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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