cjolivier01 commented on a change in pull request #9793: Enable the reporting 
of cross-entropy or nll loss value when training CNN network using the models 
defined by example/image-classification
URL: https://github.com/apache/incubator-mxnet/pull/9793#discussion_r168325934
 
 

 ##########
 File path: example/image-classification/common/fit.py
 ##########
 @@ -117,6 +117,8 @@ def add_fit_args(parser):
                        help='load the model on an epoch using the 
model-load-prefix')
     train.add_argument('--top-k', type=int, default=0,
                        help='report the top-k accuracy. 0 means no report.')
+    train.add_argument('--loss', type=str,
+                       help='report the cross-entropy or nll-loss. ce means 
cross-entropy, nll-loss means likelihood loss')
 
 Review comment:
   This seems a little confusing to me, as in what's the actual expected loss 
string.
   Maybe something like:
   "report the loss. Options are ce (cross-entropy) or nll-loss (likelihood 
loss)
   ?

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