fix cifar lr decay

examples/cifar-convnet.py

@@ -123,8 +123,8 @@ def get_config(cifar_classnum):
             ModelSaver(),
             InferenceRunner(dataset_test,
                             ScalarStats(['accuracy', 'cost'])),
-            StatMonitorParamSetter('learning_rate', 'val_error', lr_func,
-                                   threshold=0.001, last_k=10),
+            StatMonitorParamSetter('learning_rate', 'validation_accuracy', lr_func,
+                                   threshold=0.001, last_k=10, reverse=True),
         ],
         max_epoch=150,
     )

tensorpack/tfutils/optimizer.py

@@ -5,7 +5,7 @@
 
 import tensorflow as tf
 from contextlib import contextmanager
-from .gradproc import FilterNoneGrad
+from .gradproc import FilterNoneGrad, GradientProcessor
 
 __all__ = ['apply_grad_processors', 'ProxyOptimizer',
            'PostProcessOptimizer', 'VariableAssignmentOptimizer',
@@ -48,6 +48,8 @@ def apply_grad_processors(opt, gradprocs):
         processors before updating the variables.
     """
     assert isinstance(gradprocs, (list, tuple)), gradprocs
+    for gp in gradprocs:
+        assert isinstance(gp, GradientProcessor), gp
 
     class _ApplyGradientProcessor(ProxyOptimizer):
         def __init__(self, opt, gradprocs):