refactor(scar): refactor scar to allow efficient usage of GPU

Novartis · Jul 29, 2024 · c846d9b · c846d9b
1 parent 6b101f1
commit c846d9b
Showing 1 changed file with 3 additions and 2 deletions.
diff --git a/scar/main/_scar.py b/scar/main/_scar.py
@@ -450,6 +450,7 @@ def train(
             training_set, batch_size=batch_size, shuffle=shuffle,
             drop_last=True
         )
+        self.dataset = training_set
         # val_set = UMIDataset(self.raw_count, self.ambient_profile, self.batch_id, list_ids=test_ids)
         # val_generator = torch.utils.data.DataLoader(
         #     val_set, batch_size=batch_size, shuffle=shuffle
@@ -593,7 +594,7 @@ def inference(
             native_frequencies, and noise_ratio. \
                 A feature_assignment will be added in 'sgRNA' or 'tag' or 'CMO' feature type.   
         """
-        total_set = UMIDataset(self.raw_count, self.ambient_profile, self.batch_id, device=self.device, cache_capacity=self.cache_capacity)
+        # total_set = UMIDataset(self.raw_count, self.ambient_profile, self.batch_id, device=self.device, cache_capacity=self.cache_capacity)
         n_features = self.n_features
         sample_size = self.raw_count.shape[0]
         self.native_counts = np.empty([sample_size, n_features])
@@ -605,7 +606,7 @@ def inference(
             batch_size = sample_size
         i = 0
         generator_full_data = torch.utils.data.DataLoader(
-            total_set, batch_size=batch_size, shuffle=False
+            self.dataset, batch_size=batch_size, shuffle=False
         )
 
         for x_batch_tot, ambient_freq_tot, x_batch_id_onehot_tot in generator_full_data: