Update intermediate_source/char_rnn_classification_tutorial.py

Co-authored-by: Joel Schlosser <[email protected]>

intermediate_source/char_rnn_classification_tutorial.py

@@ -220,7 +220,7 @@ def __getitem__(self, idx):
 # as regular feed-forward layers.
 # 
 # This CharRNN class implements an RNN with three components. 
-# First, we use the `nn.RNN implemnentation <https://pytorch.org/docs/stable/generated/torch.nn.RNN.html>`__ 
+# First, we use the `nn.RNN implementation <https://pytorch.org/docs/stable/generated/torch.nn.RNN.html>`__ 
 # , next we define a layer that maps the RNN hidden layers to our output and finally we apply a softmax. Using nn.RNN 
 # leads to a significant improvement in performance (e.g. cuDNN-accelerated kernals) versus implementing 
 # each layer as a nn.Linear. It also simplifies the implementation in forward().