Update file compute_embeddings.py

new_specie/compute_embeddings.py

@@ -4,6 +4,7 @@ import numpy as np, pandas as pd, torch
 import umap
 from tqdm import tqdm
 import argparse
+torch.multiprocessing.set_sharing_strategy('file_system')
 
 parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter, description="Compute the auto-encoder embeddings of vocalizations once it was trained with train_AE.py")
 parser.add_argument('modelname', type=str, help='Filename of the AE weights (.stdc)')
@@ -26,7 +27,7 @@ df = pd.read_csv(args.detections)
 
 print('Computing AE projections...')
 loader = torch.utils.data.DataLoader(u.Dataset(df, args.audio_folder, args.SR, args.sampleDur, channel=1), batch_size=16, shuffle=False, num_workers=8, prefetch_factor=8)
-with torch.no_grad():
+with torch.inference_mode():
     encodings, idxs = [], []
     for x, idx in tqdm(loader):
         encoding = model[:2](x.to(device))