fixes

backend/services.py

@@ -190,7 +190,7 @@ class SentimentAnalyzer:
             "sar_trial10",
             "sa_no_AOA",
         ]
-        self.model_repos = download_models(self.sa_models)
+        download_models(self.sa_models)
         # fmt: off
         self.processors = {
             "sa_trial5_1": Trial5ArabicPreprocessor(model_name='UBC-NLP/MARBERT'),
@@ -202,12 +202,12 @@ class SentimentAnalyzer:
         }
 
         self.pipelines = {
-            "sa_trial5_1": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format(self.model_repos["sa_trial5_1"],i), device=-1,return_all_scores =True) for i in range(0,5)],
-            "sa_no_aoa_in_neutral": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format(self.model_repos["sa_no_aoa_in_neutral"],i), device=-1,return_all_scores =True) for i in range(0,5)],
-            "sa_cnnbert": [CNNTextClassificationPipeline("{}/train_{}/best_model".format(self.model_repos["sa_cnnbert"],i), device=-1, return_all_scores =True) for i in range(0,5)],
-            "sa_sarcasm": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format(self.model_repos["sa_sarcasm"],i), device=-1,return_all_scores =True) for i in range(0,5)],
-            "sar_trial10": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format(self.model_repos["sar_trial10"],i), device=-1,return_all_scores =True) for i in range(0,5)],
-            "sa_no_AOA": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format(self.model_repos["sa_no_aoa_in_neutral"],i), device=-1,return_all_scores =True) for i in range(0,5)],
+            "sa_trial5_1": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format("sa_trial5_1",i), device=-1,return_all_scores =True) for i in range(0,5)],
+            "sa_no_aoa_in_neutral": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format("sa_no_aoa_in_neutral",i), device=-1,return_all_scores =True) for i in range(0,5)],
+            "sa_cnnbert": [CNNTextClassificationPipeline("{}/train_{}/best_model".format("sa_cnnbert",i), device=-1, return_all_scores =True) for i in range(0,5)],
+            "sa_sarcasm": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format("sa_sarcasm",i), device=-1,return_all_scores =True) for i in range(0,5)],
+            "sar_trial10": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format("sar_trial10",i), device=-1,return_all_scores =True) for i in range(0,5)],
+            "sa_no_AOA": [pipeline("sentiment-analysis", model="{}/train_{}/best_model".format("sa_no_AOA",i), device=-1,return_all_scores =True) for i in range(0,5)],
         }
         # fmt: on
 

backend/utils.py

@@ -1,5 +1,6 @@
 import psutil
 import os
+from tqdm.auto import tqdm
 
 
 def get_current_ram_usage():
@@ -8,31 +9,25 @@ def get_current_ram_usage():
 
 
 def download_models(models):
-    model_dirs = {}
-    for model in models:
-        model_dirs = {
-            model: model
-        }  # useless i know, but i don't want to change the code
+    for model in tqdm(models, desc="Downloading models"):
         for i in range(0, 5):
             curr_dir = f"{model}/train_{i}/best_model/"
             os.makedirs(curr_dir)
             os.system(
-                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/config.json -P {curr_dir}"
+                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/config.json -P {curr_dir} >/dev/null"
             )
             os.system(
-                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/pytorch_model.bin -P {curr_dir}"
+                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/pytorch_model.bin -P {curr_dir} >/dev/null"
             )
             os.system(
-                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/special_tokens_map.json -P {curr_dir}"
+                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/special_tokens_map.json -P {curr_dir} >/dev/null"
             )
             os.system(
-                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/tokenizer_config.json -P {curr_dir}"
+                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/tokenizer_config.json -P {curr_dir} >/dev/null"
             )
             os.system(
-                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/training_args.bin -P {curr_dir}"
+                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/training_args.bin -P {curr_dir} >/dev/null"
             )
             os.system(
-                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/vocab.txt -P {curr_dir}"
+                f"wget https://huggingface.co/researchaccount/{model}/resolve/main/train_{i}/best_model/vocab.txt -P {curr_dir} >/dev/null"
             )
-
-    return model_dirs