Update run_CNN_HB.py

run_CNN_HB.py

@@ -19,7 +19,7 @@ def collate_fn(batch):
     batch = list(filter(lambda x: x is not None, batch))
     return data.dataloader.default_collate(batch) if len(batch) > 0 else None
 
-def run(files, stdcfile, model, folder, fe=44100, pool=False, lensample=5, batch_size=32):
+def run(files, stdcfile, model, folder, pool=False, lensample=5, batch_size=32):
     model.load_state_dict(load(stdcfile))
     model.eval()
     cuda0 = device('cuda' if cuda.is_available() else 'cpu')
@@ -28,7 +28,7 @@ def run(files, stdcfile, model, folder, fe=44100, pool=False, lensample=5, batch
     out = pd.DataFrame(columns=['fn', 'offset', 'pred'])
     fns, offsets, preds = [], [], []
     with no_grad():
-        for x, meta in tqdm(data.DataLoader(Dataset(files, folder, fe=fe, lensample=lensample), batch_size=batch_size, collate_fn=collate_fn, num_workers=8,prefetch_factor=4)):
+        for x, meta in tqdm(data.DataLoader(Dataset(files, folder, lensample=lensample), batch_size=batch_size, collate_fn=collate_fn, num_workers=8,prefetch_factor=4)):
             x = x.to(cuda0, non_blocking=True)
             pred = model(x)
             temp = pd.DataFrame().from_dict(meta)