Updates

• config file from train.py accepts tensors as input
• TFRecord, add keyword argument to flag the shuffling mechanism
• Added InceptionResnetV1 in our basket of networks
• Added an option to sum the regularization losses in the CrossEntropy loss
• Implemented validation with embeddings (officially appending to the tensorboard)
• Created method Trainer.load_variables_from_external_model that load variables from another model in the current graph
• Implemented MeanSoftMaxLossCenterLoss (http://ydwen.github.io/papers/WenECCV16.pdf)
• Patched InceptionV2 (Added the flag trainable for each variable in the model)
• Implemented TFRecordImage (read, data augmentation, scaling and casting to float32)
• Added data type as input in the TFRecord datashufflers

bob/learn/tensorflow/script/db_to_tfrecords.py

@@ -85,11 +85,11 @@ import numpy
 
 
 def _bytes_feature(value):
-  return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
+    return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))
 
 
 def _int64_feature(value):
-  return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
+    return tf.train.Feature(int64_list=tf.train.Int64List(value=[value]))
 
 
 def bob2skimage(bob_image):