Update app.py

app.py

@@ -2,7 +2,7 @@ import torch
 import torch.nn as nn
 from torch import Tensor
 from torch.nn import Transformer
-
+import math
 # helper Module that adds positional encoding to the token embedding to introduce a notion of word order.
 class PositionalEncoding(nn.Module):
     def __init__(self,
@@ -10,7 +10,7 @@ class PositionalEncoding(nn.Module):
                  dropout: float,
                  maxlen: int = 5000):
         super(PositionalEncoding, self).__init__()
-        den = torch.exp(- torch.arange(0, emb_size, 2)* torch.log(10000) / emb_size)
+        den = torch.exp(- torch.arange(0, emb_size, 2)* math.log(10000) / emb_size)
         pos = torch.arange(0, maxlen).reshape(maxlen, 1)
         pos_embedding = torch.zeros((maxlen, emb_size))
         pos_embedding[:, 0::2] = torch.sin(pos * den)