "--appimage-extract"]) | |
| MSCORE = f"./{extra_dir}/AppRun" | |
| os.environ["QT_QPA_PLATFORM"] = "offscreen" | |
| else: | |
| MSCORE = os.getenv("mscore") | |