Spaces:
Runtime error
Runtime error
File size: 1,796 Bytes
a8c39f5 |
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 |
import torch
from datetime import datetime
def prettify_date(date_str):
if date_str is None:
return "None"
try:
date_time_obj = datetime.strptime(date_str, "%Y-%m-%dT%H:%M:%S.%f")
return date_time_obj.strftime("%Y-%m-%d %H:%M:%S")
except ValueError:
return "Invalid date format"
def model_information(path):
model_data = torch.load(path, map_location="cpu")
print(f"Loaded model from {path}")
model_name = model_data.get("model_name", "None")
epochs = model_data.get("epoch", "None")
steps = model_data.get("step", "None")
sr = model_data.get("sr", "None")
f0 = model_data.get("f0", "None")
dataset_lenght = model_data.get("dataset_lenght", "None")
version = model_data.get("version", "None")
creation_date = model_data.get("creation_date", "None")
model_hash = model_data.get("model_hash", None)
overtrain_info = model_data.get("overtrain_info", "None")
model_author = model_data.get("author", "None")
embedder_model = model_data.get("embedder_model", "None")
speakers_id = model_data.get("speakers_id", 0)
pitch_guidance = "True" if f0 == 1 else "False"
creation_date_str = prettify_date(creation_date) if creation_date else "None"
return (
f"Model Name: {model_name}\n"
f"Model Creator: {model_author}\n"
f"Epochs: {epochs}\n"
f"Steps: {steps}\n"
f"Model Architecture: {version}\n"
f"Sampling Rate: {sr}\n"
f"Pitch Guidance: {pitch_guidance}\n"
f"Dataset Length: {dataset_lenght}\n"
f"Creation Date: {creation_date_str}\n"
f"Hash (ID): {model_hash}\n"
f"Overtrain Info: {overtrain_info}"
f"Embedder Model: {embedder_model}"
f"Max Speakers ID: {speakers_id}"
)
|