szha commented on a change in pull request #9633: Gluon image-classification
example improvement
URL: https://github.com/apache/incubator-mxnet/pull/9633#discussion_r164932389
##########
File path: example/gluon/image_classification.py
##########
@@ -129,27 +164,39 @@ def test(ctx, val_data):
metric.update(label, outputs)
return metric.get()
+def update_learning_rate(lr, trainer, epoch, ratio, steps):
+ """Set the learning rate to the initial value decayed by ratio every N
epochs."""
+ new_lr = lr * (ratio ** int(np.sum(np.array(steps) < epoch)))
+ trainer.set_learning_rate(new_lr)
+ return trainer
+
+def as_list(x):
+ if not isinstance(x, list):
+ return [x]
+ return x
-def train(epochs, ctx):
- if isinstance(ctx, mx.Context):
- ctx = [ctx]
- net.initialize(mx.init.Xavier(magnitude=2), ctx=ctx)
+def train(opt, ctx):
Review comment:
do you intend to add metric argument here too? this way `train` only
involves using these components, which can make the code look simpler.
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