From 65f9e9c6b772ec55585f7b85312336a0d0d46123 Mon Sep 17 00:00:00 2001
From: Paul Best <paul.best@lis-lab.fr>
Date: Thu, 25 May 2023 17:34:29 +0200
Subject: [PATCH] Update file compute_embeddings.py
---
new_specie/compute_embeddings.py | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/new_specie/compute_embeddings.py b/new_specie/compute_embeddings.py
index 262f8f7..512554b 100755
--- a/new_specie/compute_embeddings.py
+++ b/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))
--
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