Deleted TODOs

Author: SuyashLakhotia

data.py

@@ -20,7 +20,6 @@ def clean_text(self):
         """
         Tokenization & string cleaning.
         """
-        # TODO: NLP preprocessing (use nltk?). Stemming, lemmatization etc.
         for i, string in enumerate(self.documents):
             string = re.sub(r"[^A-Za-z0-9(),!?'$]", " ", string)
             string = re.sub(r"(\d+)", " NUM ", string)

graph_cnn.py

@@ -217,7 +217,6 @@ def graph_max_pool(self, x, p):
             return x
 
     def filter_in_fourier(self, x, L, K, F_out, U, W):
-        # TODO: B x F x V would avoid the permutations?
         B, V, F_in = x.get_shape()
         B, V, F_in = int(B), int(V), int(F_in)
         x = tf.transpose(x, perm=[1, 2, 0])  # V x F_in x B

graph_cnn_train.py

@@ -155,10 +155,6 @@
                         l2_reg_lambda=l2_reg_lambda)
 
         # Convert sparse matrices to arrays
-        # TODO: Is there a workaround for this? Doesn't seem memory efficient.
-        # TODO: https://github.com/tensorflow/tensorflow/issues/342#issuecomment-160354041
-        # TODO: https://github.com/tensorflow/tensorflow/issues/342#issuecomment-273463729
-        # TODO: https://stackoverflow.com/questions/37001686/using-sparsetensor-as-a-trainable-variable
         x_train = np.squeeze([x_i.toarray() for x_i in x_train])
         x_test = np.squeeze([x_i.toarray() for x_i in x_test])