Skip the row completed in inference sample loop

For a single prompt, the inference engine generates num_samples of result independently.
Once a row is completed, stop the row from generating tokens to reduce computation.

Signed-off-by: Luojects <13113951796@163.com>

nanochat/engine.py

@@ -195,6 +195,7 @@ class Engine:
         output_end = get_special("<|output_end|>")
         assistant_end = get_special("<|assistant_end|>") # if sampled, ends row
         bos = self.tokenizer.get_bos_token_id() # if sampled, ends row
+        pad = get_special("<|pad|>")
 
         # 1) Run a batch 1 prefill of the prompt tokens
         m = self.model.config
@@ -243,6 +244,12 @@ class Engine:
             token_column = [] # contains the next token id along each row
             token_masks = [] # contains the mask (was it sampled (1) or forced (0)?) along each row
             for i, state in enumerate(row_states):
+                # Skip the row completed
+                if state.completed:
+                    token_column.append(pad)
+                    token_masks.append(0)
+                    continue
+
                 # Select the next token in this row
                 is_forced = len(state.forced_tokens) > 0 # are there tokens waiting to be forced in deque?
                 token_masks.append(0 if is_forced else 1) # mask is 0 if forced, 1 if sampled