roywei commented on a change in pull request #14494: [MXNet-1340][Fit
API]Adding train history class
URL: https://github.com/apache/incubator-mxnet/pull/14494#discussion_r269801433
##########
File path: python/mxnet/gluon/estimator/estimator.py
##########
@@ -231,37 +221,45 @@ def fit(self, train_data,
validation data with data and labels
epochs : int, default 1
number of epochs to iterate on the training data.
- batch_size : int
- number of samples per gradient update.
- default will be 32 per device
event_handlers : EventHandler or list of EventHandler
list of EventHandlers to apply during training
batch_fn : function
custom batch function to extract data and label
from a data batch and load into contexts(devices)
"""
-
- self.epochs = epochs
+ self.max_epoch = epochs
if not batch_size:
- batch_size = 32 * len(self.context)
+ self.batch_size = 32 * len(self.context)
+ else:
+ self.batch_size = batch_size
+ self.stop_training = False
+ self.samples = None
+ self.batch_idx = 0
event_handlers = event_handlers or []
# provide default logging handler
if not event_handlers or \
not any(isinstance(handler, LoggingHandler) for handler in
event_handlers):
- event_handlers.append(LoggingHandler(self))
+ event_handlers.append(LoggingHandler())
- # training begin
+ train_begin, epoch_begin, batch_begin, \
+ batch_end, epoch_end, train_end =
self._categorize_handlers(event_handlers)
+
+ # passing estimator to event handlers so they can access estimator
information
+ # when a event is triggered
for handler in event_handlers:
+ handler.estimator = self
Review comment:
@nswamy This will avoid to ask user passing estimator during event handler
construction, reference:
https://github.com/apache/incubator-mxnet/pull/14462#discussion_r267125641
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