Format imports according to PEP8 (#1014)

Co-authored-by: holly1238 <77758406+holly1238@users.noreply.github.com>

Author: jgerityneurala

beginner_source/transformer_tutorial.py

@@ -45,15 +45,16 @@
 #
 
 import math
+
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
+from torch.nn import TransformerEncoder, TransformerEncoderLayer
 
 class TransformerModel(nn.Module):
 
     def __init__(self, ntoken, ninp, nhead, nhid, nlayers, dropout=0.5):
         super(TransformerModel, self).__init__()
-        from torch.nn import TransformerEncoder, TransformerEncoderLayer
         self.model_type = 'Transformer'
         self.pos_encoder = PositionalEncoding(ninp, dropout)
         encoder_layers = TransformerEncoderLayer(ninp, nhead, nhid, dropout)
@@ -251,12 +252,13 @@ def get_batch(source, i):
 # function to scale all the gradient together to prevent exploding.
 #
 
+import time
+
 criterion = nn.CrossEntropyLoss()
 lr = 5.0 # learning rate
 optimizer = torch.optim.SGD(model.parameters(), lr=lr)
 scheduler = torch.optim.lr_scheduler.StepLR(optimizer, 1.0, gamma=0.95)
 
-import time
 def train():
     model.train() # Turn on the train mode
     total_loss = 0.