Add help message for snli example (pytorch#707)

snli/util.py

@@ -20,25 +20,50 @@ def makedirs(name):
 
 def get_args():
     parser = ArgumentParser(description='PyTorch/torchtext SNLI example')
-    parser.add_argument('--epochs', type=int, default=50)
-    parser.add_argument('--batch_size', type=int, default=128)
-    parser.add_argument('--d_embed', type=int, default=100)
-    parser.add_argument('--d_proj', type=int, default=300)
-    parser.add_argument('--d_hidden', type=int, default=300)
-    parser.add_argument('--n_layers', type=int, default=1)
-    parser.add_argument('--log_every', type=int, default=50)
-    parser.add_argument('--lr', type=float, default=.001)
-    parser.add_argument('--dev_every', type=int, default=1000)
-    parser.add_argument('--save_every', type=int, default=1000)
-    parser.add_argument('--dp_ratio', type=int, default=0.2)
-    parser.add_argument('--no-bidirectional', action='store_false', dest='birnn')
-    parser.add_argument('--preserve-case', action='store_false', dest='lower')
-    parser.add_argument('--no-projection', action='store_false', dest='projection')
-    parser.add_argument('--train_embed', action='store_false', dest='fix_emb')
-    parser.add_argument('--gpu', type=int, default=0)
-    parser.add_argument('--save_path', type=str, default='results')
-    parser.add_argument('--vector_cache', type=str, default=os.path.join(os.getcwd(), '.vector_cache/input_vectors.pt'))
-    parser.add_argument('--word_vectors', type=str, default='glove.6B.100d')
-    parser.add_argument('--resume_snapshot', type=str, default='')
+    parser.add_argument('--epochs', type=int, default=50,
+                        help='the number of total epochs to run.')
+    parser.add_argument('--batch_size', type=int, default=128,
+                        help='batch size. (default: 128)')
+    parser.add_argument('--d_embed', type=int, default=100,
+                        help='the size of each embedding vector.')
+    parser.add_argument('--d_proj', type=int, default=300,
+                        help='the size of each projection layer.')
+    parser.add_argument('--d_hidden', type=int, default=300,
+                        help='the number of features in the hidden state.')
+    parser.add_argument('--n_layers', type=int, default=1,
+                        help='the number of recurrent layers. (default: 50)')
+    parser.add_argument('--log_every', type=int, default=50,
+                        help='iteration period to output log.')
+    parser.add_argument('--lr',type=float, default=.001,
+                        help='initial learning rate.')
+    parser.add_argument('--dev_every', type=int, default=1000,
+                        help='log period of validation results.')
+    parser.add_argument('--save_every', type=int, default=1000,
+                        help='model checkpoint period.')
+    parser.add_argument('--dp_ratio', type=int, default=0.2,
+                        help='probability of an element to be zeroed.')
+    parser.add_argument('--no-bidirectional', action='store_false', dest='birnn',
+                        help='disable bidirectional LSTM.')
+    parser.add_argument('--preserve-case', action='store_false', dest='lower',
+                        help='case-sensitivity.')
+    parser.add_argument('--no-projection', action='store_false', dest='projection',
+                        help='disable projection layer.')
+    parser.add_argument('--train_embed', action='store_false', dest='fix_emb',
+                        help='enable embedding word training.')
+    parser.add_argument('--gpu', type=int, default=0,
+                        help='gpu id to use. (default: 0)')
+    parser.add_argument('--save_path', type=str, default='results',
+                        help='save path of results.')
+    parser.add_argument('--vector_cache', type=str, default=os.path.join(os.getcwd(), '.vector_cache/input_vectors.pt'),
+                        help='name of vector cache directory, which saved input word-vectors.')
+    parser.add_argument('--word_vectors', type=str, default='glove.6B.100d',
+                        help='one of or a list containing instantiations of the GloVe, CharNGram, or Vectors classes.'
+                        'Alternatively, one of or a list of available pretrained vectors: '
+                        'charngram.100d fasttext.en.300d fasttext.simple.300d'
+                        'glove.42B.300d glove.840B.300d glove.twitter.27B.25d'
+                        'glove.twitter.27B.50d glove.twitter.27B.100d glove.twitter.27B.200d'
+                        'glove.6B.50d glove.6B.100d glove.6B.200d glove.6B.300d')
+    parser.add_argument('--resume_snapshot', type=str, default='',
+                        help='model snapshot to resume.')
     args = parser.parse_args()
     return args