fix test (apache#13)

roywei · Jul 31, 2019 · 2b2f85d · 2b2f85d
1 parent a69b406
commit 2b2f85d
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Showing 2 changed files with 7 additions and 6 deletions.
diff --git a/python/mxnet/gluon/contrib/estimator/estimator.py b/python/mxnet/gluon/contrib/estimator/estimator.py
@@ -153,7 +153,7 @@ def _check_trainer(self, trainer):
             warnings.warn("No trainer specified, default SGD optimizer "
                           "with learning rate 0.001 is used.")
             trainer = Trainer(self.net.collect_params(),
-                                    'sgd', {'learning_rate': 0.001})
+                              'sgd', {'learning_rate': 0.001})
         elif not isinstance(trainer, Trainer):
             raise ValueError("Trainer must be a Gluon Trainer instance, refer to "
                              "gluon.Trainer:{}".format(trainer))
@@ -363,7 +363,7 @@ def _prepare_default_handlers(self, val_data, event_handlers):
 
         # if there is a mix of user defined event handlers and default event handlers
         # they should have the same set of loss and metrics
-        if default_handlers and len(event_handlers) > len(default_handlers):
+        if default_handlers and len(event_handlers) != len(default_handlers):
             msg = "You are training with the following default event handlers: %s. " \
                   "They use loss and metrics from estimator.prepare_loss_and_metrics(). " \
                   "Please use the same set of metrics for all your other handlers." % \

diff --git a/python/mxnet/gluon/contrib/estimator/event_handler.py b/python/mxnet/gluon/contrib/estimator/event_handler.py
@@ -29,10 +29,11 @@
 from ....metric import EvalMetric
 from ....metric import Loss as metric_loss
 
-__all__ = ['TrainBegin', 'TrainEnd', 'EpochBegin', 'EpochEnd','BatchBegin', 'BatchEnd',
+__all__ = ['TrainBegin', 'TrainEnd', 'EpochBegin', 'EpochEnd', 'BatchBegin', 'BatchEnd',
            'StoppingHandler', 'MetricHandler', 'ValidationHandler',
            'LoggingHandler', 'CheckpointHandler', 'EarlyStoppingHandler']
 
+
 class TrainBegin(object):
     def train_begin(self, estimator, *args, **kwargs):
         pass
@@ -434,7 +435,7 @@ def train_begin(self, estimator, *args, **kwargs):
         self.current_epoch = 0
         self.current_batch = 0
         if self.save_best:
-            self.best = np.Inf if self.monitor_op == np.less else -np.Inf # pylint: disable=comparison-with-callable
+            self.best = np.Inf if self.monitor_op == np.less else -np.Inf  # pylint: disable=comparison-with-callable
         if self.resume_from_checkpoint:
             error_msg = "To use resume from checkpoint, you must only specify " \
                         "the same type of period you used for training." \
@@ -670,7 +671,7 @@ def __init__(self,
                                  "if you want otherwise", self.monitor.get()[0])
                 self.monitor_op = np.less
 
-        if self.monitor_op == np.greater: # pylint: disable=comparison-with-callable
+        if self.monitor_op == np.greater:  # pylint: disable=comparison-with-callable
             self.min_delta *= 1
         else:
             self.min_delta *= -1
@@ -683,7 +684,7 @@ def train_begin(self, estimator, *args, **kwargs):
         if self.baseline is not None:
             self.best = self.baseline
         else:
-            self.best = np.Inf if self.monitor_op == np.less else -np.Inf # pylint: disable=comparison-with-callable
+            self.best = np.Inf if self.monitor_op == np.less else -np.Inf  # pylint: disable=comparison-with-callable
 
     def epoch_end(self, estimator, *args, **kwargs):
         monitor_name, monitor_value = self.monitor.get()