add a "stops words" support

DEMO_FOR_STOPWORDS.py

@@ -0,0 +1,34 @@
+import os
+os.environ['RWKV_JIT_ON'] = '1'
+os.environ["RWKV_CUDA_ON"] = '1'
+from rwkv.model import RWKV
+from rwkv.utils import PIPELINE, PIPELINE_ARGS
+
+MODEL_FILE = "/media/yueyulin/KINGSTON/pretrained_models/rwkv/RWKV-4-World-CHNtuned-7B-v1-20230709-ctx4096.pth"
+model = RWKV(model=MODEL_FILE, strategy="cuda fp16")
+pipeline = PIPELINE(model, "rwkv_vocab_v20230424")  #### vocab for rwkv-4-world models
+print(model)
+
+print(pipeline)
+
+ctx = "User：请根据以下材料设计一道中餐菜谱。要求生成菜名和具体做法，菜谱最后以”完成！“结束。材料：猪后腿肉，青椒，洋葱，盐，胡椒。\nAssistant：菜名："
+print(ctx, end="")
+
+def my_print(s):
+    print(s, end="", flush=True)
+
+end_token = pipeline.encode("完成！")
+print(end_token)
+args = PIPELINE_ARGS(
+    temperature=1.5,
+    top_p=0.3,
+    top_k=0,  # top_k = 0 -> ignore top_k
+    alpha_frequency=0.2,  # frequency penalty - see https://platform.openai.com/docs/api-reference/parameter-details
+    alpha_presence=0.2,  # presence penalty - see https://platform.openai.com/docs/api-reference/parameter-details
+    token_ban=[],  # ban the generation of some tokens
+    token_stop=end_token,  # stop generation at these tokens
+    chunk_len=256,
+)  # split input into chunks to save VRAM (shorter -> less VRAM, but slower)
+
+pipeline.generate(ctx, token_count=1024, args=args, callback=my_print)
+print("\n")

rwkv_pip_package/src/rwkv/utils.py

@@ -88,7 +88,9 @@ def generate(self, ctx, token_count=100, args=PIPELINE_ARGS(), callback=None, st
         out_last = 0
         out_str = ''
         occurrence = {}
-        for i in range(token_count):
+        continue_generating = True
+        i = 0
+        while continue_generating:
 
             # forward & adjust prob.
             tokens = self.encode(ctx) if i == 0 else [token]
@@ -103,8 +105,8 @@ def generate(self, ctx, token_count=100, args=PIPELINE_ARGS(), callback=None, st
 
             # sampler
             token = self.sample_logits(out, temperature=args.temperature, top_p=args.top_p, top_k=args.top_k)
-            if token in args.token_stop:
-                break
+            if len(args.token_stop) > 0 and args.token_stop==all_tokens[-len(args.token_stop):]:
+                continue_generating = False
             all_tokens += [token]
             for xxx in occurrence:
                 occurrence[xxx] *= args.alpha_decay
@@ -121,4 +123,7 @@ def generate(self, ctx, token_count=100, args=PIPELINE_ARGS(), callback=None, st
                     callback(tmp)
                 out_str += tmp
                 out_last = i + 1
+            i += 1
+            if i >= token_count:
+                continue_generating = False
         return out_str