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import gradio as gr | |
import os | |
import zipfile | |
import glob | |
from huggingface_hub import login, HfApi, create_repo | |
def export_model_to_hf(hftoken, experiment_name, manual_epoch_number, logs_path, repoid, create_new_repo): | |
num_epochs = int(manual_epoch_number) if manual_epoch_number.isdigit() else None | |
# Construct the weights path based on the provided number of epochs | |
if num_epochs is not None: | |
weights_path = f"/content/RVC/assets/weights/{experiment_name}_e{num_epochs}*" | |
else: | |
potential = f"/content/RVC/assets/weights/{experiment_name}.pth" | |
if os.path.exists(potential): | |
weights_path = f"/content/RVC/assets/weights/{experiment_name}" | |
else: | |
currentMax = 0 | |
for r, _, f in os.walk("/content/RVC/assets/weights/"): | |
for name in f: | |
if(name.endswith(".pth") and (name != experiment_name + ".pth")): | |
if(name.find(experiment_name) == -1): | |
continue | |
pot = name.split('_') | |
ep = pot[len(pot) - 2][1:] | |
if not ep.isdecimal(): | |
continue | |
ep = int(ep) | |
if ep > currentMax: | |
currentMax = ep | |
num_epochs = currentMax | |
weights_path = f"/content/RVC/assets/weights/{experiment_name}_e{num_epochs}*" | |
weights_files = glob.glob(weights_path + ".pth") | |
if weights_files and any(glob_result := glob.glob(logs_path)): | |
log_file = glob_result[0] | |
output_folder = "/content/toHF" | |
os.makedirs(output_folder, exist_ok=True) | |
output_zip_path = f"{output_folder}/{experiment_name}.zip" | |
with zipfile.ZipFile(output_zip_path, 'w') as zipf: | |
for weights_file in weights_files: | |
zipf.write(weights_file, os.path.basename(weights_file)) | |
zipf.write(log_file, os.path.basename(log_file)) | |
login(token=hftoken) | |
if create_new_repo: | |
create_repo(repoid) | |
api = HfApi() | |
api.upload_folder(folder_path=output_folder, repo_id=repoid, repo_type="model") | |
return f"Model uploaded successfully to {repoid}" | |
else: | |
return "Couldn't find your model files. Check the found file results above. (Did you run Index Training?)" | |
with gr.Blocks() as demo: | |
gr.Markdown("# Export Finished Model to HuggingFace test<br>[click this to get HF token](https://huggingface.co/settings/tokens)</small>") | |
hftoken = gr.Textbox(label="HuggingFace Token (set Role to 'write')", type="password") | |
experiment_name = gr.Textbox(label="Experiment Name", value="rewrite") | |
manual_epoch_number = gr.Textbox(label="Manual Epoch Number (leave blank for auto-detect)", value="") | |
logs_path = gr.Textbox(label="Logs Path", value="/content/RVC/logs/rewrite/added_IVF37_Flat_nprobe_1_rewrite_v2.index") | |
repoid = gr.Textbox(label="HuggingFace Repository ID", value="Hev832/rewrite-sonic") | |
create_new_repo = gr.Checkbox(label="Create New Repository", value=True) | |
output = gr.Textbox(label="Output") | |
btn = gr.Button("Export Model") | |
btn.click(export_model_to_hf, inputs=[hftoken, experiment_name, manual_epoch_number, logs_path, repoid, create_new_repo], outputs=output) | |
demo.launch() | |