Add support for databases which contain more than one sample in one file

bob/learn/tensorflow/script/db_to_tfrecords.py

@@ -96,7 +96,7 @@ def _int64_feature(value):
 
 
 def write_a_sample(writer, data, label):
-    feature = {'train/data': _bytes_feature(data),
+    feature = {'train/data': _bytes_feature(data.astype('float32').tostring()),
                'train/label': _int64_feature(label)}
 
     example = tf.train.Example(features=tf.train.Features(feature=feature))
@@ -143,7 +143,7 @@ def main(argv=None):
                 logger.info('Processing file %d out of %d', i + 1, n_files)
 
                 path = f.make_path(data_dir, data_extension)
-                data = reader(path).astype('float32').tostring()
+                data = reader(path)
                 label = file_to_label(f)
 
                 if one_file_one_sample: