diff --git a/hyperparams.py b/hyperparams.py
index 99ba046..51e06fc 100644
--- a/hyperparams.py
+++ b/hyperparams.py
@@ -27,7 +27,7 @@ class Hyperparams:
     num_epochs = 20
     num_heads = 8
     dropout_rate = 0.1
-    sinusoid = False # If True, use sinusoid. If false, positional embedding.
+    sinusoid = True # If True, use sinusoid. If false, positional embedding.
     
     
     
diff --git a/modules.py b/modules.py
index 4222d0a..127bb44 100644
--- a/modules.py
+++ b/modules.py
@@ -4,16 +4,19 @@
 June 2017 by kyubyong park. 
 kbpark.linguist@gmail.com.
 https://www.github.com/kyubyong/transformer
+
 '''
 
 from __future__ import print_function
 import tensorflow as tf
-
+import numpy as np
 def normalize(inputs, 
               epsilon = 1e-8,
               scope="ln",
               reuse=None):
-    '''Applies layer normalization.
+    '''
+    
+    Applies layer normalization.
     
     Args:
       inputs: A tensor with 2 or more dimensions, where the first dimension has
@@ -45,7 +48,8 @@ def embedding(inputs,
               scale=True,
               scope="embedding", 
               reuse=None):
-    '''Embeds a given tensor.
+    '''
+    Embeds a given tensor.
 
     Args:
       inputs: A `Tensor` with type `int32` or `int64` containing the ids
@@ -153,15 +157,20 @@ def positional_encoding(inputs,
 
         # Convert to a tensor
         lookup_table = tf.convert_to_tensor(position_enc)
-
+        lookup_table= tf.cast(lookup_table, tf.float32)
+        
         if zero_pad:
             lookup_table = tf.concat((tf.zeros(shape=[1, num_units]),
                                       lookup_table[1:, :]), 0)
+        
+        
         outputs = tf.nn.embedding_lookup(lookup_table, position_ind)
-
+        
+        
         if scale:
             outputs = outputs * num_units**0.5
-
+        
+      
         return outputs
 
 
@@ -260,7 +269,8 @@ def feedforward(inputs,
                 num_units=[2048, 512],
                 scope="multihead_attention", 
                 reuse=None):
-    '''Point-wise feed forward net.
+    '''
+    Point-wise feed forward net.
     
     Args:
       inputs: A 3d tensor with shape of [N, T, C].
diff --git a/train.py b/train.py
index 45a5732..7e6cecc 100644
--- a/train.py
+++ b/train.py
@@ -88,7 +88,6 @@ def __init__(self, is_training=True):
                 ## Positional Encoding
                 if hp.sinusoid:
                     self.dec += positional_encoding(self.decoder_inputs,
-                                      vocab_size=hp.maxlen, 
                                       num_units=hp.hidden_units, 
                                       zero_pad=False, 
                                       scale=False,