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Subject [GitHub] anirudhacharya commented on a change in pull request #12697: [MXNET -1004] Poisson NegativeLog Likelihood loss
Date Tue, 09 Oct 2018 01:10:52 GMT
anirudhacharya commented on a change in pull request #12697: [MXNET -1004] Poisson NegativeLog
Likelihood loss
URL: https://github.com/apache/incubator-mxnet/pull/12697#discussion_r223536222

##########
File path: python/mxnet/gluon/loss.py
##########
@@ -706,3 +707,65 @@ def hybrid_forward(self, F, pred, positive, negative):
axis=self._batch_axis, exclude=True)
loss = F.relu(loss + self._margin)
return _apply_weighting(F, loss, self._weight, None)
+
+
+class PoissonNLLLoss(Loss):
+    r"""For a target (Random Variable) in a Poisson distribution, the function calculates
the Negative
+    Log likelihood loss.
+    PoissonNLLLoss measures the loss accrued from a poisson regression prediction made by
the model.
+
+    .. math::
+        L = \text{pred} - \text{target} * \log(\text{pred}) +\log(\text{target!})
+
+    pred, target can have arbitrary shape as long as they have the same number of elements.
+
+    Parameters
+    ----------
+    from_logits : boolean, default True
+        indicating whether log(predicted) value has already been computed. If True, the loss
is computed as
+        :math:\exp(\text{pred}) - \text{target} * \text{pred}, and if False, then loss
is computed as
+        :math:\text{pred} - \text{target} * \log(\text{pred}+\text{epsislon}).The default
value

Review comment:
these definitions seem to be at odds with the definition given above in line 718

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