temp prints to test runs

src/tot/methods/bfs.py

@@ -70,6 +70,7 @@ def solve(args, task, idx, model, tokenizer, to_print=True):
         print("Started Steps!!")
 
         # generation
+        print("Started Generation...")
         if args.method_generate == 'sample':
             new_ys = [get_samples(task, x, y, args.n_generate_sample, prompt_sample=args.prompt_sample, stop=task.stops[step]) for y in ys]
         # elif args.method_generate == 'propose':
@@ -77,22 +78,18 @@ def solve(args, task, idx, model, tokenizer, to_print=True):
             new_ys = [get_proposals(task, x, y) for y in ys]
         new_ys, generate_times = new_ys[0]
 
-
-
         new_ys = list(itertools.chain(new_ys))
         ids = list(range(len(new_ys)))
 
-        print("these are the new ys")
-        print(new_ys)
-        print("****")
-
         # evaluation
+        print("Finished Generation...Started Eval!")
         if args.method_evaluate == 'vote':
             values = get_votes(task, x, new_ys, args.n_evaluate_sample)
         elif args.method_evaluate == 'value':
             values, eval_times = get_values(task, x, new_ys, args.n_evaluate_sample)
         
         # selection
+        print("Finished Eval...Started Selection...")
         if args.method_select == 'sample':
             ps = np.array(values) / sum(values)
             select_ids = np.random.choice(ids, size=args.n_select_sample, p=ps).tolist()
@@ -101,6 +98,7 @@ def solve(args, task, idx, model, tokenizer, to_print=True):
         select_new_ys = [new_ys[select_id] for select_id in select_ids]
 
         # log
+        print("Finished Selection...Logging...")
         if to_print: 
             sorted_new_ys, sorted_values = zip(*sorted(zip(new_ys, values), key=lambda x: x[1], reverse=True))
             print(f'-- new_ys --: {sorted_new_ys}\n-- sol values --: {sorted_values}\n-- choices --: {select_new_ys}\n-- generate times --: {generate_times}\n-- eval times --: {eval_times}\n')

src/tot/models.py

@@ -54,16 +54,20 @@ def hf_model(model, tokenizer, prompt, temperature=0.7, max_tokens=1000, n=5, st
         n -= cnt
 
         #actual generation
+        print(f"cnt is {cnt}. Sending inputs to model...")
+
         start_time = time.perf_counter()
         out = model.generate(**inputs, temperature=temperature, max_new_tokens=max_tokens, num_return_sequences=cnt) #might add stopping criteria depending on heuristics experimentation
         generate_time = time.perf_counter()-start_time
 
+        print(f"output recieved")
+
         for o in out:
             string_answer = tokenizer.decode(o)
             outputs.extend([string_answer])
 
         all_times.extend([generate_time/(float(cnt))]*cnt) #may modify this later to be more precise given hf is open source
-
+    print("Returning model inference outputs")
     return outputs, all_times
 
 # @backoff.on_exception(backoff.expo, openai.error.OpenAIError)

src/tot/tasks/game24.py

@@ -46,12 +46,14 @@ class Game24Task(Task):
         numbers = re.findall(r'\d+', expression)
         problem_numbers = re.findall(r'\d+', self.data[idx])
         if sorted(numbers) != sorted(problem_numbers):
+            print("sorted numbers length not equal to sorted problem numbers length")
             return {'r': 0}
         try:
             # print(sympy.simplify(expression))
             return {'r': int(sympy.simplify(expression) == 24)}
         except Exception as e:
             # print(e)
+            print("entered exception!!")
             return {'r': 0}
             
     @staticmethod