Better separate the FlexGen case

modules/text_generation.py

@@ -201,12 +201,8 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
                 reply = original_question + apply_extensions(reply[len(question):], "output")
             yield formatted_outputs(reply, shared.model_name)
 
-            if not shared.args.flexgen:
-                if output[-1] == n:
-                    break
-            else:
-                if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
-                    break
+            if output[-1] == n:
+                break
 
     # Stream the output naively for FlexGen since it doesn't support 'stopping_criteria'
     else:
@@ -223,14 +219,9 @@ def generate_reply(question, max_new_tokens, do_sample, temperature, top_p, typi
                 reply = original_question + apply_extensions(reply[len(question):], "output")
             yield formatted_outputs(reply, shared.model_name)
 
-            if not shared.args.flexgen:
-                if output[-1] == n:
-                    break
-                input_ids = torch.reshape(output, (1, output.shape[0]))
-            else:
-                if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
-                    break
-                input_ids = np.reshape(output, (1, output.shape[0]))
+            if np.count_nonzero(input_ids[0] == n) < np.count_nonzero(output == n):
+                break
+            input_ids = np.reshape(output, (1, output.shape[0]))
 
             if shared.soft_prompt:
                 inputs_embeds, filler_input_ids = generate_softprompt_input_tensors(input_ids)