now works for word-level LM

train.py

@@ -21,7 +21,7 @@ model_type = 'RWKV' # 'RWKV' or 'RotaryMHA' or 'MHA-Plus'
 datafile = u"V:\\NLP\\simplebooks\\simplebooks-92-raw\\train.txt" # https://dldata-public.s3.us-east-2.amazonaws.com/simplebooks.zip
 model_level = 'character' # 'character' or 'word'
 
-ctx_size = 256 if 'character' else 128
+ctx_size = 256 if model_level == 'character' else 128
 nLayers = 5
 nHead = 8
 nEmb = 512
@@ -87,7 +87,10 @@ LENGTH_OF_EACH = 300
 for run in range(NUM_OF_RUNS):
     context = "It was"
 
-    x = np.array([train_dataset.stoi[s] for s in context], dtype=np.int64)
+    if model_level == 'word':
+        x = np.array([train_dataset.stoi[s] for s in context.split(' ')], dtype=np.int64)
+    else:
+        x = np.array([train_dataset.stoi[s] for s in context], dtype=np.int64)
 
     real_len = len(x)
     if real_len < MAX_LEN:
@@ -114,7 +117,11 @@ for run in range(NUM_OF_RUNS):
         real_len += 1
 
         if i % 10 == 9 or i == LENGTH_OF_EACH-1:
-            completion = ''.join([train_dataset.itos[int(i)] for i in x[print_begin:real_len]])
+            if model_level == 'word':
+                completion = ' ' + ' '.join([train_dataset.itos[int(i)] for i in x[print_begin:real_len]])
+                completion = completion.replace('\n ', '\n')
+            else:
+                completion = ''.join([train_dataset.itos[int(i)] for i in x[print_begin:real_len]])
             print(completion, end = '')
             print_begin = real_len
     print()