revised

app.py

@@ -11,15 +11,15 @@ from sklearn.metrics import roc_curve, auc
 
 def process_file(file,label,info, model_name):
 
-    with open(file.name, 'r') as f:
-        content = f.read()
-    saved_test_dataset = "train.txt"
-    saved_test_label = "train_label.txt"
-    saved_train_info="train_info.txt"
-    # Save the uploaded file content to a specified location
-    shutil.copyfile(file.name, saved_test_dataset)
-    shutil.copyfile(label.name, saved_test_label)
-    shutil.copyfile(info.name, saved_train_info)
+    # with open(file.name, 'r') as f:
+    #     content = f.read()
+    # saved_test_dataset = "train.txt"
+    # saved_test_label = "train_label.txt"
+    # saved_train_info="train_info.txt"
+    # # Save the uploaded file content to a specified location
+    # shutil.copyfile(file.name, saved_test_dataset)
+    # shutil.copyfile(label.name, saved_test_label)
+    # shutil.copyfile(info.name, saved_train_info)
     # For demonstration purposes, we'll just return the content with the selected model name
     # if(model_name=="highGRschool10"):
     #     checkpoint="ratio_proportion_change3/output/FS/bert_fine_tuned.model.ep32"
@@ -35,13 +35,13 @@ def process_file(file,label,info, model_name):
         "python", "new_test_saved_finetuned_model.py",
         "-workspace_name", "ratio_proportion_change3_2223/sch_largest_100-coded",
         "-finetune_task", model_name,
-        "-test_dataset_path","../../../../train.txt",
+        # "-test_dataset_path","../../../../train.txt",
         # "-test_label_path","../../../../train_label.txt",
         "-finetuned_bert_classifier_checkpoint", 
         "ratio_proportion_change3_2223/sch_largest_100-coded/output/highGRschool10/bert_fine_tuned.model.ep42",
         "-e",str(1),
         "-b",str(5)
-    ], shell=True)
+    ])
 
     result = {}
     with open("result.txt", 'r') as file: