Fixing merge conflict

megatron/text_generation_utils.py

@@ -175,21 +175,11 @@ def synced_generate(model, context_tokens_tensor, context_length_tensor, max_len
     if tokens is not None:
         return tokens[:, :context_length], output_logits, full_logits 
 
-<<<<<<< HEAD
 def generate(model, sentences=None, max_len=0, all_probs=False):
-    if torch.distributed.get_rank() == 0:
-        context_tokens_tensor, context_length_tensor = tokenize_batch(sentences)
-        c = context_length_tensor[0]
-        b = context_tokens_tensor.size(0)
-        start = time.time()
-        send_generate_info(context_tokens_tensor, context_length_tensor, max_len, all_probs)
-=======
-def generate(model, sentences=None, max_len=0):
     model.eval()
     if torch.distributed.get_rank() == 0:
         context_tokens_tensor, context_length_tensor = tokenize_batch(sentences)
-        send_generate_info(context_tokens_tensor, context_length_tensor, max_len)
->>>>>>> server
+        send_generate_info(context_tokens_tensor, context_length_tensor, max_len, all_probs)
     else:
         context_length_tensor, context_tokens_tensor, max_len, all_probs = receive_generate_info()
     
@@ -206,7 +196,6 @@ def generate(model, sentences=None, max_len=0):
         decode_tokens = decode_tokens.cpu().numpy().tolist()
         for decode_token in decode_tokens:
             resp_sentences.append(tokenizer.detokenize(decode_token))
-<<<<<<< HEAD
             words = []
             for token in decode_token:
                 word = tokenizer.tokenizer.decoder[token]
@@ -218,12 +207,7 @@ def generate(model, sentences=None, max_len=0):
         if all_probs:
             full_logits = full_logits.cpu().numpy().tolist()
 
-        end = time.time()
-        print(str(b)+","+str(c)+","+str(len(decode_tokens[0]))+","+str(end-start), flush=True)
         return resp_sentences, resp_sentences_seg, output_logits, full_logits, decode_tokens 
-=======
-        return resp_sentences
->>>>>>> server
 
 def generate_samples_eval(model, context, max_gen_length, eos_token_id):
     """