fix bug in nag optimizer (apache#13683)

* fix bug in nag optimizer ``` grad += wd * weight mom[:] += grad grad[:] += self.momentum * mom weight[:] += -lr * grad ``` This will minus wd*weight twice, but in`state = momentum * state + grad + wd * weight weight = weight - (lr * (grad + momentum * state)) ` only minus once. * fix bug in nag test fix bug in nag test * rewrite nag test * rewrite nag * fix nag with in-place operations * fix nag with in-place operations
stephenrawls · Feb 16, 2019 · 7ff6ee3 · 7ff6ee3
1 parent 90e6791
commit 7ff6ee3
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diff --git a/python/mxnet/optimizer/optimizer.py b/python/mxnet/optimizer/optimizer.py
@@ -978,10 +978,10 @@ def update(self, index, weight, grad, state):
         if state is not None:
             mom = state
             mom[:] *= self.momentum
-            grad += wd * weight
             mom[:] += grad
+            mom[:] += wd * weight
             grad[:] += self.momentum * mom
-            weight[:] += -lr * grad
+            weight[:] -= lr * grad
         else:
             assert self.momentum == 0.0
             weight[:] += -lr * (grad + wd * weight)

diff --git a/tests/python/unittest/test_optimizer.py b/tests/python/unittest/test_optimizer.py
@@ -385,10 +385,10 @@ def update(self, index, weight, grad, state):
             else:
               mom = state
               mom[:] *= self.momentum
-              grad += wd * weight
               mom[:] += grad
+              mom[:] += wd * weight
               grad[:] += self.momentum * mom
-              weight[:] += -lr * grad
+              weight[:] -= lr * grad
         else:
             grad32 = array(grad, ctx=grad.context, dtype=np.float32)
             grad32 = grad32 * self.rescale_grad
@@ -400,10 +400,10 @@ def update(self, index, weight, grad, state):
                 weight32[:] += -lr * (grad32 + wd * weight32)
             else:
                 mom[:] *= self.momentum
-                grad32 += wd * weight32
                 mom[:] += grad32
+                mom[:] += wd * weight32
                 grad32[:] += self.momentum * mom
-                weight32[:] += -lr * grad32
+                weight32[:] -= lr * grad32
             tmp = weight32.astype(weight.dtype)
             tmp.copyto(weight)