Change MyProgBarLogger to LoggerCallBack

examples/ocr/eval.py

@@ -23,7 +23,7 @@ from hapi.model import Input, set_device
 from hapi.vision.transforms import BatchCompose
 
 from utility import add_arguments, print_arguments
-from utility import SeqAccuracy, MyProgBarLogger, SeqBeamAccuracy
+from utility import SeqAccuracy, LoggerCallBack, SeqBeamAccuracy
 from utility import postprocess
 from seq2seq_attn import Seq2SeqAttModel, Seq2SeqAttInferModel, WeightCrossEntropy
 import data
@@ -91,7 +91,7 @@ def main(FLAGS):
 
     model.evaluate(
         eval_data=test_loader,
-        callbacks=[MyProgBarLogger(10, 2, FLAGS.batch_size)])
+        callbacks=[LoggerCallBack(10, 2, FLAGS.batch_size)])
 
 
 def beam_search(FLAGS):
@@ -140,7 +140,7 @@ def beam_search(FLAGS):
 
     model.evaluate(
         eval_data=test_loader,
-        callbacks=[MyProgBarLogger(10, 2, FLAGS.batch_size)])
+        callbacks=[LoggerCallBack(10, 2, FLAGS.batch_size)])
 
 
 if __name__ == '__main__':

examples/ocr/train.py

@@ -28,7 +28,7 @@ from hapi.model import Input, set_device
 from hapi.vision.transforms import BatchCompose
 
 from utility import add_arguments, print_arguments
-from utility import SeqAccuracy, MyProgBarLogger
+from utility import SeqAccuracy, LoggerCallBack
 from seq2seq_attn import Seq2SeqAttModel, WeightCrossEntropy
 import data
 
@@ -129,7 +129,7 @@ def main(FLAGS):
               eval_data=test_loader,
               epochs=FLAGS.epoch,
               save_dir=FLAGS.checkpoint_path,
-              callbacks=[MyProgBarLogger(10, 2, FLAGS.batch_size)])
+              callbacks=[LoggerCallBack(10, 2, FLAGS.batch_size)])
 
 
 if __name__ == '__main__':

examples/ocr/utility.py

@@ -102,31 +102,31 @@ class SeqAccuracy(Metric):
         return self._name
 
 
-class MyProgBarLogger(ProgBarLogger):
+class LoggerCallBack(ProgBarLogger):
     def __init__(self, log_freq=1, verbose=2, train_bs=None, eval_bs=None):
-        super(MyProgBarLogger, self).__init__(log_freq, verbose)
+        super(LoggerCallBack, self).__init__(log_freq, verbose)
         self.train_bs = train_bs
         self.eval_bs = eval_bs if eval_bs else train_bs
 
     def on_train_batch_end(self, step, logs=None):
         logs = logs or {}
         logs['loss'] = [l / self.train_bs for l in logs['loss']]
-        super(MyProgBarLogger, self).on_train_batch_end(step, logs)
+        super(LoggerCallBack, self).on_train_batch_end(step, logs)
 
     def on_epoch_end(self, epoch, logs=None):
         logs = logs or {}
         logs['loss'] = [l / self.train_bs for l in logs['loss']]
-        super(MyProgBarLogger, self).on_epoch_end(epoch, logs)
+        super(LoggerCallBack, self).on_epoch_end(epoch, logs)
 
     def on_eval_batch_end(self, step, logs=None):
         logs = logs or {}
         logs['loss'] = [l / self.eval_bs for l in logs['loss']]
-        super(MyProgBarLogger, self).on_eval_batch_end(step, logs)
+        super(LoggerCallBack, self).on_eval_batch_end(step, logs)
 
     def on_eval_end(self, logs=None):
         logs = logs or {}
         logs['loss'] = [l / self.eval_bs for l in logs['loss']]
-        super(MyProgBarLogger, self).on_eval_end(logs)
+        super(LoggerCallBack, self).on_eval_end(logs)
 
 
 def index2word(ids):

hapi/model.py

@@ -1267,7 +1267,7 @@ class Model(fluid.dygraph.Layer):
 
         if mode == 'train':
             assert epoch is not None, 'when mode is train, epoch must be given'
-            callbacks.on_epoch_end(epoch)
+            callbacks.on_epoch_end(epoch, logs)
 
         return logs