Spaces:
Sleeping
Sleeping
File size: 3,400 Bytes
2373905 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 |
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("<small>Export Finished Model to HuggingFace<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()
|