3

app.py

@@ -340,14 +340,18 @@ def construction_layout():
 def evaluate_v1(inputs, model, quantizer, tokenizer, width, height, device, do_sample=False, temperature=1.0, top_p=1.0, top_k=50):
     json_example = inputs
     input_intension = '{"wholecaption":"' + json_example["wholecaption"] + '","layout":[{"layer":'
+    print("tokenizer1")
     inputs = tokenizer(
         input_intension, return_tensors="pt"
     ).to(model.lm.device)
+    print("tokenizer2")
     
     stopping_criteria = StoppingCriteriaList()
     stopping_criteria.append(StopAtSpecificTokenCriteria(token_id_list=[128000]))
 
+    print("lm1")
     outputs = model.lm.generate(**inputs, use_cache=True, max_length=8000, stopping_criteria=stopping_criteria, do_sample=do_sample, temperature=temperature, top_p=top_p, top_k=top_k)
+    print("lm2")
     inputs_length = inputs['input_ids'].shape[1] 
     outputs = outputs[:, inputs_length:]
     

app_test.py

@@ -340,14 +340,18 @@ def construction_layout():
 def evaluate_v1(inputs, model, quantizer, tokenizer, width, height, device, do_sample=False, temperature=1.0, top_p=1.0, top_k=50):
     json_example = inputs
     input_intension = '{"wholecaption":"' + json_example["wholecaption"] + '","layout":[{"layer":'
+    print("tokenizer1")
     inputs = tokenizer(
         input_intension, return_tensors="pt"
     ).to(model.lm.device)
+    print("tokenizer2")
     
     stopping_criteria = StoppingCriteriaList()
     stopping_criteria.append(StopAtSpecificTokenCriteria(token_id_list=[128000]))
 
+    print("lm1")
     outputs = model.lm.generate(**inputs, use_cache=True, max_length=8000, stopping_criteria=stopping_criteria, do_sample=do_sample, temperature=temperature, top_p=top_p, top_k=top_k)
+    print("lm2")
     inputs_length = inputs['input_ids'].shape[1] 
     outputs = outputs[:, inputs_length:]